Alexander Johannes Warnecke Degradation Mechanisms in NMC

Aachener Beiträge des ISEA

Alexander Johannes Warnecke

Degradation Mechanisms in NMC-Based Lithium-Ion Batteries

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Degradation Mechanisms in NMC Based

Lithium-Ion Batteries

Von der Fakultät für Elektrotechnik und Informationstechnik der Rheinisch-Westfälischen Technischen Hochschule Aachen

zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften genehmigte Dissertation

vorgelegt von

Diplom-Ingenieur Alexander Johannes Warnecke

aus Brilon

Berichter:

Universitätsprofessor Dr. rer. nat. Dirk Uwe Sauer Universitätsprofessor Dr.-Ing. Michael Danzer

Tag der mündlichen Prüfung: 22. September 2017

Diese Dissertation ist auf den Internetseiten der Hochschulbibliothek online verfügbar.

Alexander Johannes Warnecke

Degradation Mechanisms in NMC Based Lithium-Ion Batteries

Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliographie; detailed bibliographic data are available in the Internet at: http://dnb.d-nb.de. Electronic version The electronic version is available online on the institutional repository of RWTH Aachen University (https://publications.rwth-aachen.de). D82 (Diss. RWTH Aachen University, 2017) AACHENER BEITRÄGE DES ISEA Vol. 105 Editor: Univ.-Prof. Dr. ir. Rik W. De Doncker Director of the Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University Copyright ISEA and Alexander Johannes Warnecke 2017 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without prior permission of the publisher. ISSN 1437-675X Institut für Stromrichtertechnik und Elektrische Antriebe (ISEA) Jägerstr. 17/19 • 52066 Aachen • Germany Tel: +49 (0)241 80-96920 Fax: +49 (0)241 80-92203 [email protected]

Vorwort

Diese Arbeit entstand im Rahmen meiner Tätigkeit als wissenschaftlicher Mitarbeiter am Institut für Stromrichtertechnik und elektrische Antriebe (ISEA) der RWTH Aachen, am Lehrstuhl für Elektrochemische Energiewandlung und Speichersystem-technik von Prof. Dirk Uwe Sauer. Während der fünfeinhalb Jahre am Institut hatte ich die Möglichkeit, in vielen Themenfeldern der Lithium-Ionen-Batterie zu arbeiten. Der Start mit Alterungsuntersuchungen und Modellierung hat sich als gute Grundlage für meine Dissertation herausgestellt. Viel Spaß machte aber auch die Zeit im Analyselabor, bei der Zerlegung und Untersuchung von Zellen.

Professor Sauer danke ich für Möglichkeit bei ihm im Themenbereich Batterien zu Promovieren und natürlich für die Betreuung während der gesamten Zeit. Herr Professor Michael Danzer danke ich sehr für die Übernahme des Korreferats und seine konstruktiven Anmerkungen zur Arbeit.

Solch eine Arbeit ist nie eine pure Einzelleistung. Allen Kollegen, Studenten und Projektpartnern aus dieser Zeit möchte ich für jegliche Unterstützung danken, ohne die dies nicht möglich gewesen wäre.

Die Arbeitsatmosphäre am ISEA ist eine ganz besondere. Neben den hohen Erwartungen an die Arbeitsleistung kommen Spaß und Miteinander nie zu kurz. Die Zeit am Institut werde ich sehr vermissen. Madeleine möchte ich danken, dass sie mich mit Studienarbeit und Diplomarbeit ans Institut geholt hat. Auch in den späteren Jahren hat sie mich stets als Abteilungsleiterin und Kollegin unterstützt. Die Laborzeit mit den Kellerkindern wird für mich Unvergesslich bleiben und kann so schnell nicht übertroffen werden. Zu den Kellerkindern zählen natürlich Kollegen und Studenten.

Spezieller Dank geht an Jens, Meinert und Luke für das fachliche Korrekturlesen. Auch wenn die Anmerkungen oft viel Arbeit verursacht haben, haben diese die Qualität der Arbeit gesteigert. Für die Überarbeitung in sprachlicher Hinsicht gilt mein Dank meinen Schwestern Christina und Annika, sowie wieder Luke.

Zum Schluss möchte ich mich noch meiner Familie und Freunden bedanken. Eure Unterstützung habt ihr gezeigt, indem es kein Problem war auch mal keine Zeit für euch zu haben, besonders in den kritischen Phasen der Doktorarbeit.

Aachen, im Oktober 2017 Alexander Warnecke

Introduction and Motivation i

Table of Contents

Introduction and Motivation .................................................................................. 1

Lithium-ion batteries ............................................................................................. 5

Working principle ........................................................................................... 6

Components of a lithium-ion battery .............................................................. 7

Anode ..................................................................................................... 9

Cathode ................................................................................................ 14

Separator .............................................................................................. 18

Electrolyte ............................................................................................. 20

Ageing behavior of NMC-based cells ................................................................. 23

Cell of investigation ..................................................................................... 23

Electrical properties .............................................................................. 24

Initial characterization and post mortem analysis ........................................ 27

Acquiring geometrical data ................................................................... 30

Identification of material composition .................................................... 34

Description of morphology .................................................................... 37

Electrical electrode characteristics ........................................................ 39

Accelerated ageing analysis ........................................................................ 41

Concept of accelerated ageing ............................................................. 41

Ageing behavior in storage conditions .................................................. 42

Ageing behavior in cycling conditions ................................................... 47

Variability in ageing curves ................................................................... 57

Separation of degradation behavior............................................................. 59

Influence of the cell design on degradation ........................................................ 61

Spatial resolved measurements of lithium concentrations ........................... 62

Importance of delivery conditions ................................................................ 64

Influence on calendric ageing ...................................................................... 67

Influence in cycling conditions ..................................................................... 71

Approach for calculation of geometry caused transition .............................. 72

Passive electrode in automotive cells .......................................................... 76

Linearized degradation ....................................................................................... 79

ii Degradation Mechanisms in NMC-Based Lithium-Ion Batteries

Rapid cell break down ........................................................................................ 85

Lithium plating ............................................................................................. 85

Post mortem of cell in the linear degradation phase .................................... 86

Post mortem of cells with break down ......................................................... 87

Model approach for cell break down ............................................................ 89

Ex ante assignment of degradation effect .......................................................... 93

Electrical impedance spectroscopy (EIS) .................................................... 93

Differential voltage analysis (DVA) .............................................................. 94

Dissolution of transition metals .......................................................................... 99

Driver for dissolution of transition-metals ..................................................... 99

Dissolution by HF ................................................................................ 100

Disproportion reaction ......................................................................... 100

Effects of re-deposition on the cathode ..................................................... 101

Impact of material loss on cathode capacity .............................................. 102

Effects at the anode/electrolyte interphase ................................................ 102

Measurement techniques for identification and quantification of dissolved transition metals .................................................................................................. 103

Impact of stress factors ............................................................................. 105

Influence of temperature and SoC ...................................................... 106

Influence of cycling depth and current rate ......................................... 110

Conclusion for influence of dissolution on overall cell ageing .................... 114

Advice for improved operation strategy in electric vehicles ................. 115

Structural changes ........................................................................................... 117

Ideal and real structure of NMC ................................................................. 117

Identification of crystal structure ................................................................ 119

Structural changes due to lithium insertion and extraction ........................ 120

Structural changes in storage .................................................................... 124

Structural changes by usage ..................................................................... 126

Summary of structural changes ................................................................. 127

Electrolyte decomposition on the cathode .................................................... 129

Gravimetric analysis of the CEI .............................................................. 130

Thermo-gravimetric analysis of the CEI ................................................. 132

Introduction and Motivation iii

Current collector corrosion ............................................................................ 137

Dissolved aluminum ............................................................................... 137

Optical analysis ...................................................................................... 139

Comparison of method ........................................................................... 141

Influence on cell degradation ................................................................. 141

Conclusion and outlook ................................................................................ 143

Bibliography .................................................................................................. 145

Appendix ....................................................................................................... 157

Own Publications ................................................................................... 157

Scientific Journals ............................................................................... 157

Conference Publications ..................................................................... 157

Supervised Thesis .................................................................................. 158

Introduction and Motivation 1

Introduction and Motivation

“Climate change is happening, humans are causing it, and I think this is perhaps the most serious environmental issue facing us” – Bill Nye “The Science guy”

“We're running the most dangerous experiment in history right now, which is to see how much carbon dioxide the atmosphere (..). can handle before there is an

environmental catastrophe.” – Elon Musk

The above-stated quotes illustrate that climate change is an important issue on the agenda of researchers as well as economical world leaders. To stop global warming, major changes need to occur in the sectors of energy, industry, agriculture, and transportation. One of the highest impact and widely discussed topics is the decreased use of fossil energy sources for the transportation sector. At the moment, petroleum is the main source of energy for transportation with around 95% [1].

Typical combustion engines have improved drastically since the invention in 1883, but the typical efficiency in today’s vehicles is still low. One way to reduce the usage of fossil fuels is using electric powered vehicles, where energy comes from high efficient power plants or even better, from renewable energy. To store the electric energy in the vehicle, two main techniques are in favor for the next decades: hydrogen fuel cells and batteries [2]. Self-evidently, both techniques have advantages and disadvantages. As an example, the refueling of fuel cell vehicles with liquid hydrogen can be accomplished with fast filling speeds; whereas the charging of battery powered vehicles ranges from half an hour to several hours. In contrast, the erratic power demand of vehicles shortens the lifetime of a fuel cell, which cannot be seen for battery electric vehicles. However, the price and absence of a hydrogen infrastructure led to a higher market share for battery electric vehicles (BEV).

Currently lithium-ion batteries are used as an energy storage in BEVs, but as it can be seen from the high prices for electric vehicles they are not competitive as compared to vehicles with combustion engines (Tesla Model S 60 starting at 69,019 € [3] vs. BMW 5er starting at 45,200 € [4]). Batteries are the most cost intensive component of these automobiles [5]. To build affordable electric vehicles, many manufacturers sell cars with a small battery resulting in lower ranges (around 150 km) [6].

To justify such high investments, the most important and cost intensive component of a BEV should have an exceptionally long lifetime. However, testing batteries for ten to twenty years is not possible for manufacturers who aim to stay competitive concerning the rapid development of new and innovative vehicles. For them it is of

2 Degradation Mechanisms in NMC-Based Lithium-Ion Batteries

crucial importance to understand and gather lifetime results in a rather short period. Unfortunately, the results of small lab cells differ significantly from that of full cells of an adequate size and type. The degradation mechanisms seem to change so that cost-intensive tests of the later cells cannot be omitted. As a result, it is necessary to find a way to attribute the degradation of commercial lithium-ion batteries to the results of lab cells, tested in research.

The following thesis is aimed at the ageing of a commercial lithium-ion battery, with a special focus on the influence of the positive electrode (cathode). A schematic of a degradation curve for commercial cells is graphically depicted in Figure 1. As one can see the degradation is split up into three phases starting with a possible influence of the geometry of the cell and ending with a rapid break down. The linear graph signifies the material degradation. The focus of this work is on the linear region. It is intended to associate the three phases with the ongoing degradation effects, which is done by electrical testing and post mortem analysis.

Figure 1: Schematic overview of the divided ageing regions of Nickel Manganese Cobalt (NMC)-based lithium-ion battery. After how much capacity loss (X%) the third phase starts differs for each battery type.

The commercial cell design used for the analysis of the following thesis is a 20 Ah cell from the Korean manufacturer EIG. With regards to the cathode materials, the current and most widely used material group was chosen [7]. The material belongs to a class definite as Layered Transition Metal Oxides. The crystal structure consists of consecutive layers of oxygen, lithium and the transition metals. The widely used transition metals are nickel, cobalt, manganese and aluminum. Starting point for materials with a combination of transition metals was an Li(NixMnyCoz)O2 (NMC) with

Introduction and Motivation 3

the ratio of 1:1:1 [8], but due to cost constrains of cobalt the share of cobalt was reduced while the share of nickel was increased. Furthermore the energy density of the active material was improved by the higher share of nickel [9]. The following thesis focuses on the ageing of a cathode with a 4:4:2 NMC, which is an advanced development and potentially active material for automotive applications.

The structure of this thesis is organized as follows. Section 2 provides an introduction to the lithium-ion battery and the deployed materials. Furthermore the theoretical framework of degradation mechanisms is outlined. After a detailed elaboration of the analyzed cell, the degradation behavior under several stress parameters is presented. Moreover, the identification of different ageing phases and a fitting of degradation parameters is presented in the following ageing section. Aforementioned phases one and three (Figure 1) are explained in detail in separate sections (4; 6). Degradation mechanisms for the cathode as discussed in literature are analyzed and separately discussed. Finally, the identified cathode degradation mechanisms and their impact on the full cell behavior are evaluated. In addition, the approach of dividing the degradation curve is reviewed.

Hitherto, no overall ageing study could be found in literature that separates the degradation of the cell and assigns the capacity loss and resistance increase to an on-going material ageing. A lot of research has been done at the material level, so that the effects are known in general, however, using multiple techniques and combining the findings to explain the full cell degradation is a new approach.


Lithium-ion batteries 5

Lithium-ion batteries

Lithium-ion batteries are today’s dominant technology in the field of automotive batteries. Since the first fundamental research in the early 1970s [10] and the commercial introduction by Sony 1991 [11], the properties have improved considerably. Today there is not “one lithium-ion battery” but several positive and negative electrodes that use the functional principle of exchanging lithium ions. This enables manufacturers to tailor a battery for the specific demands of an application. This multitude of material combinations makes universal conclusions on the properties impossible. For comparison, the cell that is used in the Tesla Model S has a nominal capacity of 3.15 Ah1, nominal voltage of 3.7 V and an energy density of about 245 Wh kg-1. In contrast, a cell for a stationary storage from Leclanché has a nominal capacity of 60 Ah, nominal voltage of 2.3 V and an energy density of about 70-80 Wh kg-1 [12].

Figure 2: Safe operating window of a lithium-ion battery. If the safe operation window is left, the ageing drastically increases. Exceeding these limits of safety result in problems.

In comparison to many other battery technologies, lithium-ion batteries require monitoring of the cell voltage and temperature while in use. This is a result of the very small safe operational window, which is represented graphically in Figure 2. If operation leaves this safe operational window, various side reactions in the battery 1 Capacity measured with a cell from a Tesla Model S P85 from 2013 at ISEA


take place. Some of these effects just shorten the lifetime by increasing the ageing, like medium high temperatures and slightly higher state of charge (SOC) of the battery. Other effects, like lithium plating, are a direct risk for the cells safety as internal short-circuits may occur and with this the potential risk for fire increases. Low voltages of a deep-discharged cell do not lead to safety issues in many other technologies, however they are problematic for lithium-ion cells. The current collector of the anode starts to dissolve and thus can also lead to an internal short-circuit by dendrite formation of this material. Extremely high temperatures can lead to thermal runaway of the cells, hence, this should also be avoided. Beside all these negative consequences, the wide range of lithium-ion cell designs deliver the best performance at a reasonable price relative to all other currently available battery technologies.

The following chapter explains the working principle and the components that are used in lithium-ion batteries to the degree that is necessary for a solid understanding of the subsequent chapters. Furthermore, the known ageing aspects of the materials are described briefly. Due to its overall importance for the thesis, the cathode related degradation mechanism will be explained and discussed in a wider range in sections 8 to 11.

Working principle

Lithium-ion batteries consist of two electrodes – anode and cathode – that are acting as insertion hosts for lithium ions. The Electrolyte is responsible for the ion transport and the porous separator for the electric insulation of the two electrodes. These components are shown in the schematic overview in Figure 3. When the battery is charged or discharged, the lithium ions are exchanged between the electrodes and do not undergo a chemical reaction. The absence of a chemical reaction within the charging and discharging process results in the high reversibility and hence the long lifetime. Any chemical side reactions are undesired and are considered as degradation effects. When a battery is assembled, all lithium is located in the crystal structure of the positive electrode (cathode), which are typically lithium metal oxides (e.g. LiNixMnyCozO2, LiCoO2), spinels (e.g. LiMn2O4) or phosphates (e.g. LiFePO4). While charging the battery the first time, the lithium ions move to interstitial sites of the negative electrode (anode), which is generally a graphite material. The transport of the ions is done by a non-aqueous electrolyte, consisting of a conductive salt, lithium hexafluorophosphate (LiPF6) [13], in carbonates. The porous separator is not participating in the reaction, but has influence on the length of the path from cathode to anode by its structure and with this, on the internal resistance of the battery.

The potential range of a graphite anode exceeds the stability window of the electrolyte at lower potentials. Within the lithiation process the potential during normal

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electronics lowered the price for cylindrical cells and also the availability, so that it was the first choice for the company Tesla [17]. The metal housing of the cylindrical cell has a defined geometry and the production of rolled electrodes currently has the highest output speed, which makes it suitable for cheap mass production [18]. The second alternative is the prismatic cell, a hard case housing in a prismatic form. The electrodes are also rolled inside, without a roll shaft, but the form of the housing and the connection terminals facilitate the integration into a battery pack. Accordingly, these types of cells are commonly used in vehicles (e.g. Mitsubishi iMiEV). One big advantage of the prismatic form is the defined geometry, it enables engineers to easily design battery packs with a building block principle without leaving much unused space. Further, the metallic case of around 0.5 mm thickness allows a good heat transfer for a simple thermal design approach. A drawback of a prismatic case is the low usage of space, resulting in a low volumetric energy density. The filling volume of the rolled electrodes is low, compared to the total cell volume resulting in unused volume inside the housing. Furthermore the big amount of housing weight, compared to active material, leads to lower energy densities. The third version of housings is the pouch cell (also known as “coffee bag cell”), which is a soft case cell. The electrodes are typically stacked but also appear to be rolled in small cells and then covered by a PE/PP laminated aluminum foil, typically about 100 μm in total thick2. The inside of a pouch foil is poly ethylene, which is melted for a good sealing of the cell. In addition to that the outside of the aluminum is covered in poly propylene for durability of the housing. This kind of case is light so that the highest gravimetric energy densities can be achieved. A disadvantage of this thin housing is the low mechanic stability. When gas is formed in the cell, due to an undesired event or when it ages, the bag typically bulges so that the cell loses the defined form. In contrast to the hard case cells, pouch cells are not having an over pressure value to release these gases. This losing of a defined geometry disqualifies the cell for many automotive companies. The sensitivity of the cells on the pressure or force from the outside is also critical for all applications with a variation of ambient pressure, like aviation or aerospace.

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metallic electrode when deposited in the charging process, resulting in even more active surface for electrolyte reduction. These dendrites have a high risk of producing internal short-circuits, which can be regarded as a huge drawback regarding the safety of the battery system.

An alternative to the metallic lithium electrodes are intercalation compounds. These are electrode materials where a stable host structure remains nearly unchanged when the lithium guest ion is inserted or extracted. So various host materials like transition-metal oxides, chalcogenides, lithium alloys, and carbons can possibly be used, but all have a higher potential against metallic lithium (vs. Li/Li+) [10]. Additionally the weight of the host structure has to be considered as an inactive component, as it is not directly participating in the reaction and therefore lowering the energy density of the electrode.

Carbons nowadays are the most widely used anode materials in commercial cells, more specifically graphite. Hundreds of types of graphite materials are available for lithium-ion batteries; they vary in particle size, crystallinity, manufacturing (natural and synthetic), impurities and structural defects, but they are all layered materials [20, 21].

The graphite particles are composed of small monocrystalline areas called crystallites. They consist of stacked graphene layers, which are a two dimensional, hexagonal lattice of carbon atoms with a thickness of one atom. At ambient conditions (pressure and temperature) the maximum content of one lithium per six carbon host atoms can be intercalated as it is shown in equation (1):

(1)

The intercalation of the lithium ions is processing through the open surface between the graphene planes and only on defects through the planes [22]. This makes graphite a two dimensional compound, where the ions can travel in plane between the graphene layers. While charged, the AB structure (Figure 5 left) is shifted to an AA structure (Figure 5 right) by the interlayer lithium atoms. Consequently, two neighboring graphene layers then directly face each other. The distance between the two graphene layers widens in a fully lithiated state by about 10.3 % [10]. The lithium is distributed in the plane in such way that it has the farthest distance to its direct neighbor as it is shown schematically on the right side of Figure 5.


Figure 5: Structure of graphite without lithium on the left and as LiC6 on the right. The schemes on the top show a side view of the graphene layers and the figures on the bottom show a top view on the layers. Without lithium the stacking order is AB and with lithium AA with a higher layer distance.

One characteristic of graphite is the step-wise occupation of graphene interlayers by lithium. The thermodynamics lead to the stageing effect, a step-wise process where the stage index s indicates the number of graphene layers between two nearest guests. It is related to the energy that is required to expand the van-der-Waals gap between two graphene layers and the repulsive interactions between the lithium atoms. It is preferred to have a few highly occupied layers rather than a random distribution of the guest species. The described stages can be observed in the charge/discharge curves of the graphite (Figure 6). A plateau indicates a region where two stages exist in parallel. Considering the real measurement, the voltage changes show no sharp edges due to in-homogeneities and over potentials.

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A completely different approach for an active material is lithium titanate oxide (LTO). This material is an intercalation compound where lithium is stored in the crystal structure. The insertion and extraction is done at 1.5 V vs. Li/Li+ [25]. The material has the highest voltage level of the anode materials that are used for lithium-ion batteries, which results in a lower total cell voltage and with this lower energy density. Beside low energy density of cells with an LTO electrode, the lifetime appears to be outstanding, which can be attributed to two reasons. Firstly, the electrolyte is stable at the high potentials so that the absence of decomposition leads to the absence of the most prominent degradation mechanism. Secondly, the material is not undergoing any volume changes so that it is classified as “zero-strain” material [25]. The material is used in cells that have a high Ah-throughput, for example, in electric busses, trains, or in stationary applications where the energy density is a minor parameter.

In the past, a lot of research was done on the stability of the graphite anodes and the reduction of SEI losses, as it is the main degradation process in the batteries. Further ageing processes are cracking of the particles, loss of contact, and lithium plating. For further information on degradation of graphite electrodes in lithium-ion batteries one can refer to the thesis of Münnix [26] or further literature [27-30].

As mentioned earlier, the surface layer is formed mainly in the first cycle, when the potential of the anode is below the stability of the electrolyte components. While the battery is used or stored, the SEI formation is continuing. The state of the art explanation for this is, that the SEI is not a perfect insulator and with this, some electrons are transferred to the electrolyte, where further reduction takes place [31].


Figure 8: Changes at the anode/electrolyte interphase [27].

Cathode

The previous section elaborated on the diversity of anode materials. In comparison the plurality of possible cathode materials is much higher. Beside the materials used currently, a plethora of new materials appear to be usable for lithium-ion batteries. The small radius of a lithium-ion enables insertion into many host materials. Alongside the improvements of current materials, new intercalation cathodes with multi-electron processes have come into focus of researchers [32, 33]. The commercialization of these materials are planned in the future, this is why this thesis covers the degradation of existing materials. The materials used today can be grouped by their crystallographic structure, which can be layered oxides, spinels or olivine materials. As each of these material groups has different properties. Therefore, each has a specific application.

Lithium iron phosphate (LiFePO4), or LFP for short, is the most prominent material of the olivine structure class. It has an energy density of about 170 mAh g-1 and a nominal voltage of 3.45 V against metallic lithium (vs. Li/Li+). The olivine structure allows a diffusion of lithium ions in all three dimensions within the intercalation or extraction. Despite this property the electric conductivity of the LFP is poor [34, 35]. Two approaches are used to solve this issue. The first one is coating with diverse graphite materials and the second is decreasing the particle size which often leads to the use of nanoparticles [36]. With these afore-mentioned methods LFP provides sufficient energy density and power capability which is used mostly in hybrid vehicles like the Fisker Karma or the BMW Active Hybrids [7]. The precursors of the lithium


iron phosphate are cheap compared to other cathodes which contain rare earth elements. From a safety perspective, LFP cathodes show a good feature. The high heat stability comes from the efficient bonding of oxygen in the structure, so that LFP material itself is not feeding a thermal runaway [37]. Contrary to this, the cell system itself can undergo a thermal runaway.

Spinels are mostly represented by lithium manganese oxide (LiMn2O4 or LMO). This material has a relatively low capacity density of around 120 mAh g-1, but an above average voltage of 4.1 V vs. Li/Li+ [38] and with this an energy density up to 480 Wh/kg [39]. It shows a good thermal stability when heated as a result of the high manganese content [40]. This is important for safety concerns. A slower thermal runaway helps to detect high temperatures in problematic cells and counteract. The material suffers from poor cycle life and calendric ageing at high temperatures and voltages, caused by the dissolution of manganese [38]. This is described for NMC in section 8. One way to tackle the dissolution problem is the use of LMO as a blend in combination with other materials; layered oxides for example. Such a blend is used in the most widely sold electric vehicle, the Nissan Leaf3.

The general formula for layered oxides is LiMO2 in which the M stands for several possible metals or a mix of them. These materials are represented by lithium nickel manganese cobalt oxide (LiNixMnyCozO2 or NMC) and lithium nickel cobalt aluminum oxide (LiMnxCoyAlzO2 or NCA) [7]. The layered oxides show the best properties for mobile applications. These are a high energy density and a long lifetime. The majority of current electric vehicles are equipped with batteries that are using layered oxides as cathode materials, pure or in a mix together with other materials [7]. The advantage of this material group is the adaptability towards the desired application. The share of transition metals is the key parameter to adjust the properties [41]. The typically applied materials are nickel, manganese, and cobalt, whereas each of the components favor some properties. Cobalt stands for high voltages, nickel delivers higher capacities and manganese is adding safety [41]. The materials are not participating in the reaction of the lithium-ion battery itself but take a supportive role. When lithium is removed from the structure, oxygen atoms change their binding towards a transition metal which is then going into a higher oxidation state. If manganese is present in the form of Mn4+, which is the highest oxidation state of manganese (source). As a result, manganese cannot be further oxidized, so that it is not participating in the process. By its absence in the oxidation process, manganese keeps the crystal structure stable, which is associated with a longer lifetime of the material. Nickel changes its oxidation state at a low voltage level up to 3.8 V against metallic lithium from Ni2+ to Ni4+ when lithium is removed from the structure. Cobalt

3 Cells from a Nissan Leaf of unknown building date were measured at ISEA. The cathode consisted

of a LMO/NMC blend.


changes its oxidation state at higher voltages from Co3+ to Co4+ [20]. The participation at different voltage levels explains changes in the charging and discharging voltage curves, so that with a different composition of the cathode material the characteristic of the battery change. For the 1:1:1 NMC, nickel participates in the first two thirds of the charge and after this, the cobalt is predominantly oxidized further [41]. If more than 70-80% of lithium is extracted the crystal structure changes dramatically, releases oxygen and produces heat, which can be seen as thermal runaway when a lithium-ion battery with layered oxide cathode is overcharged [42].

While charging and discharging, the crystal structure undergoes minor changes due to the lithium insertion and extraction. The total volume change is low, so that stress in particles is low, resulting in a long cycle life. The volume expansion accounts for 1% to 3% [43-45], depending on the reports. Our own calculations for the structural changes between charged and discharged are introduced and explained in section 9. With 1.7%, the measured results are in accordance with aforementioned literature.

The first layered oxide that was used in a commercial cell was LiCoO2 (LCO), which has a high nominal voltage of 3.9 V and a capacity density of 150 Ah kg-1. However, it demonstrates an insufficient cycle life and safety behavior for automotive applications [46]. Despite the negative properties, the material is still used for mobile consumer electronics up. Driven by the high cobalt prices and the cycle life performance alternative materials were investigated. The alternative material is a mix of the transition metals cobalt, nickel and manganese, which enhances several properties. Considering the first introduced material all elements had the same share, why it is called 1:1:1. The notation always describes the share of the transition metals. The ratio of the transition metals to lithium is always 1:1, except for lithium rich materials. Lithium rich materials have a higher share of lithium, which improves the energy density, but also adds the problem of a suppressed spinel structure, which leads to high irreversible losses within the first charge. At the moment, the materials are subject of research and not commercially used. The reason for that is the low cycle life of only a few hundred cycles [47]. As described by Li et al. [9] the combinations are manifold. It is claimed that the 4:4:2 NMC shows a better performance as compared to the 1:1:1. Additionally the cobalt content is lowered, which is important for the cost of the materials. Cobalt is a rare earth material that is mainly mined in the Congo [48]. This makes it expensive and hence the absence of this material is desired. The current trend for layered cathode materials is to use higher nickel contents. They have a high energy density, higher possible capacity, and superior thermal stability [49]. Unfortunately most of the electrolytes are not stable if 4.2 V are exceeded. Therefore, increasing the upper cut-off voltage is an ambitious aim for new cathode materials. Recently the group around Jeff Dahn explained the capacity loss by electrolyte decomposition at the cathode and formation of gas, especially CO2 [50].

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allow ionic transport through the electrolyte from one electrode to the other. It is a porous membrane that is chemically and electrochemical stable against the electrodes and the electrolyte, especially under strongly oxidative and reductive environments [55]. The material should deliver a high porosity with a sufficient mechanical strength. By its presence in the ionic path, it extends the transport path and with this, has influence on the resistance of the cell system.

The thickness of the separator is its most important property, due to the influence on the energy density and specific energy. At the moment the standard thickness is about 25 μm, down to 10 μm for high energy applications [56]. Also a uniform thickness is important to prevent inhomogeneous charging of the electrodes. The porosity should be sufficient to hold enough electrolyte and not lengthen the ionic path between the electrodes too much. Common separators have a porosity of 35-45% [56]. The size of the pores should not vary too much in order to maintain the same size and tortuosity for an even current distribution. Pore sizes smaller than the smallest particles of the active materials are preferred. Particles for most active materials are in a μm-scale and additive components in a nm-scale. A typical pore size of a commercial separator ranges from 30-100 nm [56]. The mechanical strength is especially important for the assembly, the penetration or failure case, higher mechanical strength is desired for a safe and long lasting battery.

With respect to the composition and structure, separators can be divided into three types: microporous polymer membranes, non-woven fabric mats, and inorganic composite membranes. Nearly all microporous polymer membranes used in the current batteries are based on semi-crystalline polyolefin materials including polyethylene (PE) [57, 58], polypropylene (PP) [59-61] and their blends such as PE-PP [62-64]. The main difference with regard to their property is the melting point of the materials. The PE separators are thermally stable up to 120-130 °C, the melting point of PE. In contrast PP separators can be used up to the melting point of 165 °C. A combination of these materials is used in the PE-PP separators, where the difference in the melting point is used to provide the shutdown property. At least one PP layer is responsible for the mechanical stability at temperatures above 130 °C. The PE fills the pores and blocks the ionic path locally so that a thermal runaway can be prevented if the temperature rise is slow enough. These shut down separators are produced as a PE-PP bilayer or PP-PE-PP trilayer [56].

Non-woven fabric mats like glass fiber mats are often used in lab cells. The large thickness of about 300 μm reduces the power for commercial cells too much, by an extended diffusion path. In lab scale batteries, the higher thickness improves the reproducibility by pardoning misplacements or lithium dendrite growth at the metallic lithium counter electrode.


Inorganic composite separators, also named ceramic separators, consist of a mat of fine ceramic particles bonded by a small amount of binder. They are also often used in combination with polymer membranes [65]. Only a small amount of commercial cells use ceramic separators, for example Leclanché or Litec [66].

Electrolyte

The ion transport media in a lithium-ion battery can be realized in a solid, liquid, or gel state. The solid electrolytes have a high ionic resistance. Their use requires higher temperatures. The latest developments make it possible to use them also at room temperature [67]. Major advantages of these electrolytes are their non-flammability and high mechanical strength. This results in an increased safety level. Upscaling for commercial cells is still a challenge because at the moment, the common processes are not capable for high production speeds. Within the next years these materials will probably enter the mass market of lithium-ion batteries. The second big group of electrolytes are the gel electrolytes - or polymer electrolytes. They function as a hybrid between the solid and the liquid ones. The main advantage of a polymer is that it would not leak if the cell case is damaged. Many lithium-ion batteries are labeled polymer [68], but there not yet a sharp definition for it.

The last and most important electrolyte group are the liquid electrolytes. The high working potentials of the common active materials exclude water based electrolytes, as water would be electrolyzed above 1.23 V (against standard hydrogen electrode or SHE) and the typical voltages in lithium-ion batteries are exceeding 3.0 V. Moreover the ionic liquids form an interesting as they are thermodynamically stable over a wide voltage range so that a use in high voltage cells is possible. For these, no solvent is necessary, but the molecules are large, so that the internal resistance is increased [55]. The ongoing research on these liquids aims to improve the properties like conductivity, but especially replace the most costly components. Ionic liquids are far more expensive than organic electrolytes so that they are not used in commercial cells at the moment.

The electrolyte of commercial lithium-ion batteries is typically a non-aqueous liquid that is based on organic solvents which are expensive compared to the other cell components and also flammable. An ion conductor is added that is responsible for the conductivity of the electrolyte. Nearly all batteries comprise the conductive salt LiPF6 in a 1 - 1.2 molar solution [55]. The electrolyte properties depend on the used solvents, the conductive salt and its molarity. Typically used solvents are ethylene carbonate (EC), propylene carbonate (PC), vinylene carbonate (VC), ethyl methyl carbonate (EMC), dimethyl carbonate (DMC) and diethyl carbonate (DEC) [14]. PC, VC and EC are cyclic carbonates, which are added for proper film formation [10]. PC was used at the begin of the commercialization of lithium-ion batteries, it was later replaced by EC because of the better properties to form a stable SEI on the anode


[10]. EC typically decomposes at a potential of 0.8 V against metallic lithium and with this exhibits a higher decomposition voltage as compared to other applied solvents. This leads to an early decomposition of EC during the first charge but hardly any reduction of other solvents. To improve the film formation, other cyclic carbons are used as additives in a small amount, like VC. It decomposes at 1.5 V against lithium and with this even earlier than EC [69]. The list of used additives and likewise properties that should be improved is nearly endless. A good overview on additives is given in [14]. The exact list of deployed additive compounds is a secret of the manufacturers and thus hard to find in a post mortem analysis. One example for another additive used is biphenyl. When the battery is overcharged it is decomposed at the cathode and increases the resistance so that the overcharging is suppressed.


Ageing behavior of NMC-based cells 23

Ageing behavior of NMC-based cells

Basis of the degradation studies are the measurements at an exemplary NMC-based cell. The dominant degradation mechanisms are investigated with electrical test methods and post mortem analysis. Further, the limiting electrode is identified. Knowledge about these mechanisms is necessary to improve the current and next generation materials in lithium-ion batteries. Therefore, ageing tests have been conducted over a time span of more than three years. The materials of these cells have been analyzed to study the degradation on electrode level to have a good insight into the ongoing reactions.

Cell of investigation

The selected cell, EIG ePLB C020, was used in the European research project Batteries2020 [70]. Many of the results are originally from the work done in that research project. The EIG pouch cell has a nominal capacity of 20 Ah, a nominal voltage of 3.65 V, and an energy density of 174 Wh/kg [68].

Figure 11: Photo of the EIG ePLB C020 cell with contact holes at the connection tabs after testing within the preparation for post mortem analysis. The numbers on the scale mat are cm.

The EIG ePLB C020 cell has a NMC-based cathode and a graphite based anode. The used material at the positive electrode is identified as an NMC material with a 4:4:2 composition (see 3.2), which means that the transition metals are distributed to 40 % nickel, 40 % manganese and 20 % cobalt. This is a known composition optimized for higher storage capacities compared to 1:1:1 composition [9]. The anode comprises of a graphite type material with an additive vapor grown carbon fibers (VGCF) to improve electrical conductivity, as seen in Figure 19 where the fibers are visible on top of the anode particles.


Electrical properties

The primary electrical properties are the maximum charge voltage of 4.15 V and the minimum discharge voltage of 3.0 V. These are defined by the manufacturer. The currently recommended charge from EIG is 0.5 C, which would not be suitable for fast charging in electric vehicles. The charge would last at least two hours. In the tests, currents up to 2.5 C in pulse tests are used for identifying the internal resistance in check-ups and up to 2 C as constant charge discharge currents in ageing test. The discharge curves at different C-rates are given in Figure 12. For higher discharge rates of more than 0.2 C, the internal resistance leads to a high polarization, so that the end of discharge voltage is reached earlier, causing a strong dependency of the usable capacity from the current rate. This is an important reference, so that comparable cycling in a selected SOC range is done best when controlled by Ah-throughput.

In addition the pulse resistance curve is illustrated, from 10% up to 100% SOC in charge and discharge direction for pulses of 1 C for 10 s. The voltage change after 10 s, compared to the equilibrium state, is divided by the flowing current of 1 C and results in a dynamic resistance of the cell. Due to tolerance in timing of the voltage and current measurement, this parameter typically shows a high variance, even for one cell4. The variation of ± 5% is difficult to evaluate, but with respect to the later following resistance curves over ageing, one can assume that there is no important difference between the cells. A clear SOC dependency is notable in the graph. In the lower SOC range up to 50%, the resistance in discharge direction is higher, which can be explained by the fact that lithium extraction is harder if less lithium is in the graphite structure. In the range of 60% - 70% the internal resistance rises which is assigned to the pure phase of the graphite anode in that range. The sudden decrease of the charge resistance for 100% SOC can only be explained by the onset of the lithium plating reaction. This indicates a high probability for plating when the cell is charged with higher current rates.

4 This can be seen in the fluctuating resistance curves over ageing as they are depicted in sections

3.3.2 and 3.3.3.


Figure 12: On the left, the voltage characteristics at 25 °C of a cell at different current rates over the discharged capacity is shown. The current rate ranges from 0.2 C to 2 C, as these were the used rates for ageing the cells. On the right, the pulse resistance (1 C, 10 s) values over the SOC range, for a fresh cell at a temperature of 25 °C are plotted. The discharge is given in blue and the charge in red.

The open circuit voltage (OCV) also gives an impression about the polarization voltages at 0.2 C. As seen in Figure 13, the polarization is higher for lower SOC, which corresponds with the measured pulse resistance values.

With these basic properties, the electric behavior can be described and implemented in an electrical model and as a basis for an ageing model as it is described by Schmalstieg et al. in [71] for different NMC cell. A modification of this ageing model is used in section 5 to describe the dependency of the capacity loss from the stress parameters.

0 5 10 15 20Capacity in Ah

3

3.2

3.4

3.6

3.8

4

4.20.333 C Discharge0.2 C Discharge1 C Discharge2 C Discharge

0 50 100State of Charge in %

1.5

2

2.5

3

3.5

4

4.5

5

5.5Discharge directionCharge direction


Figure 13: Low current charge and discharge curves (0.2 C) over SOC and OCV measurements over the SOC. The polarization of the low current discharge can be seen in the deviation from the equilibrium voltage values.

Up to now, there is no report found where exactly this cell is used in an electric vehicle. One prototype on the basis of a Piaggio Ape was built in Italy by Prof. Davoli. In the 60,000 kilometers driven, no battery caused failures were reported [72]. The company EIG is currently delivering batteries for the Tata electric vehicle; so it can be assumed that a similar cell is used in their electric vehicle [73] .

For a valid statement about the lifetime of a certain cell type, a variety of tests have to be done with several batteries. To ensure the comparability of these measurements, the variation between the tested cells should be small. For this, two electrical parameters from the beginning of life tests are compared. The first parameter shown in Figure 14 a) is the pulse resistance, which is measured at 50% SOC in discharge direction. Furthermore there is no literature known, given any information about a correlation between quality of the cell and their internal resistance at begin of life. Baumhöfer neither found a direct correlation of this parameter with the capacity nor a resistance trend [74]. The second parameter, which is also monitored over ageing, is the capacity, depicted in Figure 14 b). The initial values have a small variation of ± 1%. This would be an indication for a stable cell production or that the cells are matched by the manufacturer before shipping to the customers, which is a common proceeding in the automotive industry. Due to this small variation, a further selection before starting the tests was not necessary. Even over the testing time, no cell made the impression of a different ageing mechanism caused by differences in production.

Beside the electric parameters at begin of life, the weight at inventory was also compared. A difference in this parameter would indicate problems at the production side. Variation in the cell weights would mainly arise from a difference in the filled electrolyte. The weights of the solid components for opened cells were compared

0 20 40 60 80 100State of Charge in %

3.0

3.5

4.0

OCV in Discharge directionOCV in Charge directionQOCV in Discharge directionQOCV in Charge direction


and no notable difference occurred between the cells in a fresh state. The electrolyte amount has a minor impact if it is sufficient for wetting the complete electrode area. The histogram plot of the cell weight without any decals or connections is shown in Figure 14 c). The low variation of ± 0.5% indicates that the cell filling is homogeneous and no influence on the ageing behavior should be expected.

Figure 14: Distribution of the pulse resistance, capacity and weight of the 60 delivered cells at beginning of life. The pulse resistance shows a wider variation than the capacity and weight distribution of the cells. Cells at the other research centers show a wider spread due to different measurement equipment. The scale for the weight determination had a accuracy of 0.01 g, which would correspond to less than 0.003% of total weight.

Initial characterization and post mortem analysis

To evaluate changes of battery lifetime all electrical parameters are recorded at the beginning of life for the battery. In the same way an initial characterization of the internal parameters, which cannot be described with the electrical tests, are recorded with a post mortem analysis. For this, new cells were opened at different SOC. The

90 92 94 96 98 100 102 104 106 108 110Relative 10s Pulse Resistance at 50 % SOC in %

0

10

20Mean: 3.35 m

98 98.5 99 99.5 100 100.5 101 101.5 102 102.5Relative Capacity in %

0

10

20 Mean: 20.29 Ah

99.6 99.7 99.8 99.9 100 100.1 100.2 100.3 100.4 100.5 100.6Relative Weight in %

0

10

20 Mean: 419.46 g

a)

b)

c)


data collected is the reference for any changes that can be observed over the lifetime.

The recorded parameters in a post mortem analysis comprised of geometrical data, weight specifications, morphology of the components, as well as the identification of the used materials. A further reason for the initial post mortem characterization is the fact that the cell producer does not share any information about the composition of the cell or the utilized materials. The process of an initial characterization was also described in our publication [75] where the focus was set on the parametrization of a physico-chemical model to predict the behavior of the battery and study the ongoing processes. For this parameterization, the cell needs to be opened and disassembled.

The batteries are discharged to the defined SOC of 0%. This equates to a state at which all mobile lithium is in the cathode and the remaining lithium in the anode is either trapped or bound in the SEI, and is favored by most researchers [76-79]. All cells inspected were discharged with a stepwise discharge to the lower cutoff voltage of 3.0 V. The discharge current was selected to 1 C, C/2, C/4, C/40 and C/80, with a rest of 5 min in between. After transfer from the test center, the OCV and the internal resistance at 1 kHz was measured for quality control of the electrical preparation. This was done with a HIOKI 3554 BATTERY HiTESTER.

The environment for the cell opening has to be controlled especially with regard to oxygen (O2) and water (H2O) content as they react with components of the battery. To avoid contact with these substances, the cells are opened in an argon filled glove box. The O2 content was lower than 1 ppm and the H2O content lower than 5 ppm5 within the cell opening. Lithium metal showed slow oxidation reactions with components of the atmosphere and also charged (lithiated) graphite showed changes. The charged graphite loses intercalated lithium over time to the environments by the reaction of lithium with the atmosphere when stored unprotected for several hours. These effects made it necessary to process the samples immediately and seal them within storage. The processing times are short in comparison to the reaction rates so that significant change of the samples can be excluded.

While opening the pouch cells, short-circuits and damages of the electrodes have to be avoided. All equipment should be chemically stable against the components inside the battery and also insulating (e.g. ceramic knifes and plastic tweezers). Furthermore the cell contacts were insulated and the cell was kept in a glass pan within the disassembling process in case of short circuits. The cutting position at the

5 The water content had to be estimated for some cell openings, because solvents from the electrolyte

and further processing blocked the sensor and lead to higher display values, even if there was no H2O in the environment.


housing is easy to select, because the imprint of the electrode stack can directly be seen in the vacuumed pouch foil. After cutting the housing with just light pressure the tabs need to be cut with force without producing flakes of metal that could lead to a short-circuit or contaminate the electrodes. Afterwards the electrodes can be separated while the solvents of the electrolyte evaporate. Once the electrodes are completely dried the weights can be measured separately for all components. One can assume that all electrolyte is evaporated once the electrodes are stored in an evacuated antechamber for 2 h.

There are diverse sample preparations depending on the research question for the sample. For the electrochemical tests in coin cells, the coating on one side has to be removed with N-methyl-2-pyrrolidone (NMP) to achieve a good electrical contact between the cell housing and the current collector. After removing the active material from the back side of the electrode, the samples are punched out with a hand punch with a 16 mm in diameter. The samples were then separately washed in DMC for 1 min while the beaker is slewed. It was reported that this rinsing in DMC is sufficient to remove remaining liquid phase electrolyte [80]. After the half-cell samples are dried, they can be transferred to the coin cell preparation area. Samples for structural analysis in the X-Ray diffraction (XRD) and the samples for composition analysis in the inductively coupled plasma - atomic emission spectroscopy (ICP-AES) are just punched out, without removing the active material. The ICP-AES samples are also washed in DMC to remove remaining electrolyte components. Microscope samples do not have to be in a specific form, so that they are cut out of the electrode, without destroying the surface. Thermo-gravimetric analysis and differential scanning calorimetry (TGA-DSC) samples are punched out without washing but with a diameter of 4 mm conditioned by the sample container size.

When the electrodes and samples are stored after disassembling, they are vacuum sealed to prevent reactions in the case of elevated oxygen or water values in the glove box. However, after about 3 month of storage, the electrodes start sticking to each other, so that many techniques (e.g. electrochemical half-cell tests) are not applicable anymore. Henceforth it is recommended to proceed with the measurements as fast as possible [81]. An overview of the cell opening procedure is given in Figure 15.


Figure 15: Flow chart for disassembly of lithium-ion cells and analysis of components (modified from [81]).

Acquiring geometrical data

The measurement values in the post mortem analysis are consistently based on geometrical data (the electrode surface area or the electrode volume). For this, all geometrical data of the housing, the electrodes and separator has to be collected within each cell opening, including weights and dimensions of all components. Exact electrode weights are used to calculate changes caused by layer deposition as it is done in section 10. The remains of dried electrolyte are typically falsifying the weights, which is why a correction by these additional weights is necessary. As a detailed description on how to determine the correct weights is currently missing in literature, an electrode weight correcting needed to be established.

The dimensions of the electrodes can be measured after separation of anodes and cathodes, the values are listed in Table 1. The total area of the electrodes is defined by the area that is covered with active material. The anode is typically larger in dimensions than the cathode to prevent overcharging and lithium plating. The active part of the electrode has a directly facing counter electrode. Thus the cathode has no passive area. The influence of the passive part of the anode is covered in detail in paragraph 4. A schematic of the cell setup is given in Figure 16. The dimensions are measured with a ruler. The thickness of the electrodes and separator were measured with a micrometer screw from Mahr (Micromar 40 ER) with a precision of 2 μm. For a reliable thickness of the electrode and current collector, a combination of different


techniques has been used. The results of ICP-AES measurements and cross section microscope pictures were combined. For electrode thickness, micrometer and cross section pictures are most reliable. The current collector is determined best by ICP-AES. The values are listed in Table 1.

Figure 16: Schematic of the setup in the EIG ePLB C020 cell with the Z-fold separator and the electrodes with the cut out.

Table 1: Geometrical data of the EIG ePLB C020 cell, acquired by post mortem for a fresh cells at 0% SOC. The electrode thickness is divided into active material (AM) and current collector (CC).

Anode Cathode Separator Electrolyte No. sheets 20 pcs. 19 pcs. 1 pcs. - Length 193.5 mm 188.5 mm 197 mm - Width 126 mm 122 mm 5,544 mm - Cut out6 8 mm² 8 mm² - - Thickness AM 67 μm 55 μm 24.5 μm - Thickness CC 10 μm 20 μm - - Total area 9749.2 cm² 8725.8 cm² - - Active area 8725.8 cm² 8725.8 cm² - - Passive area 1013.4 cm² 0 cm² - - Weight total 165.9 g 193.6 g 24.8 g 14.5 g (loss)Porosity 23.8 % 25.2 % 40.8 % -

6 Both electrodes have a cut out at the corners of 2 mm x 2 mm with an angle of 45°.

32

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electrolytes were the ratio is known. The electrochemical tests show that the compatibility is best with the BASF LP50 electrolyte, which has most of the measured solvent components. The following calculations will be based on this electrolyte.

The LP50 electrolyte is a mixture of EC and EMC with a ratio of 1:1 by weight and a 1 molar concentration of the conductive salt LiPF6. The measured mass loss after drying is the mass of the evaporated EMC. With this assumption, the electrolyte mass can be calculated with the following equation:

(2)

The density of the conductive salt is LiPF6 is 1.5 g cm-3, the molar mass MLiPF6 of the salt is 151.905 g mol-1 and the concentration of the salt kLiPF6 is 1 mol l-1. The share of the solvent components is represented by ai and the densities by i. The evaporated mass of the electrolyte ms1 was 14.54 g for a fresh cell, which results in a total of 33.37 g electrolyte in the cell. The share of the volatile solvent components that are decomposed in the SEI formation is neglected, due to the assumption that only VC is decomposed within the formation cycle.

The calculated remains of the electrolyte need to be subtracted from the electrode mass. Therefore, some assumptions about the distribution and the homogeneity of the electrolyte have to be done. Before sending cells to the post mortem analysis, the cells are discharged and stored for several hours, so that the electrolyte and also the salt concentration has enough time to come to an equilibrium state so that a homogeneous distribution can be assumed. Beside the evaporating part of the electrode, also the initially formed SEI belongs to the remaining electrolyte parts. This SEI share can only be found at the anode, so that for this an uneven distribution is expected. The exact amount of electrolyte that is consumed in the formation is not known and no literature for this value was available so that the uneven distribution of electrolyte remaining by the SEI is neglected. One can assume that the electrolyte has been in all porous elements of the cell and with this, completely inside the separator and electrodes. While separating all components, the electrolyte still remains in the porous parts of the components, so the pore volume of the components is correlated with the electrolyte, also with the remains. The correction of the weight has to be done for the electrodes and the separator.

(3)

(4)


(5)

The volumes listed are the pore volumes of the corresponding materials and the complete volume is the summed pore volume of all cell components. The pore volumes are calculated by the following equations, which are exemplary for the anode:

(6)

(7)

The volumes of the separator and cathode are calculated equally. In the equations, P is the porosity of the component, d is the thickness of the coating and A the area of the electrode.

Table 2: Corrected weights of the electrodes and separator and the calculated pore volume.

Anode Cathode Separator Measured Weight 165.85 g 193.64 g 24.75 gPore Volume 15.55 cm³ 12.09 cm³ 10.92 cm³Corrected weight 158.26 g 187.73 g 19.42 g

From now on, the corrected weight values will be used as a reference for all cells if not stated otherwise. The same method is applied for aged cells, where the overall weight loss due to evaporation is less. This is a result of the already decomposed electrolyte on anode and cathode. In section 10, a more detailed focus is set on the weight changes during ageing to analyze the amount of decomposition products at the cathode.

Identification of material composition

The identification of the composition includes the stoichiometry of the active material and the separator. Identifying the stoichiometry of the active cathode material that is utilized is the most important part of the material composition. For this, the stoichiometric analysis is done with ICP-AES. Therefore, 20 mm diameter DMC washed samples were dissolved in aqua regia. The procedure were done at 0% and 100% SOC to determine the utilization of the electrodes. The concentration of metals is given in μmol cm-2, where the area is the geometrical area of the active material of


the sample and is listed in Table 3. The cathode material consists of lithium, nickel, manganese and cobalt where the ratio is Li1(Ni0.4Mn0.4Co0.2)O2. The measurement was confirmed by X-ray diffraction (XRD) measurements where the structure of the material is analyzed. The lithium loss in the cathode is due to the initial SEI formation in the first cycles and the passive electrode effect, described in paragraph 4. An exact quantification of the SEI is not possible, but we can assume that after a complete discharge, all remaining lithium at the anode is in some ways lost for further cycling. Beside lithium, complex organic and inorganic substances form the SEI however their measurement is not possible with the available methods. The correlation of capacity loss and trapped lithium in the SEI is good, so it can be assumed that at a fully discharged state, all lithium belongs to the SEI and is inactive. This leads to an initial portion of the SEI of 6.5%, which is in a good range within the literature values [10].

Table 3: ICP-AES results for fresh cells in discharged and charged state.

Fresh cell 0% SOC Fresh cell 100% SOC Absolut

in μmol cm-2 Relative

in %8 Absolut

in μmol cm-2 Relative

In % Anode Cathode Anode Cathode Anode Cathode Anode Cathode

Lithium 11.74 170.9 6.47 94.24 100.2 74.67 58.32 43.46

Phosphor 1.35 0.39 - - 0.130 0.10 - -

Nickel 0.004 75.77 2.2*10-3 41.78 0.008 72.15 4.7*10-3 42.00

Manganese 0.004 75.28 2.2*10-3 41.51 0.011 70.41 6.4*10-3 40.98

Cobalt 0 30.28 0 16.7 0.004 29.22 2.3*10-3 17.01

Aluminum 0.009 104.4 - - 0.019 97.66 - -

Copper 78.18 0.004 - - 75.66 0.011 - -

Cathodes with layered oxides are never fully delithiated due to stability issues. The utilization of the cathode at a given end of charge voltage is an important factor, because it is assumed that the cathode is overcharged (more lithium is removed) over the life time [82]. This would be a clear indicator for cathode ageing. When the cell is charged to 4.15 V which causes 43.5% of the lithium compared to the sum of NMC to remain in the cathode. With regards to the initial SEI loss, the total mobile lithium accounts to the remaining 51.9% which is responsible for the 20 Ah capacity of the cell. The usage can also be calculated to confirm the measured result of the 100% SOC cell. The exact charge from 0% to 100% SOC is known from electrical 8 The relative amount of lithium is based on the total amount of NMC. The ideal relation between

nickel plus manganese plus cobalt and lithium is 1:1.


test data. By the correlation of the elementary charge of each lithium-ion (one electron) the exact amount of lithium differs in the anode, between 0% SOC and 100% SOC, and can be calculated by Faradays law as it is stated in equation (8). The calculated additional lithium in the anode is 87.9 μmol cm-2 for the charge of 20.55 Ah to charge to 100% SOC, resulting in a usage of the cathode of about 54.6%, which is close to the measured value.

(8)

The identification of the binder material was done indirectly. When an attempt to remove the active material with different solvents (water, acetone, methanol, NMP) was made the best solvent for the cathode and the anode was NMP, so that it is an expert guess that the often used polyvinylidene fluoride (PVdF) is used as binder for both electrodes.

The identification of the microporous polymer was done by identifying the melting of the polyolefin material with differential scanning calorimetry (DSC) in a combined TGA-DSC. The energy that is used for melting the material shows a significant peak slightly above 135 °C, which is the melting point of PE [56]. With the absence of a peak at 165 °C, which would indicate the existence of PP [56] (and also other peaks), the separator in the EIG cell can be identified as a PE membrane as shown in the DSC curve in Figure 18.

Figure 18: DSC curve of a 4 mm diameter separator sample of the EIG cell (20 K min-1). The local minima, slightly above 135 °C, indicate the melting of the separator at the melting temperature of polyethylene.


Description of morphology

Mainly the morphology of the electrodes is of interest regards to normal ageing, excluding high temperatures and over-voltages. The important factors are the particle size, the particle shape, and the porosity. The particle size and its changes are important, because over time the particles could crack and would then be covered by an increasing SEI layer. This would change the diffusion length and also the total active surface. The particle size can be seen in microscope pictures in Figure 19. A Keyence VK-9710K confocal microscope was used. The resolution of the microscope is limited to the wavelength of light. As such, it is not possible to detect and describe nanoparticles. In NMC batteries, nanoparticles are only expected to appear as conductive additives, which are not expected to age. A further characterization of these additives is not necessary for this reason. It can be seen in the microscope pictures of the anode and cathode in Figure 19 the size of the cathode particles is about 9 μm. Single particles of the anode are not clearly detectable and a more homogeneous area is observable, so that a defined particle size has to be estimated to be around 10 - 15 μm in diameter.

The particle size of the cathode can be verified by mercury intrusion porosimetry measurements. The particle size can be calculated from the pore volume with a model that assumes spherical particles. If the shape of the particle is different than spheres, flakes or an additional layer on the anode, the result would have a high uncertainty. The porosimetry delivers a distribution of particle size in the sample. Changes in the distribution could refer to cracking or agglomeration of particles, which would be true even for non-spherical particles. The average measured particle size in Figure 21 is in good accordance to the values obtained with the optical method.

38

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The pore volume, and with this the porosity, of the anode, cathode, and separator were determined with mercury intrusion porosimetry. The separator has a porosimetry of 40.8% and accordingly is within the range of the values from literature with 35% - 45% [56]. The anode has a porosity of 23.8% and with this it is lower than the cathode with 25.2%. Both values are lower than other published values from Ecker et al. [75], but as the cell is designed for a high energy density, the values are plausible.

Figure 21: Particle size distribution for a cathode of a fresh cell. The blue curve shows the distribution of the particles over their size. Most particles are in the range of 9 μm. The size of the conductive additive particles is visible at 20-30 nm.

Electrical electrode characteristics

To be able to analyze the characteristics of anode and cathode separately, half-cells of each are evaluated against metallic lithium. The half-cells were assembled in coin cell housings and the active materials were separated using a Whatmann glass fiber separator. Due to its thickness, this separator prevents short circuits. The thickness of 300 μm also helps to prevent problems of inaccurate positioning of the electrodes. As the Whatmann is 10 times thicker than the commonly applied separators, this results in problems of correlating the coin cell and the full cell resistance. Because that the exact electrolyte composition could not be identified, different electrolytes were tested and the one with the highest achievable half-cell capacity at the cathode was chosen, which is the BASF Selectylite LP50.

For coin cell tests, typically single side coated electrodes are used to achieve a low contact resistance between the housing and the current collector. The removal of the

0.01 0.1 1 10 100Particle Diamater in μm

0

5

10

15

Rel

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e P

artic

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olum

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active material on the backside was done with NMP. By applying the solvent and using light pressure with a tissue, the active layer was removed.

The 16 mm diameter samples used in the coin cells have an active surface area of 2.01 cm2. With the knowledge of the complete electrode area of the cell and their nominal capacity the nominal areal loading is calculated. Thus, the coin cell capacity is expected to be 4.6 mAh. The capacity can be achieved in half cells, if the voltage limits of the full cell are used. However, it is not suitable due to the larger over voltages in the coin cell, this is why considerably lower current rates are used (0.05 C – 0.2 C). So separate voltage limits for the coin cells wider than for the full cell had to be used.

Figure 22: Half-Cell curves of the electrodes from a new EIG ePLB C020. In the top, the NMC cathode is plotted and in the bottom, graphite. Both electrodes were charged with a rate of 0.05 C with respect to their calculated capacity of 4.6 mAh. The charge direction was selected in accordance to the full cell.

The upper part of Figure 22 displays the cathode curve with a capacity of about 6.5 mAh up to 4.5 V. This is higher than the expected 4.6 mAh but can be explained with the higher voltage limit. The curve shows two separate areas; one until 4.5 mAh and the other one until 7.2 mAh which represent the different ongoing oxidation in the NMC while lithium is extracted.

The anode exhibited unrealistic low capacities of less than 5% of the expected value with the described sample preparation procedure. Switching the electrolytes and also the additives in the electrolyte, like the VC content, yet did not increase the measured

0 1 2 3 4 5 6 7 8Cathode Capacity in mAh

3

3.5

4

4.5

0 1 2 3 4 5 6 7 8Anode Capacity in mAh

0

0.5

1


capacity. Cells with the back facing part of the active material not removed showed proper capacities. This suggests that perhaps the removal of active material seemed to damage the active material irreversibly. Cells with double sided active material have the problem that the internal resistance is much higher and the amount of active material taking part in the charging/discharging process is unknown. However, the recorded low voltage profile of the electrode was important to receive information about the balancing of the electrodes. The capacity received for the charge (in terms of full cell convention) shown in the lower part of Figure 22 was 6.4 mAh, and in good accordance with the estimated value of 6.2 mAh. It is assumed that at the current rate of 0.05 C, the distance from lithium to the back side of the electrode is too long to participate in the reaction.

Accelerated ageing analysis

To properly prepare a cell for analysis of the degradation mechanisms, the batteries have to show decent capacity loss and resistance increase. This is done by accelerated ageing without changing the major ageing mechanisms. The degradation curves under varying stress parameters are analyzed to see the degradation path for first conclusions on the ongoing degradation and additionally to identify outliers.

Concept of accelerated ageing

Today’s electric vehicles have a realistic driving range of 150 km to 500 km [3, 4]. The sales figures indicate that the primary sold full electric vehicles have a range of 150 km (e.g. the Nissan Leaf [6]). To test the ageing behavior of the battery cells from this class of vehicles the best option would be, to use real driving profiles (or artificial ones like the worldwide harmonized light-duty vehicles test procedure (WLTP) [84]) to age the batteries and estimate the achievable lifetime. With this technique it would be possible to get an accurate lifetime statement from a real application. The driving range lifetime for typical today’s vehicles with combustion engines are between 150,000 km and 250,000 km, which can equivalently be assumed for the battery electric vehicles (BEV). The typical calendric lifetime of such a vehicle differs in Europe but varies from 8 to 12 years [85]. It is easy to notice, that the testing time would be too long, compared with the development cycle of new batteries. This leads to the fact that the ageing needs to be accelerated without changing the major degradation effects inside the battery.

For a given battery system calendric ageing is mainly dependent on the temperature and the state of charge (SOC) of the cell which corresponds with the stored voltage of the cell. Literature on basic chemistries explains that nearly all processes double their reaction rate by doubling the temperature [86]. This is also valid for most of the processes in lithium-ion batteries if no other process, like plating, becomes dominant


[87-89]. The electrolytes of the batteries are the least stable components in terms of temperature dependency. The limit of the electrolyte is often set to 60 °C, which manifests the limitation for testing [88]. Some literature even states lower temperatures of 45-50 °C for the decomposition of LiPF6 [90]. Moreover, lithium plating, which is a process happening at low temperature while charging the cell, does not following this rule. The plating process increases with lower temperature, which is in contrast to the idea of increasing the temperature for faster ageing [91]. The degradation by lithium plating only happens when the battery is cycled, more precisely when it is charged. So the acceleration of calendric tests by increasing the temperature in certain limits is valid and was thus done for this thesis.

When taking a closer look on the use of batteries in electric vehicles, one can see that cars on average cover about 36 km per day [92]. Firstly, this shows that the average driver would mostly need a car with a low electric driving range and secondly that the car is not used and “standing still” most of the time (95% [92]). The cars are typically used for about one hour per day, the rest of the time the battery remains unused. To accelerate the cyclic ageing, we can now erase the standing times and sum up all the cycling. With this the acceleration can be done without the change of any of the cycling parameters of the battery. Resulting from this acceleration a faster ageing of the batteries, than in the real application, without changing the degradation mechanisms is expected. This leads to valid ageing information within a short time to study the dominant degradation processes in the battery.

Ageing behavior in storage conditions

To test the cells with storage conditions under different SOCs and temperatures as afore mentioned, ten conditions have been selected and tested over the past three years. Each condition is set up with three cells to identify outliers. The temperature ranges from 25 °C to 45 °C and the state of charge from 20% to 100%. All storage ageing conditions can be seen in Table 4. The numbers in the condition are the distinct identifiers of the cells that were used.

Table 4: The table summarizes the calendric ageing matrix with the total number of cells at that condition. The number in brackets indicates the number of cells that were disassembled and analyzed.

SOCTemp.

100% 80% 65% 50% 35% 20%

25 °C 3 (1) 3 35 °C 3 (3) 3 (1) 3 3 3 3 (2) 45 °C 3 (2) 3


The calendric ageing graphs can be seen in Figure 23. All storage temperatures of 25 °C, 35 °C and 45 °C are shown. The expected behavior would be that an increased ageing is expected for both, higher temperatures and higher storage voltages. This typical behavior was also observed by other researchers [77, 93, 94]. On the left side of this figure the lowest temperature can be seen. The cells at 50% SOC show a rise up to 103% of the initial capacity followed by a stable trend until end of test after 950 days. The 80% SOC cells show nearly 2% of capacity loss within 950 days of ageing and just a small rise compared to the 50% SOC cells. This suggests that the difference in the behavior correlates with the respective SOCs of the stored cells.

The same difference can be observed for the cells aged at 45 °C, in the right graph of Figure 14. At 45 °C, the ageing is more profound, which is probably a result of the elevated temperatures. Compared to the 25 °C tests the 50% SOC cells at 45 °C show a capacity rise and afterwards a decreasing capacity, but is still better than at the begin of the ageing test with 100.5% of the initial capacity. The petrol colored 80% SOC cells at 45 °C show massive influence on the stored time on the remaining capacity. Also the variation among the cells increases for longer ageing times.

The center of Figure 23 displays the ageing curves of the cells stored at 35 °C. These cells have been stored for more than 950 days. The matrix at 35 °C has more test points than the two other temperatures to help understanding the dependency of the ageing on the stored voltage. The effect of a rising capacity in the beginning of life can also be observed for the cells aged at 35 °C. To understand the reason of this effect, one of the 20% SOC cells was removed from the test after 320 days. This was cell 52, which had the highest capacity rise of the calendric cells. Every time a cell was removed from the test and a post mortem analysis was performed, it is highlighted by a black star in the ageing graphs.

Different to the expected behavior, which would be a sudden capacity loss, the 100% SOC cells at 35° C and one of the 80% SOC 45° C cells keep a stable remaining capacity of 87%. This capacity remains over a long time period of 150 to 300 days before it drops below the 80% end of life criteria. For this behavior, no final explanation could yet be found. It is expected that a change of the dominant degradation mechanism occurs.


Figure 23: Calendric ageing of the EIG cell at three test temperatures. The remaining capacity is plotted over the ageing time, in the left graph at 25 °C, in the center at 35 °C and on the right at 45 °C. The end of life of the batteries is at 80% of remaining capacities.

The remaining capacities of the calendric ageing tests are acquired and can be analyzed. In order to have an independent measure for this, a fitting of an ageing function was performed. With this, ageing conditions can be compared and it can also be used to extrapolate the ageing or interpolate for different temperatures and states of charge. For most of the cells only one dominant degradation mechanism is assumed so that this mechanism is modeled by a linear capacity loss rate. For this, only the linear part of the degradation is used. This disregards the rapid cell break down and the capacity increase at begin of life, which are probably caused by an additional superimposed effect. So it was determined that a linear degradation describes the material degradation best. In Figure 24 two examples for the capacity loss rates are displayed. The cells at 65% SOC, in light green, initiate with an increase in remaining capacity followed by a linear degradation. After about 700 days the degradation mechanism changes and the linear degradation stops. The second example are the cells from 50% SOC in orange, which also show an increasing capacity at begin of life, but afterwards a steady declining capacity. The assumed linear degradation rates are displayed by the dashed lines. The rates for all cells and conditions are listed in Table 5.

Rel

ativ

e C

apac

ity in

%

Rel

ativ

e C

apac

ity in

%

Rel

ativ

e C

apac

ity in

%


Figure 24: Detailed view of the ageing curves from 35 °C at 50% SOC in orange and 65% SOC in light green. The degradation rates are displayed with the dashed lines in the corresponding color.

Table 5: Ageing rates of the linear part of the degradation curves. The ageing rates are mean values of the three cells from one condition.

InmAh/d.

100% SOC 80% SOC 65% SOC 50% SOC 35% SOC 20% SOC

25 °C 0.604 0.157 35 °C 2.821 1.707 1.154 0.540 0.485 0.06545 °C 5.540 1.747

The capacity of a battery cell is important for the drivable range in an electric vehicle but the internal resistance of a battery is also a key parameter. The power performance of the cell is highly dependent on this parameter. In many projects the end of life for batteries from performance issues is set to doubling the initial resistance value. In the project Batteries2020, were the original data comes from, we did not use this parameter as EOL criteria to see the ongoing performance with regard to the second life of the battery.

0 100 200 300 400 500 600 700 800 900 1000Ageing Time in d

97

98

99

100

101

102

103R

elat

ive

Cap

acity

in %

65 % SOC50 % SOC


Figure 25: Resistance measured with pulse measurement at 1 C after 10 s at 50% SOC for the calendric ageing cell, on the left at 25 °C, in the middle at 35 °C and on the right at 45 °C. With the ongoing ageing resistance increases and correlates with the capacity loss.

Figure 25 shows the change of the internal resistance of the calendric aged cells at all tested temperatures. The internal resistance is tested with a pulse test with 1 C after 10 s in discharge direction at 50% SOC. The change of the internal resistance at 25° C is small, but shows the trend to increase over time. The difference between the cells at 50% SOC and 80% SOC is smaller than expected from the difference in capacity. All cells at 25 °C show a slight improvement in the beginning until a nearly linear increase of 1% per 100 days starts. The influence of the stored SOC is small compared to the variation so that a dependence of it cannot be described within the testing time of 950 days.

In the middle of Figure 25 the 35° C resistances are depicted. The dependency from the SOC can be seen very well, even if the lower SOC show just small differences between the ageing conditions. In contrast to these tests the 100% SOC cells show the tendency to increase the resistance very rapidly after the start of the test. After they exceed the point of 130% of resistance increase the gradient of the curve changes to a much faster increase. This data correlates well with the capacity loss data in which the capacity loss fastens after 480 days. The cells seem to exceed a critical point from where the battery degrades much faster. This indicates a change in the dominant ageing mechanism. The resistance curve from the 45° C and 80% SOC

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cell shows the same behavior. The curve has the same characteristics, but hits the critical point nearly 100 days earlier. Also these cells show a fast loss of capacity at the same time.

In summary the findings for calendric aged cells, all cells show similar degradation behavior until the cells reach end of life at 80% remaining capacity, which means that even for different temperatures and SOC, the degradation mechanisms seem to remain unchanged. This includes the breakdown of cells and the more rapid degradation after a change in the dominant degradation mechanism. It is possible to extrapolate the ageing curve form for the other tests to see the expected lifetime depending on the temperature and state of charge. The observed intermediate constant capacity at 87% was also observed for different ageing conditions, so that a systematic change in degradation is expected at that state.

Between the ageing days 500 and 800, all cells show a high variation in the measured capacity which is probably not caused by degradation effects but rather from the testing and the equipment. This phenomena is analyzed in further detail within paragraph 3.3.4

Ageing behavior in cycling conditions

In the use of a battery, many parameters vary. As a result, testing of all these leads to a high complexity. If each test is set up with a statistical relevant number of cells, the costs would be enormous forcing this to be unlikely to be realized. In the project Batteries2020, it was possible to establish a very complex test matrix to gain insight to all important influence factors. This was made possible by combining test infrastructure and personal of five test centers. In total, over 130 cycle ageing cells were tested in 37 use conditions. A detailed analysis of all these cells including the post mortem analysis (explained in 3.2) would exceed the framework of this thesis. A representative selection of cells is analyzed and presented here. The complete ageing matrix is in listed in Table 6.

Within the project different cyclic ageing tests were used to detect the influence of parameters like DOD, middle SOC, C-rate and temperature separately. The DOD was varied between 20% and 100%. The current rate was varied from 0.333 C to 2C in charge and discharge direction, mainly at 35 °C. The result of these tests should show the influence of fast charging and standard charging. For the discharge, only a minor influence by the current rate was expected. The middle SOC is varied to see if the cell has ranges of increased ageing, as it was reported for other NMC-based cells [91]. The temperature was set to the same three temperatures as the calendric test. The control was done with respect to the cell surface temperature so that with prolonged cycling adjustments at the equipment were necessary. The current idea of performing ageing tests include that the cells were aged under use conditions, and


also undergo calendric ageing in that time. To get an idea of the influence of the calendric ageing tests, a rough calculation can be done. The middle SOC for most of the cells cycling is 50% SOC; this is also the average SOC within the cycling process. As it can be seen in Figure 23, cells that are stored at 50% SOC show at temperatures below 45 °C hardly any loss of capacity (below initial capacity). The influence of the calendric ageing on the cyclic ageing tests with 35 °C or lower can therefore be disregarded. At 45° C the calendric share can be neglected if the testing times are shorter than 500 days. At this temperature, the longest lasting test performed was 1,500 FCE, which corresponds to 250 days at the ageing temperature. This assumption should just show that no massive influence of the calendric share in capacity loss and resistance increase is to be expected.

Table 6: Cyclic ageing matrix with the total number of cells at that condition. The number in brackets indicates the number of cells that were disassembled and analyzed.

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Symmetric cyclic with high Ah-throughput

The first cyclic ageing tests that will be focused on are the ones close to a realistic application with 80% discharge depth. These tests show - from all cells presented - the highest Ah-throughput and with this the highest number of FCE and further reached end of life. The cells, tested at 25 °C, were charged and discharged with 1 C in the range of 90% - 10% SOC (80% DOD). With 3,500 FCE the cell had a throughput of 70,000 Ah charged until they experienced an instantaneously rapid capacity loss. The remaining capacity before the cells had a break down at about 87%. This is the same remaining capacity as the calendric ageing cells had a constant remaining capacity over time, so that a correlation might be possible. The variance between the tested cells is significantly low, which indicates highly reproducible results.

At an electric vehicle application with a depth of discharge of 80%, the 3,500 FCE are equivalent to 4,375 cycles. With the typical range of 150 km [6], this would be equivalent to 650,000 km. The remaining capacity curve in the upper part of Figure 26 shows an initial increase similar to the calendric ageing cells from the previous paragraph. The maximum capacity is reached after 200 FCE or 43 days in the test. After this, a homogeneous degradation can be observed until the remaining two cells of the test break down at 3,300-3,500 FCE. The degradation rate of these cells is calculated in the monotonously decreasing part of the ageing curve, because only one degradation mechanism is expected. The rate is calculated to 0.7 mAh FCE-1. These ageing rates are only valid for a part of the degradation curve but probably give the best hint on the dependency of the material degradation from the applied stress factors. Compared to this, the lower part of Figure 26 shows cells under the same conditions but with an elevated temperature of 35 °C. It can be seen here that the general degradation behavior is the same. The cells experience a temporary increase of capacity and after this, a linear capacity loss until they have a rapid capacity loss just before end of test. These cells show the increased degradation rate of 1.25 mAh FCE-1. Unfortunately no further temperature with the exact ageing conditions is available so that a temperature dependency cannot be calculated. The increasing capacity of on of the yellow cells is related to an exchange of the used testing device.


Figure 26: Degradation curves of the cells aged with 1 C in charge and discharge direction between 90% and 10% SOC at 25 °C and 35 °C. The petrol colored curves are from cells at 25 °C and the orange ones from 35 °C. The increase of capacity of a 35 °C cell from 2,000-2,500 FCE is probably due to incorrect measurements from the testing device.

The resistance curves of these two ageing conditions are shown in Figure 27. It can be determined that they correlate well to the capacity loss curves because the specific inflection points occur at the same time. The cells show a steady behavior over the whole lifetime. However, once they exceed 30–40% of resistance increase the capacity breaks down. It can be concluded from these findings that the internal resistance of the cells should be monitored carefully to predict a sudden drop of cell capacity and performance. The fast resistance increase after exceeding 130-140% of the initial resistance was also observed at the calendric ageing cells. The remaining capacity at that ageing state was also at 87% so that a clear correlation is assumed. This rapid degradation probably cannot be traced back to a simple material change which would be more of a smooth change. Effects may be caused because the system is out of balance at that point.

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Figure 27: Resistance curves for cells from cyclic ageing with 1C/1C, 80% DOD at 50% mid. SOC for the temperatures 25° C and 35° C. If the curves exceed 30 - 40% resistance increase the immediate breakdown is the consequence.

Temperature dependency

Cells aged at the three test temperatures are provided on the left side of Figure 28. The cells are cycled between the voltage limits (100% DOD). The red curves show the capacity loss at 45 °C. It can be seen that the behavior of the three cells differ; two cells show an capacity increase whereas one cell does not. However, the ageing curve looks like it was shifted compared to the other two cells. Probably the cell had a different ageing history or was used for the set-up of the test device. A similar behavior for cells with different history was also reported by Lewerenz et al. [95]. The tests were performed at another test center so that a detailed analysis is not possible with respect to the test procedures. The ageing rates of the cells increase with temperature, as expected, due to faster ageing processes. Compared to the before described ageing conditions, we do not see a breakdown of the 45 °C cells at 87% remaining capacity for all cells. An explanation for this could be the high internal resistance and with this the internal temperature, which could change the main degradation mechanism. This could be the reason that the gradient changes after 700 cycles. The cells at 35 °C show the breakdown below 85% remaining capacity, which is 2-3% lower than the previously described cells. On the other hand, these cells do not show the increase in capacity of 2-3% that was seen previously. Shifting the 35 °C cells by this, the drastic capacity loss happens at the same remaining capacity. The 25 °C do not show the breakdown in the graphs. One cell was analyzed after reaching 85% remaining capacity, the others were planned to continue cycling to receive more information about the degradation path. For these two cells, the breakdown came along with swelling of the cells so that further capacity tests could not be performed in a secure way.


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The resistance curves on the right side of Figure 28 show a drastic increase of the pulse resistance value for all cells. They all exceed the critical mark of 130% of internal resistance without the breakdown. One explanation for differences in behavior could be the ageing strategy. As explained before the cells are cycled between voltage limits and not Ah-based using the actual discharge capacity. For the comparison of temperature influences, the linear ageing rate of the degradation curve is compared. For the 45 °C cells the part that is assumed to be linear is short and ends after 500 FCE. The ageing rate for 25 °C is 1.1 mAh FCE-1, for 35 °C the rate is 2.97 mAh FCE-1 and for 45 °C the rate is more than doubled with 8 mAh FCE-1. The typical rule of thumb that estimates doubled ageing rate for 10 K higher temperatures is underestimating the ongoing degradation effect in the cell.

Figure 28: Capacity and resistance curves of cells that are cycled with 0.333 C – 1 C and 100% DOD at 25 °C in blue, 35 °C in green and 45 °C in red. The expected temperature dependent lifetime is visible in the capacity loss and resistance curves.

Middle SOC dependency

The dependency on the degradation of the middle SOC is tested at 35 °C. In the left of Figure 29, the degradation curves for five different middle SOCs are shown. These cells were tested with 0.333 C in charge and 1C in discharge direction. The depth of discharge is 20% whereas the middle SOC is different. The low DOD allows seeing a more detailed influence of the middle SOC, because the used SOC ranges vary. For higher DODs the used state of charge range would overlap too much so that a difference in the tests would be hard to see. Further, small DODs enable us to use very high and also low middle SOCs. Most of the cells did not show any ageing for

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the tested 1,600 FCE. Only cells at 80% middle SOC displayed ageing. They lost about 4% of their initial capacity. Despite this, the cells group in the order of their middle SOC. The cells with the lowest middle SOC have the highest remaining capacity and vice versa. This order was also observed for the calendric ageing tests, whereof the beginning of the ageing is shown in the right of Figure 29. The simple comparison indicates that the same ageing mechanism is present, because the cells show the same behavior. The low discharge depth has no or a minimal added ageing to the calendric degradation that happens over the used time. The only exceptions from this are the 65% middle SOC cells, but they also do not show the characteristic capacity increase at begin of life so that this is probably related.

Figure 29: The left side shows the cyclic ageing trends of cells at 35 °C at 20% DOD (0.333 C for charging and 1 C for discharge rate). On the right, the calendric ageing curves for 35° C and the corresponding storage SOCs are displayed. For each ageing condition a representative cell is selected.

To validate the influence of the middle SOC, a comparison for cells with higher DOD is done. From the findings at the 20% DOD cells it can be expected that the cells group in the same way as the calendric aged cells. Figure 30 shows on the left the cycled cells with a DOD of 50% and on the right calendric ageing cells at the same SOCs as the middle SOCs. The cyclic ageing cells show a big variation in each test condition making the differences between the middle SOCs difficult to detect. The differences between 35% and 50% middle SOC are negligible but also the calendric cells show at this storage SOCs only small differences. Only the 65% middle SOC cells show 4% higher capacity loss after 1,500 FCE. In total, the cells lost more capacity than the calendric cells so that it can be assumed that the additional ageing

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is caused by the cycling of the cells due to the higher depth of discharge compared to the previously presented cells.

Figure 30: On the left side the cyclic ageing trends of cells at 35° C and 50% DOD with the current rates of 0.333 C for charging and 1 C for discharging at different middle SOCs are shown. On the right the calendric ageing curves for 35° C and the corresponding storage SOCs are displayed. For each ageing condition a representative cell is selected.

DOD dependency

To investigate the difference in ageing rate depending on the depth of discharge, tests at 25 °C, 35 °C and 45 °C have been conducted. All the tests show the same capacity loss dependency from the discharge depth, but at a different rate, so that the focus here is on the cells at 25 °C. These ageing tests have some advantages over the tests at the higher temperatures. Firstly, the tests were performed at ISEA with a full ageing path with all pauses and changes in devices are tracked. Secondly, the cells have the highest Ah-throughput and show the least variation, which is a sign for reliable results.

The cycling depth for the cells was varied from 20% up to 100% DOD. The resulting ageing curves are shown in Figure 31. The cells with 35% and 65% DOD were cycled for 1,500 FCE and then taken out of test without failing. The reason for the end of these tests was, that the cells were used in the project to build a heterogeneous battery pack of cells from different ageing history and state of health. Nevertheless the results of these cells indicate that they group by the used depth of


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discharge. That means that high DODs are rather less favorable for a long life than low DOD. Ecker et al. [91], stated that cells with a high DOD are cycled over the full lithiation range and this induces stress by graphite expansion inside the anode particles, which results in more SEI buildup and with this more capacity loss. Beside this, the cells with 100% DOD had a throughput of more than 3,000 FCE until they had to be taken out of test because of swelling. No cells reached an end of life of 80% remaining capacity during the duration of the project, even the 50% DOD and 20% DOD cells were continued over the project time.

Figure 31: Ageing curves of cyclic aged cells at 25 °C and different DOD. The black stars indicate when a cell was taken out of test for post mortem analysis.

As already seen for the calendric and nearly all other cells, the batteries experience a capacity rise within the first cycles. The maximum capacity that was reached was 102% of the 80% DOD cells, but only for a short time. The other cells show a more slowly increase to 101%. After this nearly 500 FCE lasting process, all cells show a linear degradation, so that here a superposed effect at begin of life is expected. This effect is discussed in detail in paragraph 4. For the linear capacity loss, degradation rates were calculated and are listed in Table 7. In general these cells achieve a rather long lifetime of more than 3,000 FCE, which is equal to more than 450,000 km in an electric vehicle (150 km range). In addition to that the results indicate that longer lifetimes are possible if the batteries are partly used.

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Table 7: Degradation rate for cells with a middle SOC of 50%.

In mAh/FCE

100%DOD 80% DOD 65% DOD 50% DOD 35% DOD 20% DOD

25 °C 1.408 0.842 - 0.453 - 0.17735 °C 2.812 1.855 1.123 0.745 0.507 0.23245 °C 7.396 5.534 4.366 3.292 2.528 1.946

Current rate dependency

The last parameter that is separately investigated is the current rate, which is of high importance for the electric vehicle application. These parameters determine the maximum power output of the battery pack and the charging time of the EV. Especially the charging time will be one of the key factors for the social acceptance of electric vehicles. The battery and vehicle producer must know the maximum charging current for fast charging which is acceptable regarding a reasonable lifetime. To examine this, three different test sets were analyzed.

At first the discharge current is varied while all other parameters are kept constant. The results can be seen on the left side of Figure 32. The results show that the capacity increases much more for the test with the 2 C discharge current, but the decreasing slope of the three test conditions is comparable. The ageing rates are in the range of 1.2 mAh FCE-1 to 1.6 mAh FCE-1, only the very slow tests at 0.333 C charge and discharge exhibit higher loss rate. The long testing time increases the calendric share of cells in this test condition. The conclusion of this variation is that there is no strong dependence of the degradation from the used discharge current rate in the used range up to 2 C.

In the middle of Figure 32, the charge current value was varied while the other parameters were kept constant. Again, the cells with the higher load current (1 C, 2 C) show a higher increasing capacity compared to the cells aged at low current rates (0.5 C and 0.333 C). It can be observed that in these tests the declining slope, or ageing rate, of the cells is nearly the same; excluding the 2 C cells, where the variation is very high. The cells from 0.333 C to 1 C have an average degradation rate of 1.3 mAh FCE-1. The 2 C cells show a comparable capacity loss in the first 700 FCE with doubling the speed of ageing of 2.6 mAh FCE-1, followed by a drastic drop in capacity. This is probably due to the extremely high current rate, which results in plating on the anode.

The third test set proves these results. Here the charge and discharge rates are kept symmetrical and the 2 C cells show a sudden drop in capacity after 700 to


1,000 FCE. Also the cells with only a high charging rate of 2 C experienced end of life after 700 – 1,000 FCE. The reason for this drop was massive plating, which was observed in the post mortem analysis. A conclusion from the variation of charge and discharge current rates is, that the cell is limited in charging current in between 1 C to 2 C. When exceeding this current rate a drop in capacity will occur so that the onset of the plating is described best with a step function. There, the limitation for the fast charging can be seen, so that charging currents higher than 1 C should not be allowed.

Figure 32: Ageing curves of three different test sets that were designed to see the influence of the charge and discharge current. On the left, the influence of the discharge current, in the middle of the charging current and on the left both tests combined.

Variability in ageing curves

As seen in the paragraphs before or in detail in Figure 33, some tests show remaining capacities, which are not following the general ageing trend of the cells. This is not always caused by the actual ageing, but often by the test devices or errors in the testing setup. Especially for calendric tests, the cells are connected manually every checkup to the Digatron testers to measure the current state of health. After each checkup the cells are connected in storage to the voltage source, remaining SOC over storage time. By the fact that such a test matrix includes a huge amount of

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cells and more than one operator is working on such a project, mistakes occur. Further, within the long testing period of over three years, the devices are calibrated frequently and exchange of test equipment happens. Combining all these influencing factors, it is clear that systematic failures and outliers occur. Here, the most important outliers of the tests are analyzed and their influence on the ageing behavior is discussed.

Figure 33: Capacity measurements that show a higher variation in the time period from 550 days to 780 days. The capacity measurements are displayed in the top graph, the temperatures within the check-up are shown in the middle graph and the maximum voltage of the test circuit in the lower graph.

Figure 33 shows previously presented cells displaying unexpected remaining capacities in the time period from day 550 to days 780. In the residual testing time, the degradation curves reveal a very homogeneous behavior. The limited resources for the accelerated ageing tests lead to the fact that more than one cell is tested in a temperature chamber, resulting in a compromise for the adjusted temperature. As a

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consequence the temperature in each check-up is different. The limits in the project were set to ± 1 K, which was a hard target because the used temperature chambers (Binder MK53 and Binder MK240) have an accuracy of ± 2 K. Additionally the temperature sensors from AD 590 have a precision of ± 1 K. Combining both tolerances, the temperature within the check-ups should be within ± 3 K to minimize the influence on the measured capacity. In the middle of Figure 33 the average temperatures for each check-up are summed up. They are all within a range of ± 1.5 K of the set temperature. The trend of the average check-up temperatures show an increase which is caused by resistive heat due to the increasing internal resistance over ageing. The lower part of Figure 33 shows the maximum voltage of the test circuits within the check-up. The test circuits with a 6 V maximum voltage are devices of the type Digatron MCT 50-06-12 ME with accuracy of ± 0.1% of the end value (50A) in the current measurement, which results in an uncertainty of 0.15 Ah (at a 0.333 C discharge). The 18 V devices are Digatron MCT 100-06-12 ME with accuracy of ± 0.1% of the end value (100A) in the current measurement, which results in an uncertainty of 0.3 Ah (at a 0.333 C discharge). The wider operation range of the 18 V devices comes along with the drawback of less precise current measurement. The higher nominal error is accumulating within one charge or discharge so that a 0.75% higher or lower discharge capacity is measured. One conclusion is that the unexpected remaining capacities that we see are a result of a variation in test equipment and not fractures of an ongoing ageing process.

Separation of degradation behavior

As seen in the previously presented degradation curves and schematically in Figure 34, nearly all cells show a similar behavior which is are three phases of ageing. The first part of the degradation is an increase of the initial capacity, the second part of the ageing is a linear capacity loss of the battery and the third part is a rapid breakdown. These parts of the degradation curves will be studied separately. Following paragraph 4 is explaining the phenomena of the initial capacity rise which is related to the internal structure of the battery and not related to the used cathode material. Concept on the rapid capacity loss at end of life is given in paragraph 6. The breakdown is explained briefly because it is related to lithium plating, which is one of the most important anode ageing effects and this thesis focuses on cathode ageing. The following section of this chapter gives an overview on the linear-like degradation in the cell. This is most likely related to a ageing of the used materials and with this, in the focus of the thesis. The sections 8 to 11 will discuss the relationship between the linear-like capacity loss and the ongoing ageing processes related to the positive electrode.


Figure 34: Three phases of the degradation curve of the EIG cell. The first phase is the increase of capacity, the second is a linear degradation and the third phase is the rapid break down.

The scope of this thesis is on the degradation behavior of NMC-based cells, the cathode active material on the tested cells. The capacity rise and break down of the cell have a drastic influence on the actual capacity, but if the assumption of linear-like ageing is correct, these are not caused by the cathode material. When correlating any changes in the cell, or more specifically in the cathode, with the remaining capacity, a wrong conclusion may be drawn. For example, with elevated temperature and or cell potentials, it is expected that the cathode material dissolves. It is unlikely that the dissolution could follow the trend of the breakdown but would rather continue linear as indicated by the dotted blue line in Figure 34. Therefore, a correlation between the displayed changes in the cathode and the linear capacity loss, which dominates in the second phase, will be shown.

Influence of the cell design on degradation 61

Influence of the cell design on degradation

The capacity loss in the cell is not always a linear process, as it can be seen for the EIG cell. By interpreting the degradation curves, unexpected behavior can be seen for many cells (e.g. the increase in capacity at begin of life). Within these “capacity loss” curves it is very likely to have super-posed effects besides the actual ageing of the active materials. Within the following paragraph the influences by the cell design, more specifically the geometry of the electrodes on the degradation, is studied. Without the knowledge of this influence, the interpretation of the ageing functions of the materials is impossible. The influence of the geometry on the coulombic efficiency as well as pictures of opened cells were reported by Gyenes et al. [96], without providing evidence of correlation to ageing, however this was published recently by Lewerenz et al. [95]. The following part of the thesis proofs the theory and exceeds the findings given in literature by evaluating the lithium concentration distribution.

Figure 35: Example for the geometry influenced capacity increase at begin of life. On the left, the schematic from the three ageing phases is shown and on the right, the measured curves in calendric storage at 35 °C are shown.

Every lithium-ion battery with a carbon or silicone electrode has a geometric overhang of these anodes compared to the cathode and furthermore a higher areal capacity density. This leads to an overall higher capacity of the anode of such a lithium-ion battery. A schematic drawing of the geometries is given in Figure 36. The primary reason for this is the prevention of lithium plating [97] which occurs when the anode is overcharged and the local potential is dropping to, or below, 0 V against metallic lithium. The excess anode is preventing this in normal operation conditions by only allowing partial charging of the anode. Furthermore the overhang at the sides allows small tolerances within the stacking process according to misplacements. The

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geometrical overhang is generally thought as passive electrode that is not participating in the charge and discharge reaction.

Figure 36: Schematic overview of the setup from a stacked cell with an anode overhang to the sides and passive anode on the outer anode sheets. The distance from cathode to the active anode is in a μm-scale and to the passive parts in a mm-scale.

The presented cell from EIG is a pouch cell with stacked cathodes and anodes. The anodes have a geometrical overhang of 2 mm on each edge, resulting in a geometrical excess of the anode of 6% compared to the cathode area. The cell is assembled with a stack of 19 cathodes and 20 anodes. All electrodes are double side coated with active material as it is also shown in the schematic in Figure 36. The reason for this is the facilitated production of the anodes as compared to a separate production of double sided inner anodes and single side coated anodes for the outsides. The outfacing anodes add additional 5.6% of passive electrode area, so that in total the anode area is 11.6% larger than the cathode or the active anode respectively.

Spatial resolved measurements of lithium concentrations

To reenact the processes inside the battery and more accurately the state of charge of the passive and active anode, a spatially resolved lithium concentration measurement is necessary. The metal concentration is measured with ICP-AES, which enables measuring the concentration of many elements in a liquid phase. The used device is a Varian 725-ES.

The concentration was measured at 20 mm diameter samples. These were washed in dimethyl carbonate (DMC) to remove the conductive salt and remaining electrolyte solvents [76, 78, 98]. For this, the samples were rinsed in DMC for 3 min and afterwards dried inside the glove box. The samples then were dissolved in 15 ml aqua regia and then filled up to 100 ml with ultrapure water. These dissolved samples are measured with ICP-AES. It is the preferred method to investigate the


metal content of samples in lithium-ion batteries [77, 79, 99, 100] and also often used to determine the lithium content [77, 79, 101]. For ICP-AES calibration Merck single element standards were used for Li, Al, Ni, Mn, Co, Cu and Merck XIV multi element standard for P. The calibrated concentrations were ranging from 0.1 mg l-1 to 50 mg l-1. All metal concentrations presented in this publication are in reference to the geometric active material area. A sample with double sided electrode material has a geometric active material area of about 6.28 cm² and a one side covered electrode has an area of 3.14 cm². The concentration of lithium and other metals is given in μmol cm-2. To determine the maximum and minimum amount of lithium in the anode, fresh cells at 0% SOC and 100% SOC have been opened directly after discharging/charging and the concentration in the center of the cell was measured to exclude the influence of the passive anode. The concentration for 0% SOC is 11.7 μmol cm-2 and 100.2 μmol cm-2 for 100% SOC.

To receive a spatial resolution of the element concentrations, the samples were taken at several points inside the cell. Two positions inside the cell stack were selected for anode and cathode, the outer sheets, for seeing the concentration in the passive anode, and the most inner sheet for the most even point. On one electrode sheet itself, samples at the edges and in the middle of the sheet were taken. At the outer sheets of the anode double side coated samples and additionally single side coated samples were taken. For the single side coated electrodes, the coating was removed for some at the inside and for some at the outside. Resultantly it was possible to associate the found lithium concentration in the double side coated sample to the inside or outside of the cell. The samples positions are shown in Figure 37.

Figure 37: Schematic of the sample position for the spatially resolved metal concentration measurements.

As it can be seen in Figure 37, the samples are distributed over the area of each sheet. To show the concentration of each sheet, the double sided samples from the middle are averaged, which is also done for the samples at the edges. An average lithium concentration for the front and the backside is measured. The red and green


samples are single side coated and are located between the middle and the edge. The removal of active material made exact positioning impossible. For the red samples the active material on the outside remained and was measured, which is the passive part of the electrode. The green samples represent the active electrode of the outer sheets.

For visualization of the lithium distribution, the stack is schematically shown in Figure 38. The inserted areas show the sample position, edge or middle of the electrode and if the sample was single or double side coated with active material. The number inside the area is the averaged concentration of measured lithium in μmol cm-2 referring to a single layer. The green and red area show the single side coated samples of the outer sheets where just the inner or the outer part was measured. This form of visualization will be consequently used in the next sections.

Figure 38: Visualization of the lithium distribution inside a fresh cell which was opened at 0% SOC.

Importance of delivery conditions

After fabrication and formation at the producer, the cells are stored and shipped in a defined state of charge determined by the manufacturer. This SOC is typically below 30% SOC, forced by the regulation of cell shipment by air cargo. This regulation has been active since the 1.4.2016 [102]. The cells presented here were stored and shipped at about 68% state of charge (~3.74 V). Cells with a carbon anode have no lithium inside the negative electrode within the fabrication process as it is shown in Figure 39 on the left. The lithium is intercalated for the first time within the first cycle of the formation. Within the first cycles, the SEI is formed and the cell is prepared, but the lithium is only intercalated in the anode regions that directly face a cathode. This is illustrated in the middle part of the figure for our delivery state. When the cell is stored the lithium concentration in the active anode area is higher compared to the

Lithium distribution of a fresh cell at 0% SOC

18.7 17.110.6

25.6

11.3 10.7

19.3 17.710.7

23.4


passive anode area, resulting in high voltage differences. The typical voltage of a graphite without lithium is above 1.5 V (as it can be seen in Figure 22), compared to the partially lithiated graphite of about 0.1 V to 0.5 V. The lithium ions from the higher charged graphite migrate through the electrolyte to the anode areas with a lower charge. This process is fast in the beginning when the voltage difference is high and gets slower once the voltage difference is low. This results in a partly reversible loss of lithium ions into the passive electrode area. This is also shown in Figure 39 on the right where the lithium distribution within the production and delivery process is illustrated step by step.

Figure 39: Lithium distribution in the cell where the color of the anode indicates the concentration. a) After production, the complete anode is free of lithium. b) Immediately after production and in shipment condition, the lithium is only at the active regions of the anode. c) Over time the lithium diffuses into the passive part of the anode. d) The cell after long storage when equilibrium is reached. Every anode area has the same SOC, which is slightly lower than after production.

The cell was delivered at a state of charge of about 68%. The cells were stored for longer periods due to the shipment and the fact that the cells were stored at the research institutes before starting the test. Additionally, it is assumed that the cells were stored at the producer before the order was placed. This leads to the point that the balancing process between the active and the passive electrode has enough time to develop an even distribution of lithium in the cell itself. To ensure this, the lithium concentration was measured spatial-resolved within one of the delivered cells without any further electrical test. Unfortunately the edges of the sheets are too small to have reliable ICP-AES measurements so that the outfacing anode parts represent the passive electrode. The lithium distribution can be seen in Figure 40. The middle electrode shows very similar values for the lithium concentration at the edge with 63.4 μmol cm-2 and the middle with 68.9 μmol cm-2. A concentration of 68.9 μmol cm-2 is equivalent to a state of charge of 68%. The lower concentration at the edges of the electrode can be explained by the diffusion of lithium from there to the overhang. The outer electrodes 1 and 20 have, for the double sided samples, a drastically lower lithium concentration as a result of the unequal concentration of the inner and the outer part of the electrode. The separate concentrations can be seen in


the red and green boxes. The inner concentration is similar to the center but with the outward facing active material showing a lower concentration of roughly 30 μmol cm-2 (25% SOC). The variation between the three samples from front and backside is similar so that the values are assumed reliable. Additionally, the lithium concentration is slightly lower towards the edges at the outer electrodes, which is related to drift of lithium to the passive area of the electrode. The expectation of the outfacing electrodes to be charged in the same SOC compared to the active anode could not be validated, by the measured value of 35% SOC compared to 65% in the active part. One reason for the SOC difference could be the low voltage difference between these two storage SOCs, because they are at beginning and ending of the second graphite plateau. Furthermore the storage temperature was below 25 °C the whole storage time, which slows down transients.

Figure 40: Spatial resolved lithium concentration of fresh cell which was measured in delivery condition at about 68% SOC.

The initial assumption that the complete outfacing electrode was evenly charged to the active anode was not valid, as one can see in Figure 41, where a photo of one outfacing electrode of a 700 days stored cell is shown. Only the first 2 cm are highly lithiated, so that with the given time of three years (or even more) since production the process seems to not proceed any further. By this finding the totally used area of an outfacing electrode seems to also be dependent on the dimensions. For the used EIG cell, the totally used area comprises only 45% of the passive electrode, which reduces the passive anode to cover only 8.7% of the active area.

Lithium distribution of a fresh cell at 68% SOC

49.9 50.568.1

31.1

63.4 68.9

48.9 49.768.1

28.3


Figure 41: Outer anode of a cell that was opened at 0% SOC after 700 days in storage at 80% SOC. Only the outer 2 cm are showing a light yellow shine, which stands for a lithiation of 80% SOC or higher. The middle part seems to have a state of charge lower than 80%.

Influence on calendric ageing

Within the scope of this section are the calendric aged cells that are stored with the conditions given in Table 4. The remaining relative capacities at the discharge rate of 0.2 C are given in Figure 42 within the first 400 days. The variance of the initial cell capacities was small (average of 20.29 Ah with a variance of 2.2 mAh at 0.333 C), so that the focus is on the relative capacities. The left part of the figure represents the loss at 25 °C, the middle at 35 °C and the right one at 45 °C. As it can be seen, the capacity loss depends strongly on the SOC stored. As it can be also seen for 0.333 C discharge rate in 3.3.2 the capacity decrease is stronger for higher temperatures and also higher stored state of charge as it is often reported [91, 94]. Beside this, some cells displayed a capacity increase after the initial tests. This capacity increase was also observed in the tests of other researchers [93, 101, 103]. This is, as also Lewerenz at al. [95] describes, the influence of the passive electrode, and with this, the influence of the cell design.


Figure 42: Ageing curves of calendric stored cells at different temperatures and SOC for the first 400 days. The capacities were measured with 0.2 C at 25 °C.

It can be seen that the cells with a stored SOC below the delivered SOC of about 68% show a capacity increase in the first 250 days of ageing. The capacities increase depending on the stored SOC about 1.5% of the initial value at 0.2 C. This is higher for cells with a low SOC and becomes smaller with a state of charge close to delivery SOC. The cells that are stored above the SOC of 65% do not show an increase of capacity. As it was explained in the previous section, the passive anode was lithiated within the storage period between formation and cell opening. The passive electrode effect for cells that have a higher SOC than the before stored cells would lead to lithium flowing into the overhang, which would then result in a capacity decrease. On the other hand the effect would lead to a flow of lithium from the passive anode to the active part, if the SOC is lower than the delivery SOC, resulting in the witnessed capacity increase.

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Figure 43: Ageing curves of calendric stored cells in the first 400 days. The capacities were measured with a current rate of 0.333 C.

In Figure 42 the capacities for 0.2 C are shown. In comparison to this the first 400 days of the 0.333 C tests are displayed in Figure 43. For this higher current rate the capacity increase is higher and even cells that were stored above the delivery SOC show a capacity increase. This would mean that for all storage conditions more lithium was available in the active area. After the first check-up, the cells above 65% SOC lose capacity and cells with lower SOC gain capacity. This indicates that additional to the passive electrode effect, a second effect is present. This effect is responsible for the increase of about 1.2 % between the first and the second check-ups (65% SOC cell). The described second process seems to be an activation that is not happening for the tests at 0.2 C. The check-ups are designed in a way that the 0.333 C capacity tests are the primary tests and later in the check-up the 0.2 C tests are conducted, so that activation in the first cycle would be a reasonable explanation. The activation seems to be dependent on the SOC, but not the ageing temperature, as the increase is nearly the same for the cells stored at 50% SOC.

The physical evidence for the passive electrode effect is the measurement of a change in the lithiation at the different stored SOCs. For this, two cells from 20% and 100% SOC after 700 days were opened in post mortem analysis and the spatially resolved lithium distribution was measured. The results are presented in Figure 44. Both cells were opened at 0% SOC. Focusing on the averaged values at the middle electrodes, the cells both show a difference. This is related to the higher capacity loss and with SEI growth at the anode. When lithium is integrated in the SEI, the overall concentration is increased. For both cells, the concentration on the inner side

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of the first and last electrode (green) are similar to the averaged values in the middle. This shows that the lithium is distributed evenly in the electrode stack. The differences in both electrodes can be seen by the values of the outward facing regions of the anodes at top and bottom. The concentration of lithium, compared to the delivery state, is higher for the 100% SOC cell and lower for the 20% cell which proofs that within the storage also electrode parts that have a high distance to the active part of the electrode are lithiated.

Figure 44: Lithium distribution in calendric aged cells at 100% SOC on the left and 20% on the right. The values are based on the geometric active material area of each sample.

Against the expectations, the concentration in the passive electrode is not exactly the concentration of the state of charge, which would be about 100 μmol cm-2 for 100% SOC and 28 μmol cm-2 for 20% SOC. For this behavior, several explanations can be found. As shown for the cell in the delivery state, the passive anode was not completely lithiated, even for long storage times, so that the same is expected for the calendric stored cells. The samples for measurement of the outside concentration are taken over a wider range above the border of 2 cm so that perhaps the totally not used passive part of the outside is influencing the result. Further, both cells were stored about 4 weeks at about 25 °C prior to the cell openings at 0% SOC. This was because the relevance of a fast opening after the end of the test was not known yet. This may have helped so that the higher concentrations of the backside discharge to the active areas. As a conclusion it can be said that the passive electrode effect can be measured but the quantification was not possible the way, the analysis was conducted.

Lithium distribution at 100% SOC storage

29.8 30.424.8

38.9

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32.3 28.324

38.1

Lithium distribution at 20% SOC storage

13.8 17.812.6

19

14 14.5

13.8 17.214.8

16.8


Influence in cycling conditions

The influence of the cell geometry on cyclic ageing tests can be seen in the data from this project. The similarity in behavior of cells cycled at different middle SOCs and the calendric ageing cells was already elaborated on in 3.3.3. Here, the conclusion is that the cells are cycled with a small DOD around the middle SOC, so that the passive electrode is lithiated in the same way as the middle SOC would affect the passive electrode in a calendric storage test.

Data from cells which experience a high DOD, the anode is cycled over a wider voltage range, are more complicated to interpret. For the cycles, the mean voltage of the anode is the determining parameter. In Figure 45, the first 1,500 cycles of the cells with middle SOC are shown. The presented data shows that all cells have an increase of about 1%. Only the 80% DOD cells, which were tested in Ikerlan, show an initial short-time increase of 1.5-2% and then normalize to 1%. Depending on the DOD, the increase remains stable for different times. Lower DODs tend to hold the higher capacity longer than higher DODs, which is related to the overlaying degradation of the cell. The cells at 20% DOD show a minimum after 600 FCE which is related to a problem in the testing protocols. From 100%, 80% and 50% discharge depth cells were taken out of test after 2,400 FCE to 3,000 FCE to measure the lithium distribution in the cell. There were no cells available from test conditions with lower DOD, because the tests were stopped before valuable results could be generated.

Figure 45: Capacity increase for the cyclic ageing cells at 25 °C with a middle SOC of 50% and different DOD. For each test condition, a characteristic cell is plotted.

The lithium distribution in the cells with different discharge depth is shown by Figure 46. For the cells with 80% and 50% DOD no separate measurements of the outside

0 250 500 1000 1500Full Cycle Equivalents in #

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100% DOD80% DOD65% DOD50% DOD35% DOD20% DOD


and inside concentration were performed. For 100% DOD, as for the previously presented cells, the concentration of the active anode area (green) is correlated with the concentration of the center parts of the cell. The passive part of the anode, in red, shows a higher concentration of 26 μmol cm-2. This is slightly lower than it was in delivery condition. By the fact that the middle SOC of the cell was with 50% also lower than the delivery SOC, the migration from lithium to the active anode can be explained. With the assumption that lithium is homogeneously distributed in both the passive and active region, we are now able to calculate the lithium concentration in the outward facing passive anode. For both cells, the calculated concentration at the outside is about 27.5 μmol cm-2, which is again lower than the delivery SOC and similar to the measured concentration of the 100% DOD cell.

Figure 46: Lithium distribution of cyclic ageing cells with a middle SOC of 50% and different discharge depth. The cell on the left had a DOD of 100%, the cell in the middle 80% and on the right 50% DOD. For 80% and 50% SOC, no separate measurement of the inside and outside concentration was done. The values are based on the geometric active material area of each sample.

The current rate should not have an influence even if the ageing curves show differences in the capacity increase. Unfortunately, due to its unknown importance as well as different methods for the preparation of cells at the corresponding research institutes, the influence of the overhang cannot be studied equally for all conditions.

Approach for calculation of geometry caused transition

When focusing on the degradation of the material, the reversible influence by the passive electrode effect needs to be subtracted. To do so, a simple model approach for the capacity increase or decrease is chosen and will be presented in this section. The passive anode acts like a reservoir for lithium ions that is charged or discharged depending on the potential difference of passive and active anode. Electric

Lithium distribution at 100% DOD

18.5 24.722.9

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equivalent circuits are often used to describe the behavior of batteries [88], so that this is the first choice in electrical engineering. An electric equivalent circuit consisting of a source, a resistance and a capacitor emulates this behavior. The voltage source represents the active anode as an infinite source of lithium, the capacitor is the passive anode and the resistance is limiting the exchange current of lithium ions between both areas. Such a system can be solved with the start and final value method (equation (12)).

Figure 47: Electric equivalent circuit model describing the lithium flow to the passive anode.

(9)

The time constant can be calculated with a standard assumption that the process is completed after 5 . This process will be faster for higher temperatures and slower for lower temperatures. In the electric equivalent circuit the limiting component for the balancing process is the resistance, R, which will represent the temperature dependency. By comparing the process of capacity increase in the stored 50% SOC cell at the three temperatures, the time for the transient can be estimated. For 25 °C, the process last about 270 days, at 35 °C 170 days and at 45 °C 80 days. The values describe a process with an Arrhenius dependency as it is shown in the equation below:

(10)

The total amount of charge that is transferred depends on the capacitor. This is analogue to the maximum capacity increase, which is in the case of the passive electrode effect the SOC at which the cell is stored. This total amount is impossible to determine when the degradation is superimposed in the degradation curves. In Figure 48, the degradation curves of the calendric ageing cells at 35 °C are displayed with their linear degradation rate. The y-intersection of the linear degradation represents the charge that is going into the passive electrode or is coming from the passive electrode. Intersections above 100% indicate that a charge is coming from the passive anode and a value lower than 100% of the relative capacity is the result of a charge into this passive region.


The EIG cell was delivered in a SOC of about 65%, leading to a maximum capacity increase at the lowest SOC of 20% and a maximum decrease at 100% SOC. As mentioned earlier, the concentration compensation is a voltage driven process. Graphite anodes have plateaus in the voltage curve (Figure 49), which result in compensation current that is nearly zero in these plateaus. There is nearly no difference in the anode voltage between 80% SOC and 100% SOC, so that the passive anode will be charged to 100% SOC only after very long time. The compensation current will become nearly zero (as U ~ 0 V) if the last plateau, which starts at 75%, is reached, so that no further lithiation above 80% SOC may be expected in a reasonable testing time.

Figure 48: 0.2 C capacity loss curves of the calendric ageing cells at 35 °C and different storage SOCs. The average measured capacity of three cells at each condition with the standard deviation is shown in solid lines. The fit of the approximated linear ageing is shown in dashed lines of the same color as the ageing condition.

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reported that the measured lithium concentrations are also lower than expected. For example, in delivery condition of the cell, less than half the charge was found by measuring the outside anodes. A possible reason for an overestimation of the effect could be the participation of a much smaller area than calculated. For fitting the results, the measured intercepts are used as they mark the maximum in achievable charge. The resulting fit for the maximum value is:

(11)

This results in the final fit for the EIG cell after delivery at 68% SOC:

(12)

Passive electrode in automotive cells

To emphasize the importance of the electrode geometry and their influence on the ageing behavior, a selection of batteries from commercial electric vehicles were opened. The selected batteries are, in contrast to the EIG cell, all from a mass production and implemented in cars. To show the diversity of actual commercial vehicles, different car concepts were used. The manufactures pursue different strategies in pack design so that a good overview of the actual vehicles on the market is possible. The analyzed batteries originate from the VW Golf EV, Smart electric drive, Mitsubishi iMiEV, Nissan Leaf and the Tesla Model S. This also brings a broad selection of cell designs; starting from pouch in the Smart EV and the Nissan Leaf, prismatic cells in the VW Golf EV and the Mitsubishi iMiEV, and to round cells in the Tesla Model S. Also the size of the batteries ranges from 3.2 Ah up to 50 Ah. All important parameters are listed in Table 9.

Table 9: List of commercial vehicles and their cells. Also listed are the anode overhang and the maximum potentially increased capacity by the passive electrode effect.

Vehicle Cell design Nominalcapacity

Excessanode share

Maximumtransferable Capacity

VW Golf EV Prismatic 25 Ah 8 % 6.4 % 1.6 AhSmart EV Pouch 50 Ah 7 % 5.6 % 2.8 AhMitsubishi Prismatic 50 Ah 8 % 6.4 % 3.2 AhNissan Leaf Pouch 32.5 Ah 10 % 8 % 3.25 AhTesla Model S Round 3.2 Ah 12.8 % 10.4 % / 0.33 Ah


As described in the paragraphs before, rising capacities as a result of the passive anode, mask capacity losses. This is notable when cells are stored in favorable conditions and we have a knowledge of the cell’s history. The overhang of the anode was described as passive electrode and had a share of about 11% in the EIG cell which resulted in a capacity rise over ageing of maximum 3% of nominal capacity. The passive anode area of the EIG cell was extremely high, by the big share of the backside coated top and bottom anode. The overview of commercial cells will give a feeling for the relevance of the passive electrode.

The Smart EV and the Nissan Leaf cells were both stacked pouch designs. Both also had also outward facing anodes that were covered with active material. This results in similar percentage share of passive anode as the EIG cell; roughly 7% for the Smart and 10% for the Leaf. The prismatic and round cells are all wound and not stacked cells. This different design leads, contrary to the expectations, to similar results. The iMiev and the Golf had an about 8% larger anode and the anode of the Tesla was around 12.8% larger by geometry. That the highest value is seen for the smallest cell can be explained by the fact that the side overhang for a proper alignment of the electrodes has to be the same size, irrespective of the cell’s capacity.

To see the influence of the passive electrode, the potential storage conditions for the highest impact of the passive electrode effect can be assumed. This would be if the cells are stored at a high SOC, which is most likely for electric vehicles, because most of the consumers charge their cars directly after use, enabling them to drive long ranges if necessary. The highest rise of the actual capacity would be possible if the cells are stored at the lowest possible state of charge, which is theoretically 0%. After a sufficient time period, the complete lithium from the overhang is flowing back to the active anode, increasing the actual capacity.

(13)

With the above stated equation (13), the maximum capacity increase can be calculated. The area AAnode is the total anode area, whereas the area ACathode represents the cathode area. The SOCBefore is the SOC of the cell, where the cell was stored, before any capacity was retained. In the case of the highest capacity increase, this would be 100%9. The SOCAfter is the SOC in which the cell is stored

9 As can be seen in the results of the EIG cell, the maximum amount of the passive anode is 80%

SOC, because the compensation is voltage driven an in graphite the last plateau has nearly no voltage difference, so that a further lithiation is prevented.


within the regaining period. A low SOC is here favorable for high capacities. CNominal is the nominal capacity of the cell under investigation. For the Tesla Model S cell, a maximum capacity increase would be 8% of the nominal capacity.

A direct result of this effect could be questionable reported capacities for used electric vehicles. When selling a used electric vehicle, storing the car at a relative low state of charge could lead to a flow of lithium from the passive to the active part. This would lead to an interim refresh of the battery for when a potential customer test drives the vehicle or even tests the batteries capacity. When the car is in the real-world use case again, where the battery is held at relative high SOC, the lithium is flowing back to the passive part again, leading to a fast decrease in available capacity. This could influence the vehicles price on used car market. It also could be used to avoid warranty cases because of low capacities. This shows the importance of the cell design for the analysis of the actual capacity. Without knowledge about the history, only imprecise conclusions about the state of health are possible.

Linearized degradation 79

Linearized degradation

According to the previously presented results, the initial increase in remaining capacity is related to the passive anode. The subsequent capacity loss is here in focus, because this is most likely linked to the degradation of the active material in the cell. To study the influence of stress parameters on the material degradation in the complex battery setup, the ageing rate in this part of the ageing curve is taken as a reference. The degradation rates are analyzed by their influence factor and a generalized degradation function is implemented. The function has to include all tested parameters like temperature, DOD, C-Rate and middle SOC as variables for time and full cycle equivalents as input factors. The presented function is valid if only a degradation mechanism is ongoing that was also active in the linear ageing phase. This limitation excludes the function for a use in an ageing model that has to simulate the breakdown of cells. The function is valid, if different ageing factors are compared with each other. The dependency of the state of charge can be seen best in the calendric ageing curves at 35 °C. Here, the highest resolution of test points is given. The remaining capacities in the previous chapter were always shown for 0.333 C, but at every third check-up also 0.2 C capacities were measured. The initial capacity rise was different, but the ageing slopes were nearly the same as you can see in Figure 50 for these cells. The degradation rates are fitted to the measured values of 0.333 C, because the higher amount of measurement points make the identification of outliers possible.

Figure 50: Comparison of the cell degradation measured with 0.333 C on the left and 0.2 C on the right. The slopes of the linear degradation are comparable.

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Table 10: Ageing rates of calendric ageing tests, measured at 0.333 C. For the storage conditions beside the SOC, also the corresponding voltage is given. The voltage enables in this case a better correlation, because the degradation mechanisms are correlated to the electrode potentials and not to the SOC, although they are directly linked.

InmAh/d.

100%SOC4.137 V

80% SOC 3.923 V

65% SOC 3.803 V

50% SOC 3.703 V

35% SOC 3.657 V

20% SOC 3.591 V

25 °C 0.604 0.157 35 °C 2.821 1.707 1.154 0.540 0.485 0.06545 °C 5.540 1.747

The ageing rate is calculated for each degradation condition so that a dependency from the stress parameters can be done. Firstly the calendric ageing tests are analyzed and a fitting for all stored SOC is conducted. The electro-chemical equivalent of state of charge is the stored cell voltage, so that this value is used for fitting. Equation (14) describes this relation, where is the fitted parameter, t0 the begin of the linear ageing with the capacity C0 and t1 is the end of the linear ageing with the capacity C1. Begin and end of the linear ageing phase is different for each ageing condition and selected individually.

(14)

The fitting of the degradation parameters to receive an overall ageing function is based on the works of Schmalstieg et al. [71] and is used to have an easy comparison of the material ageing to the findings in the post mortem analysis.


Figure 51: Dependency of the degradation rates from the SOC and temperature with the fitted lines in red.

The plotted degradation parameter over the voltage of the cell for all calendric cells can be seen in Figure 51. The cells at 35 °C show a linear trend over the voltage with only small deviations at 35% (3.657 V) and 50% SOC (3.703 V). Therefore, the linear function from equation (15) describes the voltage dependency for the EIG cell over the tested voltage range. The fit would not be able at 25 °C and 45 °C, because there only two ageing rates are available. The fitting parameters a1 and a2 are fitted for the cells at 35 °C are written in equation (16).

(15)

(16)

A linear dependency between the voltage and the ageing rate was also found from Schmalstieg et al. [71]. They also explain that other cells with NMC vs. graphite show a staged ageing behavior, resulting in the influence of the graphite anode [88, 91]. The passive anode would also result in a staged ageing behavior and was not mentioned by them. This cell clearly does not show this staged behavior, probably because the anode does not show distinct plateaus at moderate current rates as it is shown in section 7.2 and the influence of the passive anode was considered.

For the temperature dependency the Arrhenius equation is often used. In equation (17) EA is the activation energy for the degradation process, R the gas constant and T the temperature in Kelvin. The parameter a3 is a scaling parameter to match the degradation rate.

3.4 3.6 3.8 4 4.2Volatge in V

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(17)

(18)

Figure 51 on the right shows the good accordance of the fit for the 50% state of charge cells with the parameters given in equation (18).

To combine both degradation rates, the test point at 35 °C and 50% SOC is used, because it is covered with both ageing functions. The two fitting functions do not exactly match at this point so they are scaled by the average value of both functions. The average Ø value is calculated as following:

(19)

The separate functions for voltage and temperature dependency are scaled with the averaged value Ø and are combined like it is presented in equation (20).

(20)

(21)

The complete ageing matrix with all parameters combined is given in equation (21) and is used for all ageing calculation in this thesis. Further, this function is used to subtract the calendric share of the cyclic ageing tests.

For the cyclic ageing conditions more stress parameters have influence on the degradation, the current rate in charge and discharge direction, the depth of discharge, the middle state of charge and also the temperature.

(22)

To be able to calculate the degradation rates for the depth of discharge, the calendric influence needs to be eliminated. For this, it is assumed that the cells stayed the whole ageing time in the corresponding middle SOC. So it is possible to calculate the pure calendric ageing and subtract this from the total capacity loss. After this reduction, only the influence of ageing by cycling in different discharge depths remains. The ageing rates are listed in Table 11 and the resulting graphs are displayed in Figure 52.


Table 11: Corrected degradation rates for cells with a middle SOC of 50%.

InmAh/FCE

100% DOD 80% DOD 65% DOD 50% DOD 35% DOD 20% DOD

25 °C 1.208 0.823 - 0.391 - 0.15335 °C 2.879 1.667 1.390 0.649 0.507 0.23245 °C 6.980 5.326 3.921 2.763 1.846 0.964

The temperature dependency is fitted by an Arrhenius function. For the DOD a linear fit was selected, because only at 35 °C a more stepwise or quadratic function would be possible. The other measured temperatures show a nearly linear behavior. Similar to equation (19) a combination point for temperature and DOD was selected, this was 45 °C and 80% DOD. The resulting function with the identified parameters is given with the following equation:

(23)

Figure 52: Degradation rates for the dependency from the discharge depth and their temperature dependency after subtraction of the calendric ageing effect.

In the section before, it was mentioned that the similar behavior of the cell ageing in dependence from the middle SOC and the calendric ageing can be traced back by the influence of the calendric ageing on these tests. When subtracting the calendric share, no dependency form the middle SOC can be seen. This is interpreted as there being no additional dependency from the used SOC while cycling.

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Figure 53: Cyclic ageing cells that were cycled at different middle SOC at 35 °C with 20% DOD, for which the calendric influence was substracted. No further degradation mechanism can be identified.

The charging rate displayed, that there is a limiting for performance. When charging rates exceed 1 C the normal degradation is super-posed by the rapid breakdown so that the investigation of an linear ageing rate is not possible anymore. Because the breakdown is not correlated with the material ageing we are focussing on, the validity of the ageing function is limited to charging currents up to 1 C. For the discharge direction with the measured data, no dependency between the discharge current rate and the linear degradation could be identified, so that there is no dependency in the degradation function. This is in accordance to the datasheet values from the cell producer, where the recommended charge rate is given with 0.5 C and the maximum continuous discharge rate is limited to 5 C [68].

Summarizing the findings from this section, the separately found degradation functions for calendric and cyclic ageing can be combined to receive an overall degradation function as it can be seen in the equation below:

(24)

With this function, it is now possible to correlate changes in the active material or in the cell itself to the material ageing without the influence of the initial capacity rise or the rapid breakdown. All later presented results are compared to the ageing rates to see if the effect could be associated with the capacity loss of the cell.

0 200 400 600 800 1000 1200 1400 1600Full Cycle Equivalents in #

95

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105Cyclic capacities without calendric ageing

80% mid. SOC65% mid. SOC50% mid. SOC35% mid. SOC20% mid. SOC

Rapid cell break down 85

Rapid cell break down

The degradation of the lithium-ion cells was described in detail in section 3. There it is explained, that the degradation splits up into three phases. This section will take a deeper look in the last phase of ageing, the rapid break down of the loss of capacity. Losing a high amount of capacity within a short time or just a few cycles is a major change, compared to the low ageing rates that the cells showed before, so that it is assumed that the main degradation mechanism changes. Lithium plating is the most probable degradation mechanism, where a huge and fast capacity loss is experienced.

Lithium plating

The metallic deposition of lithium on the anode surface was already described in section 2.2.1 but will be summarized here as well. Typically, lithium is intercalated in the graphite particles of the anode, but if the amount of delivered lithium ions at the anode surface is too high, the intercalation is not favored anymore. The surface of the anode is than fully lithiated so that the potential of the particle is dropping to or below 0 V vs. Li+. When this happens it is thermodynamically more favorable for the lithium ions to deposit on top of the particle in metallic form [104]. Lithium has, in this state, the tendency to deposit in dendrites. This might potentially lead to short circuiting the cell. The deposited lithium reacts with the electrolyte and forms a similar layer as the SEI [104]. This reaction consumes lithium ions and electrolyte so that lithium plating reduces the amount of electrolyte and lithium ions that could be used for the charge and discharge process. This results in additional capacity loss. Furthermore, the thicker layer on the anode results in a higher internal resistance. Not all lithium that is deposited on the anode is lost in this reaction, Smart et al. [104] showed with their testing that they could regain some amount of lithium by stripping. A quantification of the exact recovered part is unfortunately not possible, but will depend on many factors such as electrolyte composition, amount of plated lithium, morphology of the separator, pressure, and temperature. Petzl et al. [105] state that they could detect and quantify the amount of plated lithium in commercial LFP cells by using the differential voltage analysis.

The identification and quantification of plating is a hard challenge, because metallic lithium reacts directly in the atmosphere. Even when working in a protected environment (e.g. an Ar filled glovebox) reactions with used cleaning solvents like isopropanol will happen. Further the distinction of lithium in a metallic form and in an organic, or inorganic compound is possible with just a few methods, like nuclear magnetic resonance (NMR), which was not available for the investigations presented.


The method to identify lithium plating in this thesis was an optical analysis. When lithium deposits on the anode, the color of the anode changes from black to blue, to red, to yellow, to a metallically silver or gray depending on the lithiation state [106] as it can be seen in Figure 56 or Figure 58.

The quantification of the deposited lithium was done with the ICP-AES, whereas it has to be mentioned that the measured lithium content also includes the lithium that is still intercalated in the graphite and the lithium that is bound in the SEI. So the values just help with a first assumption about the amount of lithium.

Post mortem of cell in the linear degradation phase

With the postulation of lithium plating as the main reason for the drastic capacity loss, it is necessary to investigate if cells that are in the second phase of ageing display plating. For this, a cell that was aged at 35 °C at 100% SOC, from calendric tests was opened with 97% initial capacity. Ageing cells at 100% SOC has the highest likelihood for lithium plating, because the anode potential is the lowest and with this closest to the plating potential. The plating could occur due to overcharging in the check-ups or uneven charge distribution within the float storage.

Figure 54: Anode and facing separator of a 100% SoC 35° C cell from calendric ageing with 97% of initial capacity. The anode and separator show lithium plating at the edge. The color of the electrode changed around the plating which indicates an internal short circuit due to change of local state of charge.

In the post mortem analysis, the cell had a normal optical appearance, but two of the electrode sheets, in the center of the cell (sheet 10 and 11), showed lithium plating at


the edge of the electrode which is shown in Figure 54. The plating was local to just a small area at the edge and about 5 cm long. The cell was showing a high degradation rate so that it is possible that a superposition of the onset of lithium plating and the capacity loss by other degradation mechanisms was seen in the ageing curve. This mainly shows that cells far away from the normal plating conditions of high current rates and low temperatures [97] show plating, which is probably induced by inhomogeneities at the edges or by a difference in local capacity. Especially at the edges, the missing pressure from the facing cathode could be missing, so that local drying-out could result in overcharging of other areas.

Post mortem of cells with break down

For analyzing the mechanism of cell breakdown cells before and after this event have to be studied to identify the changes. For this, it would be necessary to predict the future behavior of the cell, which is only possible if the cell behavior is known. In the project Batteries2020 many cells were taken out of test after the breakdown, but at one condition we were able to take a cell out of test just before and after this event. The cells arise from the 1 C cycling at 25 °C and 80% DOD. The first cell was taken out of test after 3,300 FCE at 90% remaining capacity. 200 FCE later the second cell was taken out of test with a remaining capacity of 54%. The third cell of this test condition showed swelling, why it was not taken into account for a post mortem analysis. The swelling probably arises from gas formation by electrolyte decomposition, caused by internal short circuits.

Figure 55: Degradation curves of the cells aged with 1 C in charge and discharge direction between 90% and 10% SOC at 25 °C. Two cells were analyzed in post mortem. The third cell had severe swelling so that had to be disposed. The part of the rapid capacity loss is zoomed on the right.


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As we could see in the previous section plating occurred at the edge of the electrode cells with only 3% of capacity loss. For the first opened cell at 90% (after 3,300 FCE) state of health, no drastic changes were expected. Within the opening, many anode sheets showed a frame like plating close to the edges of the electrodes. This is exemplarily shown for electrode sheet 14 in Figure 56. There, many bubble like starting points of plating are near the edge of the electrode. It has to be said that plating only appeared on the active anode and not on the passive overhang, as we can see clearly the cathode imprint on the anode. The bubble like circles shows a starting point in the middle of the circle, which has a higher lithium concentration and an edge to the next bubble. A detailed picture is shown on the right of this figure. This could originate from a gas formation at the cathode like it is described in [50]. The formation of a frame of lithium has to happen fast because it is not directly visible in the degradation curve.

Figure 56: Picture of the down facing side of anode 14 from the cell with 90% remaining capacity, from the cyclic ageing at 25° C and 1C/1C at 80% DOD and 50% mid. SOC. The electrode shows plating nearly at all edges except the edge at the current collector.


Figure 57: Picture of the down facing side of anode 14 from the cell with 54% remaining capacity from the cyclic ageing at 25° C and 1C/1C at 80% DOD and 50% mid. SOC. The electrode is completely covered with lithium plating and electrolyte reaction products.

The opening of the cell after the breakdown showed that the complete electrode was covered with a surface film, which is assumed to be metallic lithium and electrolyte decomposition products. In the cell with 54% of the initial capacity, all anodes were completely covered with this film. This plating layer seems to contain most of the mobile lithium in the cell which is the reason for the high capacity loss of nearly 50%. Klett et al. [107] and Lewerenz et al. [108] state that this layer is not permeable for lithium ions, at least in the given time of the capacity test, which would also explain the drastic resistance increase.

Model approach for cell break down

The findings of the previously shown cells and others of this ageing matrix indicate that lithium plating seems to be the main reason for the spontaneous capacity drop. A model approach for this process is presented here. From all cells that were opened in different SOH, an analysis about the occurrence of lithium plating was done, by taking single pictures of each electrodes front and backside. A mash of 5x5 was set up and the occurrence of plating irrespective of the ageing condition was marked. In Figure 58 the tendency for plating at the areas indicated by colors, from green, with nearly no tendency until the areal plating occurs, up to red with the highest tendency for lithium plating, is displayed. As previously mentioned the edges of the active anode surface had highest tendency for plating in contrast to the inner part where nearly no plating occurred. Also at the upper side of the cells, where the way to the current collector is lower has higher values for lithium plating.


Figure 58: Lithium plating distribution on the active anode area of all opened cells in different SOH. The green areas show a low tendency for plating, and red areas show a high tendency. The result is the relative occurrence of plating on the anodes of 15 cells with respectively 20 double side coated sheets, which results in 600 anode surfaces.

The theory would be that the reaction is triggered at the edge, and plated areas are not used for the charge and discharge process any more, which would lead to a fast movement into the inner part of the electrode until the capacity decreases drastically. The stepwise process is shown Figure 59. At begin of life, when no plating is covering the anode surface the limiting current rate for a fast capacity loss is above 1 C, as it can be seen in 3.3.3. There, the areal current rate is for 1 C about 2.29 mA cm-2. This current density seems to be the limiting for the intercalation of lithium into the graphite without metallic lithium deposition. The area is nearly not reduced until a full frame of plating is reached. Continuing growth of a plating layer on the surface would decrease the used area exponentially so that a fast capacity loss and resistance increase would be the result, as we saw in the ageing tests.

0 50 100

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Lithium distribution on anodes

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Ex ante assignment of degradation effect 93

Ex ante assignment of degradation effect

Identifying the ongoing ageing mechanism by opening the cell is the state of the art technique in the field of lithium-ion batteries [81]. The method, like presented in the later sections 8 to 11, has the big disadvantage that the testing has to be finished. Techniques are capable of an ex ante assignment of the ongoing degradation are favored. With this, the complex cell openings could be supported. There are several methods where it is stated that ongoing degradation could be described, but the most important ones are the electrical impedance spectroscopy (EIS) and the differential voltage analysis (DVA). In this thesis only the DVA will be discussed in detail.

Electrical impedance spectroscopy (EIS)

The EIS has been used since the 1970’s for identifying the state of health of batteries. The stimulation of the battery is done with a low-level signal, either current or voltage, and the response of the system, voltage or current, is measured. By the shift and the amplitude, the complex resistance of the battery can be calculated at the selected frequency. By using different frequencies, the resistance of the battery at low and high frequencies can be measured. The complex resistance over the frequency represents the ongoing processes with different time constants. The double layer capacity of the electrodes is in the higher frequency range, the charge transfer of the electrodes at the medium range and the diffusion, as the slowest process, at low frequencies [109]. The measured frequency range is from mHz up to kHz.

One drawback of this method is that the measurement needs to be fitted to an equivalent electric circuit, to get information about the processes inside the battery. Unfortunately the system is under-determined, so that many solutions are possible and the start parameters for the ongoing processes need to be set by an expert guess. This expert guess could arise from theoretical literature values or from a physico chemical parameterization, as described in [75]. A further drawback is that geometrical effects, like the passive electrode, cannot be measured, because EIS has no spatial resolution.

Change in parameters of EIS measurements can be correlated with the ongoing ageing effects. This is presented in our publication in [110] for the EIG cells. For a deeper insight on the general fitting and the processes inside the battery it is referred to Witzenhausen [111]. Regarding to changes that could be identified within ageing, it can be referred to the thesis of Käbitz [112].


Differential voltage analysis (DVA)

The differential voltage analysis is the analysis of the derivation of a low current charge or discharge curve of a battery. The charge or discharge needs to be performed in such a low current rate that the cell is in a close to equilibrium state within the use. The advantage of a continuous charge/discharge compared to an open circuit voltage (OCV) measurement is that the result has a higher resolution in a shorter measurement time, due to the elimination of the time consuming equilibration pauses. Kinks in the charge/discharge curve indicate a single phases at one of the electrodes, mainly originating from the anode. For NMC cells, the overall steepness can be traced back to the cathode. By analyzing the general curve form and the shift of inflection points, loss of active material or loss of active lithium is indicated. This gives a good impression of the dominant ageing mechanism as an ex-situ method [77, 113, 114]. In Figure 60, schematic material curves of NMC and graphite are shown, which are similar to the measured curves of the cell in Figure 61. The cathode discharge curve on the left consists of two areas with an increased gradient at higher charged capacities. The first gradient arises from the nickel oxidation and the second from cobalt oxidation while lithium is extracted. The anode is typical for graphite with three plateaus visible and a high gradient at very low SOC. Two of the plateaus are very prominent and the third is only visible for very slow current rates. The potential difference between the two electrodes is seen as cell voltage and is shown schematically in green in the right figures.

Figure 60: From left to the right schematic half-cell curves of the cathode in blue and the anode in red with their derivation are shown. On the right, the superposition of the single electrode curves is shown to imitate the full cell behavior. All curves are in charge direction in regards to full cell.

Ex ante assignment of degradation effect 95

Figure 61: Plot of the half-cell curves of the tested cell on the top and their derivation on the bottom. The left plot shows the cathode, the middle plot the anode and the right plot the full cell.

To compare the theoretic idea and the measured value, the cathode vs. lithium, anode vs. lithium and full cell voltage curves and their derivation is given in Figure 61. The cathode shows a less dramatic change in gradient, but the basic curve behavior is the same. The anode shows the expected behavior. The plateaus can be detected by the peaks between the plateaus. The full cell shows a smoother curve shape than the schematic in Figure 60. The gradient changes are less distinct but can be seen clearly. The balancing of the cell can be seen here as well, where the anode has typically a capacity about 15% larger than the cathode. The shift from the first to the second plateau is in the half cell at around 60% SOC (at 4 mAh). In the full cell, the shift can be detected at around 70% SOC. The second characteristic point in the coin cell appears at 15% (1 mAh) which we see in the full cell at 10% SOC.

Figure 62 lists the results of the three main degradation mechanisms that can be monitored with the DVA. The first, and most likely mechanism, is the loss of mobile lithium. When this happens, the cathode is not fully lithiated any more when the cell is discharged, so that the half-cell curve of the cathode is shifted against the anode when the active lithium is lost. As a result, the detectable characteristic points of the anode keep a constant absolute distance, but the gradient of the cathode rises earlier in the charge so that around 50% SOC increasing values for the derivation arise.

The second and for this thesis most interesting degradation mechanism is the loss of active cathode material. This is shown in the middle of the Figure 62. When the cathode loses active material, the cathode gets smaller in terms of capacity compared to the anode, which changes the balancing. Characteristic points are not visible, but the compression of the cathode curve changes the total gradient of the

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Dissolution by HF

HF is a molecule of hydrogen and fluorine (HF) and is a very reactive acid that can also be formed inside a lithium-ion battery. One way where HF is formed inside a battery is when the typically used conductive salt lithium hexafluorophosphate (LiPF6) reacts with water (see equation (25) from [122] and (26) from [51]), which is favored at high temperatures [55, 122, 124]. The resulting products within the HF formation are different, depending on the source in literature:

(25)

(26)

Water is, in ideal cases, not present inside lithium-ion batteries. However, traces are present by residual moisture of incompletely dried components. Electrodes, separator and also the housing are dried before assembling under vacuum at high temperatures, but also after this procedure traces of water might still remaining in the small pores. Unfortunately there are no values published for remaining moisture, so that it can be assumed that there will be a wide spread. Definitions are much clearer for the electrolyte where it is typically delivered with a water content less than 20 ppm [125]. The formation of HF could be drastically reduced by the use of a fluorine free conductive salt; unfortunately the fluorine is important for the aluminum current collector. It builds up a protective layer that minimizes the corrosion losses as it is discussed in section 11. HF is an aggressive acid which attacks the surface of the cathode particle. The ions at the surface are dissolved from the crystal structure and can freely move in the electrolyte. For manganese spinel, the dissolution by HF was described by Shin et al. [121] with the following reaction:

(27)

This indicates for NMC-based electrodes, that the manganese could be in a fluorine connection when dissolved and the oxidation charge in the structure is taken by other transition metals. Further we see that the lithium is transformed to lithium fluoride which means that the dissolution by HF is accompanied by loss of active lithium.

Disproportion reaction

When a cathode is charged or discharged over the cathode voltage limits of the theoretical minimum or maximum plateaus, the crystal structure is destroyed by Jahn-Teller distortion [116], but this is just valid for manganese spinel cathodes. Then, Mn4+ is reduced to Mn3+. The Mn3+ ions tend to split up into a more stable

Dissolution of transition metals 101

form, which results in the formation of the more stable Mn4+ and the soluble Mn2+ [126]. This process happens for manganese spinel only at the defective surface of the particle [126, 127]. In NMC cathodes the oxidation state of the manganese ions is in ideal case not changed while the cell is cycled so that a disproportion would not be possible. The fact that manganese is not changing its oxidation state, and with this stabilizes the structure is the reason for the use today’s cathode materials. But probably on the defective surface or oxygen vacancy, the manganese ions change their oxidation state, caused by a higher or lower lithium concentration at the edges [44]. The defective surface of NMC electrodes and a change in crystal structure was shown by Lin et al. [128] with scanning transmission electron microscopy (STEM), just after the cell had contact with electrolyte. Shaju et al. [129] showed that even for NMC, a small content of Mn3+ can be measured with XPS. The disproportion reaction mainly takes place for the lower state of charge in lithium-ion batteries, because at the higher potential of 4.5 V all Mn3+ should be oxidized to Mn4+, which is not soluble [44]. That means that the dissolution at higher potentials is probably acidic driven by HF.

Effects of re-deposition on the cathode

The transition metals that dissolve are freely moving in the electrolyte so that they deposit on all components in the battery. Beside the deposition on the surface of the anode, a small part re-deposit on the cathode again [120, 121]. In literature only a limited number of reports are published, that cared about the re-deposition of manganese on the cathode [120]. Shin et al. measure the re-deposition while storing cathode material in electrolyte without a counter electrode, where the transition metal could deposit on. The problems in detecting re-deposited material in full cells might be due to the fact that the conventional methods like ICP-AES [51, 77, 79, 130] cannot differentiate between active materials and deposited. It is reported that the dissolved manganese ions, are deposited in the beginning of the ageing on the cathode as oxide compounds and in the later stages as fluoride compounds. The oxygen compounds, seem to have rather low influence on the electrical behavior [120]. One of the later deposited fluoride compounds, the MnF2, is a material that is highly resistive for electron and Li+ conduction, causing impedance rise of the cathode [131, 132]. The influence of the deposited resistive layer seems be big on the cathode and will cause capacity loss with higher currents due to a higher overvoltage loss [119, 122, 133]. The problems seem to not have a big influence if a counter electrode is used, because the majority of the ions will deposit on the anode [120]. The preferred electrode for deposition is the anode, the negative electrode, caused positive charge of the ion.


Impact of material loss on cathode capacity

While transition metals are dissolved, the host structure of the cathode is changed. This modification leads to a loss of active material and with this a decrease in capacity. This effect was described by Kim et al. [120] and Shin el al. [121]. They stated that the capacity fade by loss of transition-metal ions is not substantial, compared to other degradation effects. The amount of transition metal that is lost and with this the lithium storage places that are lost are small compared to the overall capacity.

For the EIG cell, the maximum amount of lost active material that was measured was 0.1% of the total NMC. This measurement was done at a cell that was stored at 100% SOC, at 35 °C for 700 days. With the nominal capacity Cnom and the known utilization of 51.9%, the loss of lithium storage places due to dissolution can be estimated with the following equation, assuming that each dissolved transition metal ion leads directly to a loss of a lithium storage place:

(28)

This result in an estimated loss of 10.5 mAh which is rather small, compared to the total capacity loss of 2.4 Ah. Furthermore, the loss of active material is not necessarily resulting in a capacity loss. Within the formation of the SEI in the first cycles, mobile lithium from the NMC host structure is lost. When now small amounts of active material is lost, the lithium ions have enough free intercalation places in the host structure by filling up the empty places from the SEI formation loss.

Effects at the anode/electrolyte interphase

The greatest impact of the transition metal loss is not on the cathode itself, but is induced by it on the anode. It is often measured, that the transition metal ions that are dissolved by the above explained effects are deposited on the anode and destruct the protective layer of the anode, the SEI. The dissolved transition metals interact with the electrolyte interphase leading to a capacity loss by SEI increase [120, 134] . It is also stated, that the presence of transition metals at the anode changes the morphology and their composition [121, 127, 135]. Further the dissolved metals are also known to form highly resistive layer which increases the overall anode impedance [134]. Börner et al. [116] found MnF2 at the anode surface, which was described as a product of HF dissolution earlier, that is known to accelerate the electrolyte decomposition on the surface [121, 135, 136]. Shin et al. [121] explain that the manganese ions are mostly deposited at the interphase of graphite to the inorganic SEI layer and induce there side reactions resulting in a defect layer [137, 138]. They also state that the manganese ions have a catalytic effect on the SEI

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same procedure in the ICP-AES as it is explained in 4.1, but with an additional focus on the transition metals [77, 79, 99, 100, 130]. All measurements are done like it is explained in 4.1. In contrast to Abraham et al. [134], where secondary ion mass spectrometry measurements (SIMS) are used for analyzing the transition metal dissolution, with the ICP-AES method it is possible to make a quantification of the transition metals on the anodes.

We do not expect a dependency from the state of charge of the cell at the moment of the cell opening, because the accumulation of transition metals at the surface is a process that is proceeding over time and is not changing within the charge or discharge of the cell. So cell that showed differences in the state of charge within the cell opening are not expected to have differences in their transition metal content.

All samples were measured spatially resolved, so that the lateral distribution of the transition metal can be analyzed. The cells only displays a lower metal concentration on the outward facing anode parts, which have no directly facing cathode. The missing of a facing cathode makes the diffusion path from a cathode to the outfacing anode much longer, so that this fits with the expectations. The inner parts with a counter electrode had the same concentration, within the measured accuracy, so that only the values from the inner part of the middle electrode are used for the analysis.

As also Waldmann et al. [81] explained, another method to identify the dissolved transition metals at the anode is energy-dispersive X-ray spectroscopy (EDX), which is a method for element analysis and often combined with a scanning electron microscope (SEM). It uses the principle of irradiation of a sample with electrons and detection of the generated characteristic X-ray photos [81]. Each element has a unique atomic set of peaks, depending on the electron configuration, so that the intensity and peak position can be used for material identification and quantification. Today’s devices are not capable of detecting lithium due to low energy resolution. There is only the option to measure heavier materials (Heavier than beryllium). Even if a quantification of the elements is possible, a drawback of this method is, that only the surface is measured, so that an accumulation in the bulk, or below a covering layer is not measurable. The typical penetration depth is about 1μm [139]. For the thesis it was possible to use the device at the RWTH ACS lab10 for testing the applicability of this method to the dissolution of transition metals.

The SEM pictures with the measured elements are shown in Figure 68 and Figure 69. On the left a fresh anode is displayed. Edges of the graphite material are clearly visible and the structure of the material can be identified. On the right the sample of a cell, which was aged at 100% SOC storage and taken out of test with 3% of capacity 10 A special thanks goes to Shuo Yang for the help in measuring the samples at the inorganic

chemistry lab at RWTH Aachen university.

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dissolution rate [116] whereas Waldmann shows a nearly linear dependency of manganese dissolution [77]. These contrary results are compared to measurements and discussed in 8.6.1 for the calendric ageing conditions and for the cyclic conditions.

Also conflicting results and statements are given on manganese dissolution. Shin et al. [121] state that the dissolved metals have a catalytic effect on the SEI decomposition, which would result in a nonlinear dependency between SEI increase and transition metal agglomeration on the anode. Contrary to this, Kim et al [120] measure a linear dependency of dissolved Mn which would be in conflict with a catalytic influence of the manganese. Beside this the voltage the cell is stored should have an influence on the dissolution, measured with NMC [44], and also the current rate in use, measured with LMO, [116]. Higher current rates could lead to more defects on the cathode surface and with this more Mn3+ ions which would lead to additional disproportion reactions.

Influence of temperature and SoC

Some cells from the tests that are presented in paragraph 3.3.2 were taken to measure the dissolution behavior under storage conditions. With these measurements the dependency of the storage time, temperature and stored voltage is analyzed and compared to the findings of others.

Figure 70 shows the correlation of the ongoing effects inside the cells and the degradation rate. In the upper plots, the linearized capacity loss over the ageing time is shown for the three calendric test temperatures, with 25 °C on the left, 35 °C in the middle and 45 °C on the right. In the three graphs in the middle, the measured SEI increase is shown over the ageing time. The SEI increase is measured by the amount of lithium on the anode normalized on a fresh cell. In the fresh state at 0% SOC, the concentration of 11.7 μmol cm-2 was measured, which is the SEI after formation. The amount of lithium that is cycling between the anode and cathode in fresh state is 88.5 μmol cm-2. Aged cells, that show a higher concentration of lithium at the anode in discharged state, have passivated more lithium at the anode, which is seen as SEI loss. Passivated lithium by lithium plating would also be interpreted here as SEI increase. The lower graphs show the percentage of transition metals that could be found on the anode. 100% of the transition metal is the sum of all transition metals at the anode and cathode per cm².


Figure 70: The figure shows the correlation of capacity loss, dissolved transition metal and SEI increase. This is shown from the left to the right from 25° C, 35° C and 45° C, for selected cells.

The graphs of the SEI show the measured data for all cells that have undergone a post mortem analysis. For 25 °C only one cell at 80% SOC was disassembled. The cell shows a capacity loss of nearly 2.5% in the 700 days of ageing. The post mortem analysis shows, that about 5% of the initial active lithium is bound at the anode, probably in the SEI. Losing more lithium than the actual capacity loss is technically only possible if the cell has an additional source of lithium. This could be the passive anode or that at the cathode more lithium is extracted. Which of these possible effects caused the lithium deviation, could not be clarified. Notably the absolute accuracy of the ICP-AES measurements is in the range of 1-3%, so that the increase by 5% could also be influenced by measurement inaccuracies. The relative variance between the 3 samples within one measurement was much lower than this. For

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35 °C more cells and with this, test points are available. The results of the SEI increase show that the cells group as expected. The cells with the lowest capacity loss show the least manganese increase on the anode. The cells at 20% SOC exhibit nearly no capacity loss, but shows an increase of SEI of 3% after 700 days. This is similar to the cell at 25°C. The SEI increase of the cell at 80% SOC is with 8% in good accordance to the capacity loss of 7%. The 100% state of charge cells are in the first two measurement points after 250 and 700 days show a slightly higher SEI increase, but are basically in good accordance with the trend of capacity loss. The latest opened cell after 800 days had a drastic increase in lithium content at the anode. The cell was opened at end of life with a remaining capacity of 79%. The cell faced in the last 100 days a severe capacity loss in a relative short time and within the opening plating on the electrodes, so that the cell already left the phase of linear ageing. For the third tested temperature of 45 °C two measurement points at 80% are available. The first measurement of the SEI is below the capacity loss curve, the second measurement point after 650 days is nearly at the same level as the capacity loss. Beside the 45 °C cell, the SEI increase is above the capacity loss, but in general in a good accordance. For the 45 °C cells, the linearized capacity loss could be inaccurate due to the early nonlinear capacity loss. This would also to deviations between the loss and the SEI increase.

The common theory about the SEI growth within the calendric ageing is that the SEI should be a perfect electric insulator. Unfortunately a leakage current is flowing, which lets lithium ions react with the electrolyte at the surface [31]. This effect would than depend on the stored potential of the anode. As we can see in Figure 71, above 70% SOC, the anode is in the last plateau so that the voltage at the anode of the cells stored at 80% SOC and 100% SOC should not differ too much. With the common theories, no big difference in the SEI growth of these two storage SOCs would be expected, but the difference can be shown. Beside the proposed effect of a remaining conductivity of the SEI an additional effect is necessary to make a huge difference. Due to the fact that the anode has nearly the same potential, the cathode has a higher voltage difference between these storage SOCs, so that a cathode induced effect, the dissolution and deposition of transition metals on the anode, could be the cause.


Figure 71: Anode half-cell curve with the storage SOCs marked. In the plateaus of graphite, the half-cell curve exhibits a slope because it was measured with a current rate of 0.2 C, so that the polarization has still an influence

The transition metal loss is also shown in the lower part of Figure 70 and is given as the sum of nickel, cobalt and manganese on the anode, compared to the sum in the complete cell. All cells show an increase of the values depending on the stored SOC and temperature. At 35 °C the measured values according to the SOC the cells are stored, as expected. The highest amount of transition metals was detected at the anode of the cell with the highest state of charge. The findings are also in a good accordance with the measured SEI increase, except the last measurement point of the 100% SOC cells. No drastic change, as it was observable for the lithium concentration, could be seen. The measured SEI increase was caused by lithium plating, which raises the lithium content on the anode and is not significantly related to a strong increase of dissolved transition metal. A possible reason for the increased SEI amount at the 35 °C cells with high stored SOC could be found in the transition metals. The observable increase is correlating with the transition metals found on the anode. In 8.4, the influence of transition metals with a special focus on manganese was explained. The clear correlation of the measurement data is showing that the dissolved transition metals at high cathode potentials can make a difference in SEI increase while the anode potentials remain constant. For the temperature dependency, the 80% SOC tests are compared. The increase in dissolved transition metals can clearly be seen in all three temperatures, the concentration after 700 days shows a linear increase with the temperature from 0.0005% to 0.0015%.

The measured data is unfortunately not sufficient to set up a complete model of the dissolution and its influence on the cell ageing. To achieve this, more cells must be opened, which was not possible by the limited amount of available cells and also the time for cell openings.


Influence of cycling depth and current rate

The dependency of the degradation from the cyclic influence factors was discussed in section 5. The most important finding was that the degradation is only dependent on the DOD and temperature, assuming the charging rate is below 1C. Furthermore, the calendric ageing has to be kept in mind. To analyze if the physical degradation effect responsible for the capacity loss could be the dissolution, a selection of cells also underwent the post mortem analysis. First the results that are shown in Figure 72 of different discharge depth at 25 °C are discussed. For the visualization of the results, the same style is used as before, in the top of the picture, the linearized capacity loss is shown, in the middle the SEI increase and in the bottom the deposited transition metal on the anode is shown. The comparison of the SEI increase and the capacity loss shows, that for 80% DOD and 50% DOD a good accordance is reached. The linear loss of the cells at the openings is about 8-9% of initial capacity, which correlates well with the SEI increase of 7-8%, showing, that the main capacity degradation mechanism is loss of active lithium to the SEI. The calculated loss of the 100% DOD cell is 16%, but the measured SEI increase is lower, 12%. The deviation of the SEI increase most probably results in the plating that was seen at the edges of the cell within the opening. As explained in 8.5, the samples for SEI and transition metal analysis are taken from the center of the cell and electrode. The plating of these cells could be observed at the edges so that the capacity loss by lithium plating could not be measured with the used technique, which explains the lower SEI increase for this cell. Furthermore, nonuniform deposition of the transition metals could have an influence on the results.


Figure 72: Cyclic aged cells at 25 °C and 50% middle SOC at different DOD. In the upper graph, the linearized capacity loss is shown, in the middle the SEI increase and in the bottom the share of dissolved transition metal at the anode.

Comparing the measured transition metals with the SEI increase indicates a good accordance. Qualitatively the concentration of the transition metals shows the same behavior as the SEI values. Concluding from this, the DOD has the same influence on the dissolution as it has on the capacity loss, higher DOD causes the cell to age faster. This can be explained by the fact that the transition metals dissolved at higher voltages at a higher rate, as it was shown for the calendric ageing tests. With a higher discharge depth and the same middle SOC, the cells are more often in the region of high cell potentials, which are less favorable for the cell.

A further influencing parameter on dissolution is the current rate [116]. As it is presented in the results of the ageing tests, the cells with high charging current rates had massive plating, such that they suffered a rapid breakdown. The discharge current seemed to have no major influence on this degradation. The large variation of currents that were tested at 35 °C was used to evaluate this. Cells from two charge

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rates (0.333 C and 2 C) and two discharge rates (1 C and 2 C) are used for this analysis. All other parameters are held constant. In Figure 73 the top graphs show the linearized capacity loss, which is exactly the same for the cells. The cells that are charged with 2 C are shown on the right. The cells lost until the moment of the cell opening more than 30% of initial capacity by lithium plating, so that the SEI increase (or plating) correlates well with the remaining capacity. Both cells show that in the testing of 200 days an increase of the transition metals were found at the anode. Subtracting the metal dissolution from the calendric results only about 0.0003% should be found, but the actual result is nearly three times higher, which suggests that the charge rate has a big influence on the dissolution. There is no big difference for the two tested discharge rates for 2 C charging.

Figure 73: Capacity loss, SEI increase and deposited transition metal shown over the ageing of cells with different charge and discharge rates.

At the lower charge rate of 0.333 C, the cell that was discharged with 2 C was analyzed after the breakdown with a capacity loss of 24%, which again matches with

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the measured SEI increase. Also, increased transition metal content was measured. The total amount is comparable to the cells that were charged with 2 C. In contrast to these cells, the transition metal content was measured after 2,000 cycles and roughly two years of testing. The comparison with the calendric cells shows that a concentration of 0.001% would be in the expected, so that the measurement of 0.0012% is in a good accordance with the data. The cycling with the low charge rate seems to have no big influence on the dissolution. The cells that were cycled with the lower discharge rate experienced the breakdown about 500 FCE earlier, which might be explained by difference in testing, like lower temperatures by less resistive heat generation. The dissolved transition metal of these cells is, despite the earlier breakdown, in the same region as the cell that was discharged with 2 C. Only the calendric influence can be seen if we limit the cycling to the same range as the valid currents for our model, which is in accordance with the given values of the producer [68].

Börner et al. [116] stated that the temperature whilst cycling has only a minor influence on the dissolution. To investigate this influence, cells from 0.333 C charge and 1 C discharge rate at 50% middle SOC and 80% cycling depth are used. There, cells at all test temperatures and different state of health are opened for analysis. The results are plotted in Figure 74. The calculated capacity loss is drastically different for the test temperatures, so that an influence by temperature needed to be clearly visible in the results. At 25 °C, the battery has lost 8% of initial capacity which is the same as the measured SEI increase. For the middle temperature of 35 °C three cells in total were analyzed. Two of them were taken out at the same point in time, after 1,100 FCE. The cells lost about 10-13% of capacity and showed a SEI growth by 8%. These cells already had a significant amount of plating at the electrode edges so that the higher capacity loss is probably caused by the lithium loss in plating, which is non-uniform as can be seen in section 6. This was also the case for both cells at 45 °C, which also show a drastic difference between the calculated capacity loss and the measured SEI.

The transition metal data of the anodes show a linear trend that correlates with the SEI increase, except the last measured point at 35 °C. Here the same behavior as for the calendric ageing cells is observable. It is a linear increase of the measured transition metals and an exponential increase of lithium on the anode by plating. For all cells, where no plating was measured, the increased transition metal content can be correlated with the SEI increase. Even with the few measured points a temperature dependency of the SEI growth can be seen, which allows the conclusion that also the transition metal dissolution is dependent on the temperature. This finding is in contrast to the results of Börner et al. [116] who tested in the same temperature range. Börner et al. used LTO as negative electrode, when measuring the deposition of manganese. The change in cell system could have an influence on the temperature influence. Compared to the here presented calendric results, which


are in accordance of the findings of Waldmann et al. [77], a temperature dependency for the transition metal dissolution within cycling ageing tests is plausible.

Figure 74: Capacity loss, SEI increase and deposited transition metal shown over the ageing of cells with 80% DOD, 50% middle SOC and 0.333 C charge and 1C discharge rate at three test temperatures.

Conclusion for influence of dissolution on overall cell ageing

Referring to the topic of this thesis, the ageing of NMC-based lithium-ion batteries, the dissolution seems to play a major role at higher state of charges. Even if the SEI growth was identified as the major loss mechanism, this was at least partially triggered by the dissolved transition metal.

In the given operational range, a dependency from the SOC at storage, the temperature and cycling temperature was seen. A dependency from the middle SOC whilst cycling is obvious due to the analogue behavior as the calendric aged cells. This could not be verified with the available tests. These are the same stress parameters that were identified when describing the linearized capacity loss of the

0 500 1000 1500 2000 2500Full Cycle Equivalents in #

0

20

40Cyclic ageing at 80% DOD / 50% mid. SOC / C/3-1C

25 °C35 °C45 °C


0

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cell, so that a clear correlation can be seen. A physical function for the dissolution in dependence of the stress parameters could not be found with the number of tested cells. To test this, more cells per test condition would be necessary. This would allow for the change over time to be measured with more precision.

Advice for improved operation strategy in electric vehicles

Summarizing the findings to the dissolution effect, it can be seen that some operation conditions should be avoided in the application to guarantee a long battery life. This advises only focus on the dissolution. However, the dissolution is related to the SEI growth, which is likely a result of the dissolved metals.

High SOCs in storage should be avoided for a long calendar life of cells. This is contrary to most of the use cases. Electric cars are often directly charged after a trip to maintain a good flexibility with a long range. For commercial applications, where the trip length are more predictable than for private purposes, just-in-time charging of vehicles before the trip is proposed. This will become more important if the upper cutoff voltage is increased for a higher energy density. The used voltage for the EIG cell is with 4.15 V low compared to today’s possibilities. Samsung smart phones are charged up to 4.35 V [140], which accelerates ageing. In an application, where the battery has a lifetime of two years, this is not as important, but should be in focus if the cells are used in electric cars or stationary storage applications. The operational temperature also has influence on the dissolution. This has to be taken into account by the manufacturers if they design a battery pack for different climatic regions.


Structural changes 117

Structural changes

One of the degradation mechanisms that is discussed very often in literature are the changes of the crystal structure of the NMC material [27, 51, 77, 141]. The influence of this effect is seen differently, some report that the changes that they see have a major influence on the cell behavior [27, 51] and others state that the changes that appear are minor so that their influence can be neglected [77, 142]. Some researches see big changes in the material, but assign them only to the missing lithium in the structure [77, 142, 143].

In this section, the basic properties of the structure of NMC materials are explained and also the changes that appear within the charge and discharge process. Further the effects, suggested in literature, are evaluated by their influence on the overall battery ageing. Also a detailed analysis on the stress parameters and their influence on the changes in the crystal structure and capacity loss is done for the EIG cell.

Ideal and real structure of NMC

The cathode material of this thesis is a layered oxide with the transition metals nickel, manganese and cobalt. The structure of this material is of the -NaFeO2 rock type, which is a hexagonal structure of the R m space group [144, 145] and is shown in Figure 75. The structure consists of consecutive layers of lithium, oxygen and transition metals. The exact occupation of the transition metal layer is not defined in literature. The two possibilities, first each layer is only filled with one transition metal and second, the transition metals are mixed in each layer. Lithium ions can be extracted from this structure leaving vacancies in the lithium layer [146]. When lithium ions are removed from the structure, the charge of the ion that is shared with the oxygen needs to be compensated. This compensation is done by a change in the oxidation state of the transition metals to a higher oxidation level. Depending on the redox couple of the materials used the extraction voltage of lithium changes [147]. The oxidation state for each transition metal is Ni2+, Mn4+ and Co3+ respectively [43] in the discharged state (fully lithiated). While charging, or extracting lithium, first the nickel ion changes the oxidation state from Ni2+ to Ni4+. The nickel redox couple is responsible for most of the charge in a 1:1:1 NMC up to 2/3 of the total capacity. This originates in the fact that for the change of one nickel ion, two lithium ions can be extracted. The cobalt redox couple Co3+/Co4+ is involved at higher state of charge above 2/3 of the extracted lithium. Manganese is not involved at all stays in the Mn4+ state over the whole lithiation range, which keeps the crystal structure stable [148-150]. In the used EIG cell, the 4:4:2 composition leads to a different participation of the transition metals in the discharge process. By the higher amount of nickel to cobalt ratio, compared to the 1:1:1 NMC, nickel contributes until 80% of extracted


lithium, cobalt would only be involved above this. With 4.15 V as cutoff voltage (58% of lithium extracted), the region where cobalt would be used is not reached.

Figure 75: Unit cell of NMC in R m structure (modified from Liu [42]). The structure consits from consecutive layers of lithium, oxygen and transition metals. There is no information in literature if the transition metal layers are pure or if the metals mix.

In the R m unit cell, the lithium-ion is located at the 3a site (0,0,0), the transition metal at the 3b site (0,0,1/2) and the oxygen at the 6c site (0,0,1/4) [151] . In practice, all produced materials show some deviations from this, small amounts of nickel and lithium ions switch their positions due to the similar ionic radius. Lithium has an ionic radius of rLi+ = 0.74 Å and nickel with rNi2+ = 0.70 Å. Manganese and cobalt do not show this behavior, because of their larger ionic radius [143]. This mixing of nickel and lithium is often called “cation mixing” and is discussed as a degradation of the crystal structure.

Depending on the exact composition of the transition metals, the lattice parameters of the structure differ. The number of publications describing the structure of the 4:4:2 material is low, so that only two parameter sets for the crystal data could be found. They are listed in the table below. This includes the dimension of the unit cell in a (a=b) and c-axis, the volume of the unit cell and the factor c/3a, which is a good indicator for cation mixing. A value closer to 1.633 indicates that more nickel ions are present in the lithium layer [152]. The values for the used material are originating from a fresh cathode at 0% SOC, as explained before, some lithium is already lost to the SEI formation so that no ideal Li1(NMC)1O2 material is present. The influence of the missing lithium is described in 9.3. In general the parameters of the material are


in accordance with the values from literature. The value for the a-axis is lower and the c-axis is higher than the literature values. This results in a slightly higher value for c/3a which means less ion mixing. The volume is in the range of the literature values.

Table 12: Literature and measured crystal parameters for 4:4:2 NMC.

Parameter Ma et al. [153] Li et al. [143] Measurementa 2.866 Å 2.871 Å 2.864 Å (± 0.001)c 14.254 Å 14.267 Å 14.283 Å (± 0.001)Volume 101.408 Å3 101.838 Å3 101.448 Å3

c/3a 1.658 1.656 1.662

Identification of crystal structure

The crystal structure is typically measured by X-ray diffraction, where the sample is in the form of single crystals. This is contrary to the most materials that are used in lithium-ion batteries. These materials consist of particles which again consist of small crystallites in a random orientation. To measure this, the X-ray powder diffraction is the primarily used tool. The functioning principle of X-ray diffraction is the interference of refracted X-rays by the crystal structure. X-rays of a defined wavelength, depending on the used material, are emitted in the source. In the used device for this thesis, a Panalytical Empyrian, the X-radiation is produced in copper source. Depending on the wavelength of the x-rays, the distance of the lattice planes (dhkl) and the angle of the hkl the rays are reflected and a positive interference is measurable. The measured intensity, which is an integration of counts over a given time, is plotted over the angle 2 . The relationship between these parameters is defined in Bragg’s law that is given in equation (29).

(29)

(30)

The distance of the lattice planes can be calculated for hexagonal structures with equation (30) so that for a given structure the expected diffraction peaks are calculable in advance. Further, a comparison of measured data with the ideal structure is possible and the real crystal parameters can be defined.

For the measurement of the crystal structure, 20 mm diameter double sided samples were taken during the post mortem routine. The samples were taped on an aluminum sample holder that is used in the multi sampler unit of the XRD. The measurement of


the cathode was done under ambient atmosphere. A contact with oxygen could only be prevented with special containers or sealing of the sample. The comparison of Kapton sealed samples with ones that were exposed directly to the environment showed that the oxygen had no influence on the measurable crystal structure of the samples. Further the sealing had the disadvantage of reduced intensity of the structure under investigation. Therefore, all samples of this thesis were measured in ambient atmosphere. The measured 2 range was from 10°-75° 2 , with a step size of 0.007° 2 and a scan step time of 60 s per step. A further description of the device with the used setup can be found in [26].

In Figure 76 the measurement results of a fresh cathode is plotted. It displays the peaks of the electrode material and the electrode additives. Against the expectation, no separate aluminum peaks are visible. The peak of graphite at 26° 2 has no further relevance for the structural analysis of the NMC material.

Figure 76: Diffractogram of a fresh cathode at 0% SOC. The measured intensity over the angle 2 is displayed. All peaks for the analysis are displayed in the range from 10° 2 to 75° 2 .

Structural changes due to lithium insertion and extraction

The goal of this thesis is to measure changes in the active material of the positive electrode and correlate them with the degradation of the cell. This chapter is focusing on the structural changes of the material cause by degradation. However, the crystal parameters of the layered oxides are already changing over lithium extraction [143]. While ageing, lithium is lost in the process of SEI growth. This degradation at the

10 20 30 40 50 60 70Position in 2 Cu

0.0

0.5

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2.5

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Fresh cathode at 0% SOC

(003)

graphite

(101)(006)

(102)

(104)

(105) (107) (108) (110)(113)

x 104


anode leads to a change in parameters at the cathode, by changing the lithium in the cathode in its discharged state. This change in parameters is not a degradation of the cathode material, because it is be completely reversible when refilled with lithium. To investigate the influence, three cells at different states of charge were opened and analyzed. These results are than compared with the changes seen in dependence of SOC.

Figure 77: Zoomed regions of the diffractograms from fresh cells at 0% to 100% SOC. In the left, the (003) peak is shown and on the right the (108) and (110) peaks are shown.

Ma et al. [153] shows the state of charge dependency for a 4:4:2 material for x = 1 up to x = 0.05 for Lix(Ni0.4Mn0.4Co0.2)O2. The foremost focus on the peak at 18° - 19° 2 (003) and a set of two peaks in the region from 63° - 67° 2 (108) and (110). The values in the brackets are the corresponding Miller indices of the plane that reflects the x-rays. The focus here is in the comparison of these peaks. The diffractograms of the fresh samples at 0% (x = 0.94), 68% (x = 0.60) and 100% SOC (x = 0.44) are shown in Figure 77. In the left of the figure, it is visible that with lower lithium concentration the peak shifts from 18.5° 2 to 18.2° 2 , but the intensity remains constant. This finding correlates with the ones from Ma et al.; they see for cells charged above x < 0.3 that the intensity of peak (003) drops significantly, widens, and shifts to higher angles. This is consistent with the breakdown of the crystal structure below x = 0.25 [54]. The (003) peak is representing the interlayer distance, which is the distance of the oxygen layers. This is indicated in Figure 75. With the relationship in equation (29) and (30) it can be seen, that the decrease in c-axis, the measured angle for the corresponding peak are decreasing. This is explained by Ma et al. with the increased electrostatic repulsion of the oxygen layers when lithium is extracted. The set of peaks on the right of Figure 77 also displays a change over the extraction of lithium. The peak intensity becomes lower and peaks (108) shift to lower values

Inte

nsity

in a

.u.

Inte

nsity

in a

.u.


while the (110) peaks shift higher. Also the shift of both peaks and the decrease in intensity especially for (108) is consistent with the data of Ma et al. [153] and Li et al. for 1:1:1 NMC [143]. They associate this peak separation with the shrinking of the a-lattice.

In the measured 4:4:2 cathode material, there are further changes which was not described by Ma et al. [153], but can be seen in their data. The peak triplets (101), (006), and (102) are shifting to higher angles, depicted in Figure 78. Furthermore the intensity of the (006) and (102) reflexes are decreasing with lower lithium content. The change to higher angle is hardly visible in literature data, but is also present by Li et al. [143]. Further also the vanishing of peak (006) can be seen in their data. No further changes for other peaks could be observed.

Figure 78: The peaks (101), (006), and (102) in the range of 36° - 39° 2 . The shift to higher angles is observable by extraction of lithium. Further the peak (006) completely disappeared at higher state of charge.

Overall, the unit cell volume of the EIG cell only changes by 1.7% (101.4 Å3 vs. 99.7 Å3) over the full SOC range so that stress by this decreased volume has probably just a minor influence. When analyzing the degradation, the peak shift that is caused by the lowered lithium content will be marked in the hopes to finding additional changes of the structure. For this, we applied a linear fit to peaks associated with the position changes in the lithiation range from x = 0.94 to x = 0.44. The fitted parameters are listed in the table below and visualized in Figure 79. As the figure displays, the linear fit is in accordance with the measured positions. This suggests that the interpolation appears to be valid.

36 36.5 37 37.5 38 38.5 39Position in 2 Cu

0.0

0.5

1.0

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2.5Peak (101), (006) and (102) over SOC

(101)

(006)(102)

100% SOC

68% SOC

0% SOC

x 104


Table 13: Fit function for peak position shift that is caused by a decreasing in lithium content.

Peak Fit function (003)

(108) °

(110) °

(101) °

(102) °

Figure 79: Fit and measurement values of the peak positions for the SOC influenced peaks. The position is given in 2 over the material lithiation. In the top figure, the fitting of peak (108) and (110), in the middle the fitting of peak (101) and (102) and in the bottom the fitting of peak (003) is plotted.

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1x in Lix(Ni0.4Mn0.4Co0.2)O2

18

18.2

18.4

18.6

(003)Fit (003)

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1x in Lix(Ni0.4Mn0.4Co0.2)O2

63

64

65

66

67

(108)Fit (108)(110)Fit (110)

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1x in Lix(Ni0.4Mn0.4Co0.2)O2

36

37

38

39(101)Fit (101)(102)Fit (102)


Structural changes in storage

While storage ageing, the cell is kept constant at a defined voltage at a selected temperature. As shown in 8, the dominant degradation mechanism in calendric ageing is SEI growth at the anode. It is expected, that this only has influence on the lithiation of the cathode. Nevertheless, the changes by the dissolved transition metals could also change the crystal structure of the material.

In Figure 80 the two 2 regions, which were explained before, are shown for three cells from the degradation tests at 35 °C 100% SOC. The black measurement data displays the fresh reference cell at 0% SOC. The aged cells are ordered by their capacity loss of 2%, 13%, and 21%. All cells are from the same ageing condition such that ageing effects should increase with a higher capacity loss. The (003) peak, that can be seen on the left of the figure, only shows an unexpected change for the cell with 87% remaining capacity. The peak is at higher angles as calculated for the capacity loss of the cell. For this effect, these are two possible causes. First a height misplacement of the sample and second an inhomogeneous lithium distribution in the cell. An inhomogeneous distribution of lithium is unlikely, because the gradient in the open circuit voltage curve is high, so that an uneven lithium distribution in the cathode would be balanced out by itself. Since all peaks of the material in the range of 10° - 75° 2 show a slight shift depending on the angle, the height displacement is the most likely cause.

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The (101) and the (102) peaks both show a higher deviation from the calculated peak positions. Both peaks are at lower angles than expected, but the (006) peak shows the typical shift towards lower angles; a sample height error can be excluded. No explanation in literature matches with the measured change in the peaks. This might be a sign for a change in crystal structure. The change appeared at a remaining capacity of 54%, which is in a range, where the cell is typically not used any more due to power fade and safety concerns. This was also seen in the third cell of the triplet, which suffered severe swelling. Perhaps these changes in cathode material are far from realistic changes in automotive applications.

Summary of structural changes

A conclusion for the results is that the state of charge can be monitored very well by the linear-like peak shift with degree of lithiation. For a full characterization over the complete SOC range more cells would be needed, increasing the measurement points and with this workload drastically. This issue could be solved by using the x-ray diffraction method. For this, thinner cells and housings are necessary, that do not influence the diffractogram.

Beside a local SOC measurement, the general material characterization and quality of the material can be analyzed. For a degradation analysis, the changes in the structure seem to be in the range of accuracy of the measurement. This result is in accordance to literature [77, 142, 143, 155]. To see an influence of structural changes, the impact on remaining capacity must be greater than the dominantly observed lithium loss and SEI formation at the anode.


Electrolyte decomposition on the cathode 129

Electrolyte decomposition on the cathode

Beside the already described SEI formation on the anode, there is also a decomposition reaction at the cathode which forms a protective layer. The properties of the film are due to the same reactions: the film is electrically insulating and has a high ionic conductivity. The term SEI could also be used, but as it is often associated with the anodic surface layer, in literature terms like “surface layer”, “protective film” or “cathode electrolyte interphase” are found. It will be referred from now on as “cathode electrolyte interphase” (CEI).

There are two reasons why the CEI is much harder to detect and analyze than the SEI. Firstly, all transition metal oxide cathode materials as NMC have a natural surface layer that consists mainly of Li2CO3 [156, 157]. This arises from the reactions with the CO2 in the atmosphere or precursors in the synthesis of the material [156]. Within the first contact with electrolyte, this native film is usually eroded by the acidic electrolyte salts and the active materials are usually involved in the subsequent oxidation of the electrolyte solvents on the exposed cathode surface. The second reason for the detection is the thickness of this very thin film of only a 1-3 nm [158].

The first proposal of a surface film on the cathode was done in 1985 by J. B. Goodenough et al. [159]. They saw differences in EIS spectra of cathodes that showed that not only a diffusion process was ongoing and proposed the oxidation of electrolyte on the surface as a second process. This was proven by Tarascon and Guyomard with experiments on the irreversible loss on cathode materials with different surfaces [16, 160]. The materials with higher surface area showed a higher irreversible loss, which was traced back to an even surface film of electrolyte decomposition products.

Aurbach et al. [161] proposes that hydrolysis products from the conductive salt as HF react with the native film and led to its breakdown. Such an involvement would explain the findings of LiF in the surface layer after contact with electrolyte [131]. LiF is known as an electric insulator, which would confirm the proposal of the same working principle as the SEI on the anode. In view of the highly oxidative nature of metal oxides, these authors suggested a spontaneous formation process for the new surface layer, in which the direct (hence, non-electrochemical) redox reactions occur between the active materials of cathode and electrolyte components, leading to the lithiation of the former and the oxidation of the latter [55]. A two-step process is proposed there. First, a primitive and resistive film containing LiF is formed (below 3.4 V). Next, between 3.4 V and 3.8 V, a highly conductive film is built up through a further oxidative breakdown of the primitive layer.


The resistive layer and also the further oxidation are consuming electrolyte components and lithium, which leads to a higher internal resistance and also capacity fade.

Gravimetric analysis of the CEI

The easiest approach to measure a deposition of material on the cathode electrolyte interphase, with respect to the available analytic methods for this thesis, is the evaluation of the weight change in the cathodes over ageing. The weights are taken within the post mortem procedure as explained in 3.2.1. Beside the deposited material, the lithium concentration in the electrodes changes the weight of the electrodes. The average discharge capacity of the cell is about 20.29 Ah, which can be translated to the weight change of the electrodes by 5.24 g with equation (31), where QDch is the discharged capacity, NA the Avogadro constant, e the elementary charge and MLi the molar mass of lithium.

(31)

Although the cathode weights can be corrected by the missing lithium content, which ended up in the SEI of the anode. The exact lithium loss of the cathode is measured in the ICP-AES. The deviation from the expected change by different lithium concentration is analyzed. For the fresh cells the weights in three different states of charge is displayed in Figure 82. Additionally the calculated weight change can be seen in the graph, which is matching with the measured values.

Figure 82: Corrected cathode weights over the SOC. The calculated weight change by a lower lithium concentration in dependence of the SOC in the cathode is shown as gray line.

To study the weight change in dependence from ageing, the deviation from the cathode weight, which is corrected by the lithium concentration, is used. The deviation for the storage ageing cells is shown in Figure 83.

0 10 20 30 40 50 60 70 80 90 100Cell SOC in %

185

190

195Catode weight


Figure 83: Cathode weight changes over ageing at the three test temperatures. The graphs show the deviation of the measured cathode weight from the expected cathode weight. Positive values are an indication for more remains on the cathode. The uncertainty is caused by the inaccuracy of the lab scale and the lithium concentration measurements.

Figure 83 shows weight changes for the cathodes of the calendric aged cells at the three test temperatures. The cell at 45 °C tests shows an increase of weight over the life time. This can also be observed for cells that were stored at 80% and 20% SOC. The 35 °C 10% SOC and 25 °C cell show a decrease in cathode weight. For 25 °C, this weight loss is very low and in the range of accuracy.

The 80% SOC cells at 35 °C show about 1.3 g of increase, which is about 0.9% of the whole electrode and 1.2% of the pure active material. At higher temperatures, at 45 °C the increase is even more, which indicates the temperature dependency. At 100% SOC and 35°C the results are completely different. Here, all three opened cell show a loss in weight, compared to the reference. This cannot be explained by the conventional theories. It is expected that at a higher voltage, the decomposition rate at the cathode would be higher and with this also a higher amount of products would remain on the cathode surface. Xiong et al. [50] showed that cathodes that are stored in conventional electrolytes tend to evolve gas when stored at higher voltages. One possible explanation for the lower weights of the cells at higher SOC could be that the higher gas evolution led to fewer remaining decomposition products at the cathode. By the fact that this cannot be proven, the lower weights of the 100% SOC cells cannot be sufficiently explained.

0 500 1000Storage Time in days

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Weight Changes at 35 °C

100% SOC80% SOC20% SOC


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Thermo-gravimetric analysis of the CEI

Another method to measure the CEI is using the mass loss while heating the sample and correlating this with the surface layer that had formed. The species that were proposed to be part of the native or first formed film are LiF or Li2CO3. They have melting points of 845 °C (LiF) and 720 °C (Li2CO3) [162], which are far above the decomposition temperature of the used NMC material above 220 °C. This will lead to the conclusion that only organic products and the binder will determine the weight loss up to 220 °C. A change in mass loss could so be correlated with the formation of a surface film.

The samples are measured with thermo-gravimetric analysis (TGA), which is a technique that measures weight changes while the temperature of a sample is increasing. Typical profiles are increasing temperatures until an upper maximum is reached. While the sample is heated, it is typically circulated with a protective gas, so that the sample is in a defined and non-reactive atmosphere. Due to chemical reactions that are induced by the increased temperature, mass changes can appear which are measured precisely. The influence by the sample container is eliminated with measuring a reference container as a blank measurement.

The underlying measurements are done with 4 mm diameter cathode samples that did not undergo any pretreatment. The samples are sealed in an aluminum container under argon atmosphere. The analysis is done in a Mettler-Toledo TGA/DSC 1 (STAR System), where the aluminum container is tapped with a needle to have contact with the reactive gas, which was nitrogen for all measurements. The samples were heated from 25 °C up to 400 °C with a heating rate of 10 K min-1. The weight of the samples was in the range of 5.5 mg which is high, compared to the measurement accuracy of 0.1 μg.

In Figure 84 the percentage of weight change for five samples from a fresh cell are shown. All samples show the same weight loss until 200 - 250 °C. This shows the good reproducibility of the method and of the samples. Until that temperature only the binder and organic components are burned and with this add up to the weight loss. If there is a surface film formed with the proposed species of LiF or Li2CO3, which have a high melting point, the relative material loss should be less compared to a fresh cell.


Figure 84: Relative weight curves over the temperature from five samples of a fresh cell. The temperature is measured below the sample container. The later weight reduction of the blue and green curve is probably caused by insufficient contact of the samples from the container bottom so that the sample temperature is less than measured.

As we saw in 10.1, the remaining lithium content in the cathode has an influence of the cell weight. If the cathode sample is lighter by the lower lithium concentration, the same total loss of binder and organic components would lead to a higher relative weight loss. As a consequence of this, the remaining lithium content needs to be corrected with the same function as explained before. This results in a change from 4 % weight loss at 100% SOC to 3.2% at 0% SOC.

For comparison of the aged cells, the weight change at 220 °C is measured and corrected by the remaining lithium content as it can be seen in equation (32). There

stands for the percentage change at 0% SOC and at 100% SOC, is the change in lithium concentration from 0-100% SOC in μmol cm-2,

the lithium loss of the sample in μmol cm-2 and the percentage of weight loss of the sample. A higher value represents an increased amount of surface film that is not lost until 220 °C.

(32)

0 50 100 150 200 250 300 350 400 450Temperature in °C

94

95

96

97

98

99

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Figure 85: Changes in the weight loss up to 220 °C, measured by thermo-gravimetric analysis. From left to right, the three test temperatures for storage are shown separately. For each cells, five samples from the middle of the electrodes are measured.

The weight change of the samples is displayed for the calendric cells over the ageing time as it was done for the full electrode weights itself; the outcomes are plotted in Figure 85. The results of nearly all measured cells show increasing values, which indicates, that the cathodes of this cells contain products that are not burned or evaporated until 220 °C. The measured cell that was stored at 25 °C and 80% SOC shows nearly no change in the weight loss, which means that the amount of surface products is low. This is in accordance to the weight change of the cathode measured within the cell opening. There a slight decrease was observed. Combining both methods, no substantial difference can be observed.

For the samples of 35 °C and 20% SOC, no difference could be observed, which is in contrast to the measurements of the cathode weights. A change of 0.6 g was measured after 700 days, which corresponds to a change of weight of less than 0.5%. The increased weight for the complete electrode weights could be caused by organic components at the surface or products that react until 220 °C, which would exclude the proposed products LiF or Li2CO3 for this cell. With respect to accuracy and the change that is measured for the sample at 80% SOC, we also cannot see a clear increase in surface species. This was seen again for the full electrode weights. However, the 100% SOC cells show an increase of surface products over time in the TGA measurements. These cells had no increase in full electrode weights after the opening, which is in contrast to these results. For increased temperature of 35 °C and the high SOC of 100%, it is stated that decomposition is appearing in NMC cathodes [163]. A possible explanation for the absence of increased weight in the

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gravimetric analysis is that the cells that were stored at 100% SOC showed adhesion problems at some edges, so that parts of the active material were lost in the opening procedure. This is an indication for binder decomposition at the higher temperatures and is in accordance with results from literature [164]. The somewhat linear increase of surface products is an indication for a slow permanent decomposition of the electrolyte at the cathode side.

The results from 45 °C and 80% SOC, displayed on the right of Figure 85, show that a process of decomposition is clearly temperature dependent. The much higher amount of decomposition products at the cathode surface compared to the same state of charge at the lower temperatures. By limitations of the equipment it was not possible to measure the composition of the surface products. For this analysis, XPS measurements would be a good addition to see the chemical composition at the cathode particle surface. A combined system of TGA and mass spectroscopy could also help to understand the composition of the CEI.

Aurbach et al. [156, 157] and Matsuo et al. [131] proposed decomposition products on the surface of the material are insulators, so that they increase the internal resistance leading to a drastic capacity loss at a given current density. The relative resistance curves of the cells under investigation are shown in Figure 86. The curves show a similar behavior as the measured surface film increase with the exception of the last measured values of 35 °C / 100% SOC and 45 °C / 80% SOC. Both cells had, as explained in section 3 and 6, a rapid break down which was caused by lithium plating. The plated lithium formed a surface layer that was responsible for the later resistance increase. The increase of resistance until about day 500 is nearly linear and correlates with the surface film formation of the cathode. Thus there is a likelihood that the cathode plays an important role in the internal cell resistance increase, which was also stated by Kim et al. [120]. The potential increase can be caused by the formed surface layer or by the re-deposition of dissolved species which are described in 8.2.


Figure 86: Resistance curves of the calendric aged cells which are shown in the thermo-gravimetric analysis.

To prove that the measured resistance increase in the cell originates from the cathode, half-cells were built from both electrodes. It was mentioned in 3.2.4 that the anode shows a stability issue and no sufficient data could be measured. The remaining capacity of the cathode was measured in the half cell, but the high internal resistance of the cells, caused by the thick separator, small area and bad connections shed a high variation. It was not possible to use the data for a resistance evaluation of the aged cells.

Summarizing the effects of the electrolyte decomposition at the cathode, it can be said that this effect is also present if the maximum cell voltage is limited to lower than standard values as it was done in this ageing matrix (4.15 V limit by the producer compared to a standard value of 4.2 V for NMC). The effects of the decomposition can most probably be seen in the resistance curves of the cell compared to the cell capacity. If the cell voltage is increased, which is one strategy to increase the energy density of lithium-ion batteries, this effect will play a more important role in the degradation.

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Current collector corrosion 137

Current collector corrosion

In lithium-ion batteries, the positive active material is coated on the aluminum current collector. This is because copper, with a higher electric conductivity, is not stable in the organic solvent at the high potentials. The thermodynamic stability of aluminum is limited with an oxidation potential of 1.39 V (against SHE), which causes the corrosion of aluminum in the potential range that is used in lithium-ion cathodes. Luckily, aluminum forms a native protective film on its surface so that the anodic stability increases up to 5.0 V, even in organic solvents with conductive salts [165]. The native protection layer is composed of Al2O3 or oxyhydroxide and hydroxide [166] and has a typical thickness of around 50 nm [167]. This native film gets mechanically damaged, for example in the electrode production or within the cell assembly process. The recovery of this film is strongly dependent on the electrolyte that is used in the cell, more specific on the conductive salt and less on the solvents [55]. In nearly all commercial cells, LiPF6 is found to build a stable film on aluminum when damaged, even at potentials over 4.2 V [55], a possible voltage for the new NMC materials. This should lead to a stable film on the cathode current collector in the used cell where the used salt is LiPF6 and the upper cutoff voltage is 4.15 V. The influence of different salts on the corrosion rate is not fully understood up to now [168].

Even with LiPF6 as salt, corrosion was reported for lithium-ion batteries [169-171], where they saw local corrosion pits, whereas Braithwaite et al. saw mounds instead [172].The corrosion is described as a two-step adsorption / oxidation / desorption process [165, 173]. The desorption of the oxidized products leaves the pits on the smooth alumina surface. Less soluble oxidation species, such as AlF3 or Al2(CO3)3, are formed when the conductive salt LiPF6 is used [165]. The nature of the passive film is dictated by its composition, which is strongly affected by the salt anion oxidation and less by the test parameters in use.

The aluminum corrosion may be the cause of contact loss of the active material, which would lead to capacity loss and resistance increase. Furthermore, oxidation products like AlF3 are highly insulating, so that the internal resistance of the cathode would rise. Another effect could be the influence of dissolved aluminum on the anode, as it is described in section 8 for the transition metals, but this was never reported in literature.

Dissolved aluminum

The corrosion of the aluminum current collector of the cathode can be measured similarly to the dissolution, described in section 8. The concentration of Al is measured at the anode over time, like Zheng et al. did [44]. For this, new and aged


cells are measured with the ICP-AES and the areal concentration of aluminum is shown in Figure 87. As can be seen, the new cell has a low concentration of aluminum at the anode, which is in the range of the measurement accuracy. Compared to the fresh cell, the aged cells have all except one a higher concentration of Al. The most aged cell at 45 °C and 80% SOC has a 10 times higher concentration of Al.

Figure 87: Aluminum content at the anode, which makes a quantification of the corrosion and dissolution possible. The plot shows the dissolution at three temperatures and different SOCs for the calendric aged cells over the ageing time.

Comparing the Al concentration of all cells at 80% SOC at different ageing states and temperatures, the concentration is comparable, which allows for the assumption that the influence of the temperature can be neglected. The 700 days aged 80% cell at 45 °C has a much higher value that correlates with the rapid capacity loss which could be seen in Figure 23. But it is not possible to prove if the aluminum corrosion and deposition is the reason for capacity loss or a result of this.

Analyzing, the cells that were opened nearly at the same point in time, after 700 days, from tests at 35 °C, we can see the influence of the SOC the cells are stored. The cells were stored at 20%, 80% and 100% SOC, but do not arrange accordingly. The cells at 80% SOC have the lowest Al concentration, which is against the expectation, that a higher SOC favors the corrosion at the cathode current collector. The anode has the same potential at 80% and 100% SOC, which leads only to the influence of the cathode voltage.


Optical analysis

For a further comparison, the corrosion was analyzed via an optical method. Laser microscope pictures of the current collector after active material removal were compared. Here it is expected to see pit corrosion on the current collector, as Braithwaite et al. described [172]. An example for a fresh and an aged cell can be seen in Figure 88, whereas the fresh cell is shown on the left (a) and the aged cell on the right (b). The pictures give the impression that there is no significant difference. Both show dark circular marks on them. The circular marks are probably both corrosion pits and imprints in the aluminum from the active material particles. These can be distinguished be depth. Within the production process, the electrode is exposed to a calender, whereby the electrode is compressed and the target density is achieved. In the pictures, the actual corrosion pits are marked in both pictures with red circles. The number of corrosion pits in the aged electrode is higher than in the fresh one. To have a quantitative measure, the volumes of the pits were compared, by measuring the average depth of the pits and the occurrence in a standard area. Figure 89 shows an exemplary measurement of a pit depth. The measurement area is for the cells were 0.25 mm2 (4 samples with 290 μm x 220 μm).

Figure 88: Laser microscope pictures of the current collector of a fresh cell on the left and an aged cell on the right. The linear lines that can be spotted are scratch marks from the removal of the active material. On the left and right several circular marks can be seen. They are probably corrosion pits and marks from active material particles.

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In Figure 90 the results from the optical method are shown. The absolute values are in good accordance with the results measured by ICP-AES. For the fresh cell, with the optical method the dissolved aluminum content is about 40% higher. The aged cells also show an increased content of aluminum by higher number of corrosion pits at the cathode. The absolute values (especially at 35 °C) cannot be compared, so the influence of a storage condition cannot be analyzed.

Comparison of method

In general, the optical method proves the findings measured by ICP-AES, but the much smaller measurement area leads to a higher uncertainty. The measured area is for the optical method 0.25 mm² and for the ICP-AES measurements the averaged value of 81 cm² of directly facing anode area. The relation of measured area shows the problem with the optical method. To measure a large area, the measurement time has to be increased to impractical values. Furthermore, there are two more drawbacks of this method. First, the active material of the cathode needs to be completely removed, which is also an extensive work. Second, the imprints of active material particles could falsify the results. For a distinct identification of the pits, each one has to be validated by the depth profile, which increases the work additionally.

Influence on cell degradation

The current collector corrodes in the analyzed EIG ePLB C020 cell, but the effect is very small, due to the conductive salt that acts as a protection of aluminum. Overall, the ageing characteristic of the cell seems not to be influenced by this effect too much, so that it can be neglected for this cell. This becomes clearer when the total dissolved amount of aluminum is compared to the dissolved amount of the transition metals. Manganese shows a roughly ten times higher dissolution rate than aluminum here. This result correlates with literature, where the aluminum corrosion is not seen as one of the important ageing effects in lithium-ion batteries [27]. The dissolution could become more prominent in the future if LiPF6 free electrolytes are used.


Conclusion and outlook 143

Conclusion and outlook

The focus of this thesis was the investigation of degradation mechanisms in commercial 4:4:2 NMC-based lithium-ion batteries. The selected EIG cell is with all parameters, energy density, lifetime, size, and material, a state of the art battery that represents current automotive cells. Typical degradation studies of commercial cells focus on small cells. This is done to lower the testing effort and costs [91, 94]. With its 174 Wh kg-1 the energy density is higher than the cells of today’s electric vehicles (the energy density of the cell in the Nissan Leaf is 157 Wh kg-1 [174]). Besides the unique size of the cell, the number of test conditions performed was outstanding. 160 cells were tested in 50 conditions. This helped to gain and improve understanding of the degradation in depth as well as aiding to identify the limitations of the cell. The influences of temperature, state of charge, depth of discharge, current rate of charge, and discharge directions were tested. The detailed analysis of the capacity and resistance development over storage and cycle life helped to understand the ongoing processes, for this cell. This can be derived for other cells with a similar composition.

Beside the expected degradation, unexpected improvements of the internal parameters were observed. Increasing capacities at the begin of ageing tests or after longer storage periods had been seen by other researchers before [93, 101, 103], but a responsible effect could not be explained. In this year, Lewerenz et al [95] showed a theory for this; introducing the passive electrode effect. In this thesis, for the first time, measurements of the lithium contents in the passive parts were done which prove a theory and show the influence of the cell geometry on the degradation behavior. With this, the often misinterpreted ageing curves can now be divided into reversible and irreversible ageing. Eliminating the influence of geometry, the actual ongoing irreversible degradation processes can be seen. For example, a rather linear degradation compared to the often claimed square root of time function [79, 94]. The lifetime experiments in the material development often show linear degradation of the electrodes over time or cycles, which can now be seen in full cells too. The segmentation of degradation curves helps to study, understand and improve the lifetime of cells.

The often reported “knee” in the degradation curve can now be explained, and it is possible to show the reason of the rapid breakdown as well. Areal lithium plating is the main reason for the drastic changes in the battery. The breakdown of the capacity and also the rapid resistance increase appeared at high remaining capacities in comparison to the often shown results from literature. The origin for the first plating could not be identified, but this was not in focus of this thesis. The general process of a self-accelerating degradation was explained and documented with post mortem results.


The post mortem analysis was used to focus on the impact of the cathode degradation on the full cell capacity loss and resistance increase. The in literatures, as most relevant defined, cathode degradation effects were analyzed systematically with their portion on the cell degradation. The results show, that structural defects or disorders by cycling or storage have only a minor influence on the degradation. All observed changes in the cathode crystal structure were caused by the loss of lithium to the anode. A discussed effect for NMC cathodes is also the dissolution of transition metals. It was found that this effect might have a higher impact of the capacity loss than often expected. A drastic difference in the SEI growth between stored cells at nearly the same anode voltage was observed. The marginal portion of transition metals at the anode seems to have a high impact on the loss of lithium in an anode surface layer, especially at higher states of charge and temperature. This effect will become more dominant if the current trend to increase cathode voltages is continued. This would also intensify the last important degradation mechanism at the cathode; the CEI formation. The electrolyte is decomposed at higher voltages at the cathode surface and forms a highly resistive layer. The effect, together with the SEI growth is most probably responsible for the increase of cell resistance.

It is important to understand these effects and also their influence on the full cell degradation. New materials for the cathode, like nickel rich NMCs, cheap impure materials, or high voltage cathodes will intensify them. For the material development the identification of important and unimportant degradation mechanisms for full cell degradation demonstrates the path for new developments. For the application specialists, it helps to avoid operation conditions that favor ageing. This could be for example, avoiding direct charging of the car after every trip or high cell voltage at selected temperatures.

As seen, the separation of the three degradation phases helps to assign the cell ageing to separate effects in the cell. With this approach, the development of new batteries based on design, material or balancing can be done faster. Furthermore, the misinterpretation of unexpected cell behavior is avoided.

For future work, the comparison of the same material on half-cell level in the material development and in full cells would proof the here presented concept. Further the integration of the physical effects in lifetime models would help to improve the understanding and the prediction of batteries. For a higher resolution in measurement values, more samples over lifetime should be measured. This would result in more cells per ageing condition, which often stresses the amount of available equipment. For storage ageing tests, this could be overcome by the from Lewerenz et al. presented floated storage [95]. For the analysis of structural changes, in-situ methods should be developed, to have a closer look on the influence of state of charge.

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Appendix 157

Appendix

Own Publications

In the frame of this thesis different publications were generated, which are enlisted below. Contents of these publications is, in accordance to the “Promotionsordnung der Fakultät für Elektrotechnik und Informationstechnik der RWTH Aachen” and in agreement with the supervising professor Dirk Uwe Sauer, used in this work. This is marked by a reference to the publication.

Scientific Journals

- M. Ecker, T. K. D. Tran, P. Dechent, S. Kabitz, A. Warnecke, and D. U. Sauer, “Parameterization of a Physico-Chemical Model of a Lithium-Ion Battery I. Determination of Parameters,” Journal of the Electrochemical Society, vol. 162, no. 9, pp. A1836-A1848, 2015. [75]

- M. Lewerenz, S. Käbitz, M. Knips, J. Münnix, J. Schmalstieg, A. Warnecke, and D. U. Sauer, “New method evaluating currents keeping the voltage constant for fast and highly resolved measurement of Arrhenius relation and capacity fade,” Journal of Power Sources, vol. 353, pp. 144-151, 2017. [90]

- M. Ecker, N. Nieto, S. Käbitz, J. Schmalstieg, H. Blanke, A. Warnecke, and D. U. Sauer, “Calendar and cycle life study of Li(NiMnCo)O2-based 18650 lithium-ion batteries,” Journal of Power Sources, vol. 248, pp. 839-851, 2014. [91]

- M. Lewerenz, A. Warnecke, and D. U. Sauer, “Introduction of capacity difference analysis (CDA) for analyzing lateral lithium-ion flow to determine the state of covering layer evolution,” Journal of Power Sources, vol. in Review, 2017. [108]

- P. Shafiei Sabet, A. Warnecke, H. Witzenhause, and D. U. Sauer, “Investigation of the Ageing of Lithium Ion Batteries via Electrochemical Impedance Spectroscopy and Complementary Methods,” Journal of Power Sources, vol. in Revision, 2017. [110]

Conference Publications

- A. Warnecke, D.U. Sauer, “Thermal Behavior of NMC Cathodes”, 227th ECS, Chicago, Illinois, USA, 2015.


- A. Warnecke, R. Graff, D.U. Sauer, “Dissolution of Transition Metals in Lithium-Ion Batteries with NMC-Based Electrodes”, PRiME 2016, Honolulu, Hawaii, USA, 2016.

Supervised Thesis

In the framework of this thesis, one student master thesis was generated. For this master thesis, the definition of the topic and the scientific supervision was done by me. The content of this thesis is a side aspect of my thesis and can be found in 4.6. Corresponding contents is not explicitly referenced.

“Post-Mortem-Analyse von Prototyp Lithium-Ionen-Batterien für Elektrofahrzeuge” by Mark-Philipp Maul

My thesis was supported by the following enlisted student researchers that worked und my scientific supervision.

- Anna Friedrich

- Rezan Demir

- Darya Chahardahcherik

- Martin Graff

- Niklas Kürten


ABISEA Band 1 Eßer, A.Berührungslose, kombinierte Energie- und Informations-übertragung für bewegliche Systeme 1. Auflage 1992, 130 Seiten ISBN 3-86073-046-0

ABISEA Band 2 Vogel, U.Entwurf und Beurteilung von Verfahren zur Hochausnutzung des Rad-Schiene-Kraftschlusses durch Triebfahrzeuge 1. Auflage 1992, 130 Seiten ISBN 3-86073-060-6

ABISEA Band 3 Redehorn, Th.Stromeinprägendes Antriebssystem mit fremderregter Synchron-maschine 1. Auflage 1992, 130 Seiten ISBN 3-86073-061-4

ABISEA Band 4 Ackva, A.Spannungseinprägendes Antriebssystem mit Synchron-maschine und direkter Stromregelung1. Auflage 1992, 135 Seiten ISBN 3-86073-062-2

ABISEA Band 5 Mertens, A.Analyse des Oberschwingungsverhaltens von taktsynchronen Delta -Modulationsverfahren zur Steuerung von Pulsstromrichtern bei hoher Taktzahl 1. Auflage 1992, 170 Seiten ISBN 3-86073-069-X

ABISEA Band 6 Geuer, W. Untersuchungen über das Alterungsverhalten von Bleiakkumulatoren 1. Auflage 1993, 100 Seiten ISBN 3-86073-097-5

ABISEA Band 7 Langheim, J.Einzelradantrieb für Elektrostraßenfahrzeuge 1. Auflage 1993, 215 Seiten ISBN 3-86073-123-8 (vergriffen)

ABISEA Band 8 Fetz, J. Fehlertolerante Regelung eines Asynchron-Doppelantriebes für ein Elektrospeicherfahrzeug 1. Auflage 1993, 136 Seiten ISBN 3-86073-124-6 (vergriffen)

ABISEA Band 9 Schülting, L.Optimierte Auslegung induktiver Bauelemente für den Mittelfrequenzbereich 1. Auflage 1993, 136 Seiten ISBN 3-86073-174-2 (vergriffen)

ABISEA Band 10 Skudelny, H.-Ch.Stromrichtertechnik 4. Auflage 1997, 259 Seiten ISBN 3-86073-189-0

ABISEA Band 11 Skudelny, Ch. Elektrische Antriebe 3. Auflage 1997, 124 Seiten ISBN 3-86073-231-5

ABISEA Band 12 Schöpe, F.Batterie-Management für Nickel-Cadmium Akkumulatoren 1. Auflage 1994, 156 Seiten ISBN 3-86073-232-3 (vergriffen)

ABISEA Band 13 v. d. Weem, J.Schmalbandige aktive Filter für Schienentriebfahrzeuge am Gleichspannungs-fahrdraht 1. Auflage 1995, 125 Seiten ISBN 3-86073-233-1

ABISEA Band 14 Backhaus, K.Spannungseinprägendes Direktantriebssystem mit schnelllaufender geschalteter Reluktanzmaschine 1. Auflage 1995, 156 Seiten ISBN 3-86073-234-X (vergriffen)

ABISEA Band 15 Reinold, H.Optimierung dreiphasiger Pulsdauermodulations- verfahren 1. Auflage 1996, 116 Seiten ISBN 3-86073-235-8

ABISEA Band 16 Köpken, H.-G.Regelverfahren für Parallelschwingkreis- umrichter 1. Auflage 1996, 125 Seiten ISBN 3-86073-236-6

ABISEA Band 17 Mauracher, P. Modellbildung und Verbundoptimierung bei Elektrostraßenfahrzeugen 1. Auflage 1996, 192 Seiten ISBN 3-86073-237-4

ABISEA Band 18 Protiwa, F.-F. Vergleich dreiphasiger Resonanz-Wechselrichter in Simulation und Messung 1. Auflage 1997, 178 Seiten ISBN 3-86073-238-2

ABISEA Band 19 Brockmeyer, A.Dimensionierungswerkzeug für magnetische Bau- elemente in Stromrichter-anwendungen 1. Auflage 1997, 182 Seiten ISBN 3-86073-239-0

ABISEA Band 20 Apeldoorn, 0.Simulationsgestützte Bewer-tung von Steuerverfahren für netzgeführte Stromrichter mit verringerter Netzrück-wirkung 1. Auflage 1997, 132 Seiten ISBN 3-86073-680-9


ABISEA Band 21 Lohner, A.Batteriemanagement für verschlossene Blei-Batterien am Beispiel von Unter-brechungsfreien Stromversorgungen 1. Auflage 1998, 144 Seiten ISBN 3-86073-681-7

ABISEA Band 22 Reinert, J. Optimierung der Betriebs-eigenschaften von Antrieben mit geschalteter Reluktanz-maschine 1. Auflage 1998, 168 Seiten ISBN 3-86073-682-5

ABISEA Band 23 Nagel, A.Leitungsgebundene Störungen in der Leistungselektronik: Entstehung, Ausbreitung und Filterung 1. Auflage 1999, 160 Seiten ISBN 3-86073-683-3

ABISEA Band 24 Menne, M.Drehschwingungen im An-triebsstrang von Elektro-straßenfahrzeugen - Analyse und aktive Dämpfung 1. Auflage 2001, 192 Seiten ISBN 3-86073-684-1

ABISEA Band 25 von Bloh, J. Multilevel-Umrichter zum Einsatz in Mittelspannungs-Gleichspannungs-Übertragungen 1. Auflage 2001, 152 Seiten ISBN 3-86073-685-X

ABISEA Band 26 Karden, E. Using low-frequency impedance spectroscopy for characterization, monitoring, and modeling of industrial batteries1. Auflage 2002, 154 Seiten ISBN 3-8265-9766-4

ABISEA Band 27 Karipidis, C.-U. A Versatile DSP/ FPGA Structure optimized for Rapid Prototyping and Digital Real-Time Simulation of Power Electronic and Electrical Drive Systems 1. Auflage 2001, 164 Seiten ISBN 3-8265-9738-9

ABISEA Band 28 Kahlen, K. Regelungsstrategien für per-manentmagnetische Direkt-antriebe mit mehreren Freiheitsgraden 1. Auflage 2003, 158 Seiten ISBN 3-8322-1222-1

ABISEA Band 29 Inderka, R. Direkte Drehmoment-regelung Geschalteter Reluktanzantriebe 1. Auflage 2003, 190 Seiten ISBN 3-8322-1175-6

ABISEA Band 30 Schröder, S.Circuit-Simulation Models of High-Power Devices Based on Semiconductor Physics 1. Auflage 2003, 124 Seiten ISBN 3-8322-1250-7

ABISEA Band 31 Buller, S. Impedance-Based Simu-lation Models for Energy Storage Devices in Advanced Automotive Power Systems 1. Auflage 2003, 136 Seiten ISBN 3-8322-1225-6

ABISEA Band 32 Schönknecht, A. Topologien und Regelungs-strategien für das induktive Erwärmen mit hohen Frequenz-Leistungs- produkten 1. Auflage 2004, 1 70 Seiten ISBN 3-8322-2408-4

ABISEA Band 33 Tolle, T. Konvertertopologien für ein aufwandsarmes, zwei-stufiges Schaltnetzteil zum Laden von Batterien aus dem Netz 1. Auflage 2004, 150 Seiten ISBN 3-8322-2676-1

ABISEA Band 34 Götting, G.Dynamische Antriebs-regelung von Elektro-straßenfahrzeugen unter Berücksichtigung eines schwingungsfähigen Antriebsstrangs 1. Auflage 2004, 166 Seiten ISBN 3-8322-2804-7

ABISEA Band 35 Dieckerhoff, S.Transformatorlose Strom-richterschaltungen für Bahn- fahrzeuge am 16 2/3Hz Netz 1. Auflage 2004, 158 Seiten ISBN 3-8322-3094-7

ABISEA Band 36 Hu, J.Bewertung von DC-DC- Topologien und Optimierung eines DC-DC-Leistungs-moduls für das 42-V-Kfz-Bordnetz1. Auflage 2004, 156 Seiten ISBN 3-8322-3201-X

ABISEA Band 37 Detjen, D.-0. Characterization and Modeling of Si-Si Bonded Hydrophobie Interfaces for Novel High-Power BIMOS Devices 1. Auflage 2004, 146 Seiten ISBN 3-8322-2963-9

ABISEA Band 38 Walter, J.Simulationsbasierte Zuver-lässigkeitsanalyse in der modernen Leistungs-elektronik 1. Auflage 2004, 134 Seiten ISBN 3-8322-3481-0


ABISEA Band 39 Schwarzer, U. IGBT versus GCT in der Mittelspannungsanwendung - ein experimenteller und simulativer Vergleich 1. Auflage 2005, 184 Seiten ISBN 3-8322-4489-1

ABISEA Band 40 Bartram, M. IGBT-Umrichtersysteme für Windkraftanlagen: Analyse der Zyklenbelastung, Mo-dellbildung, Optimierung und Lebensdauervorhersage 1. Auflage 2006, 195 Seiten ISBN 3-8322-5039-5

ABISEA Band 41 Ponnaluri, S.Generalized Design, Analysis and Control of Grid side converters with integrated UPS or Islanding functionality 1. Auflage 2006, 163 Seiten ISBN 3-8322-5281-9

ABISEA Band 42 Jacobs, J. Multi-Phase Series Resonant DC-to-DC Converters 1. Auflage 2006, 185 Seiten ISBN 3-8322-5532-X

ABISEA Band 43 Linzen, D. Impedance-Based Loss Calculation and Thermal Modeling of Electrochemical Energy Storage Devices for Design Considerations of Automotive Power Systems 1. Auflage 2006, 150 Seiten ISBN 3-8322-5706-3

ABISEA Band 44 Fiedler, J.Design of Low-Noise Switched Reluctance Drives 1. Auflage 2007, 183 Seiten ISBN 978-3-8322-5864-l

ABISEA Band 45 FuengwarodsakuI, N.Predictive PWM-based Direct Instantaneous Torque Control for Switched Reluctance Machines 1. Auflage 2007, 150 Seiten ISBN 978-3-8322-6210-5

ABISEA Band 46 Meyer, C. Key Components for Future Offshore DC Grids 1. Auflage 2007, 196 Seiten ISBN 978-3-8322-6571-7

ABISEA Band 47 Fujii, K. Characterization and Optimization of Soft-Switched Multi-Level Converters for STATCOMs 1. Auflage 2008, 206 Seiten ISBN 978-3-8322-6981-4

ABISEA Band 48 Carstensen, C. Eddy Currents in Windings of Switched Reluctance Machines 1. Auflage 2008, 190 Seiten ISBN 978-3-8322-7118-3

ABISEA Band 49 Bohlen, 0.Impedance-based battery monitoring 1. Auflage 2008, 200 Seiten ISBN 978-3-8322-7606-5

ABISEA Band 50 Thele, M.A contribution to the modelling of the charge acceptance of lead-acid batteries - using frequency and time domain based concepts 1. Auflage 2008, 168 Seiten ISBN 978-3-8322-7659-1

ABISEA Band 51 König, A.High Temperature DC-to-DC Converters for Downhole Applications 1. Auflage 2009, 160 Seiten ISBN 978-3-8322-8489-3

ABISEA Band 52 Dick, C. P.Multi-Resonant Converters as Photovoltaic Module-Integrated Maximum Power Point Tracker 1. Auflage 2010, 192 Seiten ISBN 978-3-8322-9199-0

ABISEA Band 53 Kowal, J. Spatially-resolvedimpedance of nonlinear inhomogeneous devices - using the example of lead-acid batteries - 1. Auflage 2010, 214 Seiten ISBN 978-3-8322-9483-0

ABISEA Band 54 Roscher, M. Zustandserkennung von LiFeP04-Batterien für Hybrid- und Elektrofahrzeuge 1. Auflage 2011, 194 Seiten ISBN 978-3-8322-9738-l

ABISEA Band 55 Hirschmann, D. Highly Dynamic Piezoelectric Positioning 1. Auflage 2011, 156 Seiten ISBN 978-3-8322-9746-6

ABISEA Band 56 Rigbers, K. Highly Efficient Inverter Architectures for Three-Phase Grid Connection of Photovoltaic Generators 1. Auflage 2011, 254 Seiten ISBN 978-3-8322-9816-9

ABISEA Band 57 Kasper, K. Analysis and Control of the Acoustic Behavior of Switched Reluctance Drives 1. Auflage 2011, 214 Seiten ISBN 978-3-8322-9869-2

ABISEA Band 58 Köllensperger, P. The Internally Commutated Thyristor - Concept, Design and Application 1. Auflage 201 J, 212 Seiten ISBN 978-3-8322-9909-5


ABISEA Band 59 Schoenen, T. Einsatz eines DC/DC-Wand-lers zur Spannungs-anpassung zwischen Antrieb und Energiespeicher in Elektro-und Hybrid-fahrzeugen 1. Auflage 2011, 138 Seiten ISBN 978-3-8440-0622-3

ABISEA Band 60 Hennen, M.Switched Reluctance Direct Drive with Integrated Distributed Inverter 1. Auflage 2012, 150 Seiten ISBN 978-3-8440-0731-2

ABISEA Band 61 van Treek, D. Position Sensorless Torque Control of Switched Reluctance Machines 1. Auflage 2012, 144 Seiten ISBN 978-3-8440-IO 14-5

ABISEA Band 62 Bragard, M. Tue Integrated Emitter Turn-Off Thyristor. An Innovative MOS-Gated High-Power Device 1. Auflage 2012, 172 Seiten ISBN 978-3-8440-1152-4

ABISEA Band 63 Gerschler, J. B.Ortsaufgelöste Modellbil-dung von Lithium-Ionen-Systemen unter spezieller Berücksichtigung der Batteriealterung1. Auflage 2012, 350 Seiten ISBN 978-3-8440-1307-8

ABISEA Band 64 Neuhaus, C. Schaltstrategien für Geschaltete Reluktanz-antriebe mit kleinem Zwischenkreis 1. Auflage 2012, 144 Seiten ISBN 978-3-8440-1487-7

ABISEA Band 65 Butschen, T. Dual-ICT- A Clever Way to Unite Conduction and Switching Optimized Properties in a Single Wafer 1. Auflage 2012, 178 Seiten ISBN 978-3-8440-1771-7

ABISEA Band 66 Plum, T. Design and Realization of High-Power MOS Turn-Off Thyristors 1. Auflage 2013, 130 Seiten ISBN 978-3-8440-1884-4

ABISEA Band 67 Kiel, M.Impedanzspektroskopie an Batterien unter besonderer Berücksichtigung von Batteriesensoren für den Feldeinsatz 1. Auflage 2013, 232 Seiten ISBN 978-3-8440-1973-5

ABISEA Band 68 Brauer, H. Schnelldrehender Geschalteter Reluktanz-antrieb mit extremem Längendurchmesser-verhältnis 1. Auflage 2013, 202 Seiten ISBN 978-3-8440-2345-9

ABISEA Band 69 Thomas, S.A Medium-Voltage Multi-Level DC/DC Converter with High Voltage Transformation Ratio1. Auflage 2014, 236 Seiten ISBN 978-3-8440-2605-4

ABISEA Band 70 Richter, S. Digitale Regelung von PWM Wechselrichtern mit niedrigen Trägerfrequenzen 1. Auflage 2014, 134 Seiten ISBN 978-3-8440-2641-2

ABISEA Band 71 Bösing, M. Acoustic Modeling of Electrical Drives - Noise and Vibration Synthesis based on Force Response Superposition 1. Auflage 2014, 208 Seiten ISBN 978-3-8440-2752-5

ABISEA Band 72 Waag, W. Adaptive algorithms for monitoring of lithium-ion batteries in electric vehicles 1. Auflage 2014, 242 Seiten ISBN 978-3-8440-2976-5

ABISEA Band 73 Sanders, T.Spatially Resolved Electrical In-Situ Measurement Techniques for Fuel Cells 1. Auflage 2014, 138 Seiten ISBN 978-3-8440-3121-8

ABISEA Band 74 Baumhöfer, T. Statistische Betrachtung experimenteller Alterungs-untersuchungen an Lithium-Ionen Batterien 1. Auflage 2015, 174 Seiten ISBN 978-3-8440-3423-3

ABISEA Band 75 Andre, D. Systematic Characterization of Ageing Factors for High- Energy Lithium-Ion Cells and Approaches for Lifetime Modelling Regarding an Optimized Operating Strategy in Automotive Applications 1. Auflage 2015, 210 Seiten ISBN 978-3-8440-3587-2

ABISEA Band 76 Merei, G. Optimization of off-grid hybrid PV-wind-diesel power supplies with multi-technology battery systems taking into account battery aging1. Auflage 2015, 194 Seiten ISBN 978-3-8440-4148-4


ABISEA Band 77 Schulte, D.Modellierung und experi-mentelle Validierung der Alterung von Blei-Säure Batterien durch inhomogene Stromverteilung und Säureschichtung 1. Auflage 2016, 168 Seiten ISBN 978-3-8440-4216-0

ABISEA Band 78 Schenk, M.Simulative Untersuchung der Wicklungsverluste in Geschalteten Reluktanz-maschinen 1. Auflage 2016, 142 Seiten ISBN 978-3-8440-4282-5

ABISEA Band 79 Wang, Y.Development of Dynamic Models with Spatial Resolution for Electro- chemical Energy Converters as Basis for Control and Management Strategies 1. Auflage 2016, 198 Seiten ISBN 978-3-8440-4303-7

ABISEA Band 80 Ecker, M. Lithium Plating in Lithium-Ion Batteries: An Experimental and Simulation Approach 1. Auflage 2016, 170 Seiten ISBN 978-3-8440-4525-3

ABISEA Band 81 Zhou, W. Modellbasierte Auslegungs-methode von Tempe-rierungssystemen für Hochvolt-Batterien in Personenkraftfahrzeugen 1. Auflage 2016, 192 Seiten ISBN 978-3-8440-4589-5

ABISEA Band 82 Lunz, B. Deutschlands Stromversor-gung im Jahr 2050 Ein szenariobasiertes Verfahren zur vergleich-enden Bewertung von Systemvarianten und Flexibilitätsoptionen 1. Auflage 2016, 196 Seiten ISBN 978-3-8440-4627-4

ABISEA Band 83 Hofmann, A. Direct Instantaneous Force Control Key to Low-Noise Switched Reluctance Traction Drives 1. Auflage 2016, 244 Seiten ISBN 978-3-8440-4715-8

ABISEA Band 84 Budde-Meiwes, H. Dynamic Charge Acceptance of Lead-Acid Batteries for Micro-Hybrid Automotive Applications 1. Auflage 2016, 168 Seiten ISBN 978-3-8440-4733-2

ABISEA Band 85 EngeI, S. P. Thyristor-Based High-Power On-Load Tap Changers Control under Harsh Load Conditions1. Auflage 2016, 170 Seiten ISBN 978-3-8440-4986-2

ABISEA Band 86 VanHoek, H. Design and Operation Considerations of Three-Phase Dual Active Bridge Converters for Low-Power Applications with Wide Voltage Ranges 1. Auflage 2017, 242 Seiten ISBN 978-3-8440-5011-0

ABISEA Band 87 Diekhans, T. Wireless Charging of Electric Vehicles - a Pareto-Based Comparison of Power Electronic Topologies 1. Auflage 2017, 156 Seiten ISBN 978-3-8440-5048-6

ABISEA Band 88 Lehner, S.Reliability Assessment of Lithium-Ion Battery Systems with Special Emphasis on Cell Performance Distribution 1. Auflage 2017, 202 Seiten ISBN 978-3-8440-5090-5

ABISEA Band 89 Käbitz, S. Untersuchung der Alterung von Lithium-Ionen-Batterien mittels Elektroanalytik und elektrochemischer Impedanzspektroskopie 1. Auflage 2017, 257 Seiten urn:nbn:de:hbz:82-rwth-2016-120944

ABISEA Band 90 Witzenhausen, H. Elektrische Batteriespeichermodelle: Modellbildung, Parameteridentifikation und Modellreduktion 1. Auflage 2017, 286 Seiten urn:nbn:de:hbz:82-rwth-2017-034373

ABISEA Band 91 Münnix, J.Einfluss von Stromstärke und Zyklentiefe auf graphtitische Anoden 1. Auflage 2017, 178 Seiten DOI: 10.18154/RWTH-2017- 01915

ABISEA Band 92 Pilatowicz, G. Failure Detection and Battery Management Systems of Lead-Acid Batteries for Micro- Hybrid Vehicles

ABISEA Band 93 Drillkens, J. Aging in Electrochemical Double Layer Capacitors: An Experimental and Modelling Approach

ABISEA Band 94 Magnor, D. Globale Optimierung netzgekoppelter PV-Batteriesysteme unter besonderer Berücksichtigung der Batteriealterung

ABISEA Band 95 Iliksu, M. Elucidation and Comparision of the Effects of Lithium Salts on Discharge Chemistry of Nonaqueous Li-O2 Batteries


ABISEA Band 96 Schmalstieg, J. Physikalisch-elektrochemische Simulation von Lithium- Ionen-Batterien: Implementierung, Parametrierung und Anwendung 1. Auflage 2017, 176 Seiten DOI: 10.18154/RWTH-2017- 04693

ABISEA Band 97 Soltau, N. High-Power Medium-Voltage DC-DC Converters: Design, Control and Demonstration 1. Auflage 2017, 176 Seiten ISBN 978-3-942789-42-4

ABISEA Band 98 Stieneker, M. Analysis of Medium-Voltage Direct-Current Collector Grids in Offshore Wind Parks 1. Auflage 2017, 144 Seiten ISBN 978-3-942789-43-1

ABISEA Band 99 Masomtob, M. A New Conceptual Design of Battery Cell with an Internal Cooling Channel

ABISEA Band 100 Marongiu, A. Performance and Aging Diagnostic on Lithium Iron Phosphate Batteries for Electric Vehicles and Vehicle-to-Grid Strategies

ABISEA Band 101 Gitis, A. Flaw detection in the coating process of lithium-ion battery electrodes with acoustic guided waves

ABISEA Band 102 Neeb, C. Packaging Technologies for Power Electronics in Automotive Applications

ABISEA Band 103 Adler, F. S. A Digital Hardware Platform for Distributed Real-Time Simulation of Power Electronic Systems

ABISEA Band 104 Becker, J. Flexible Dimensionierung und Optimierung hybrider Lithium-Ionenbatterie-speichersysteme mit verschiedenen Auslegungszielen

ISSN 1437-675X

Battery electric vehicles are a cost intensive investment, caused by the energy storage systems, which are themselves domina-ted by the battery cell costs. To ensure the economic feasibility, the lifetime needs to be well known. Degradation in lithium ion batteries is typically studied at the anode, whereas cathode-centered research is driven by higher energy densities. In con-trast to this, the degradation mechanisms of the cathode are analyzed on a physical level in this work and then correlated to the capacity loss and resistance increase of the battery. The studies are based on accelerated aging tests on a commercial high energy lithium-ion cell. The electrodes were analyzed for structural degradation, dissolution and surface layer formation. It was possible to identify and quantify processes at the cathode that have a major influence on the degradation behavior of the battery.

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