Lithium Inventory Research Articles

Influence of state of charge window on the degradation of Tesla lithium-ion battery cells

The Tesla Model 3 is currently one of the most popular electric vehicle (EV) and was the best selling EV in 2020. In this article, performance and degradation of 21700 cylindrical cells, taken from a new vehicle, were studied by cycling within 10% State of charge (SOC) windows. Cells tested in either very high and very low SOC windows show faster degradation than at moderate SOC. In particular, the shortest service life was for cells cycled below 25% SOC. The ageing mechanisms of the cells cycled in these most extreme windows have been monitored by non-destructive electrochemical methods including analyses of differential voltage, incremental capacity, and voltage hysteresis. The combination of loss of lithium inventory (LLI) accelerated in early cycling by SiOx utilization, paired with loss of active material (LAM) of SiOx are responsible for the most rapid ageing, which is observed in the cells cycled in the 5%–15% SOC window. Calendar ageing, however, is not accelerated by storage at low SOC. The results from this study offer an understanding of the distinct, SOC-dependent ageing patterns observed in the cells. This understanding of the ageing mechanisms in different cycling and storage conditions can be used to recommend improved customer usage patterns and substantially extend the lifetime of lithium-ion batteries in operation.

Beyond Battery State of Charge Estimation: Observer for Electrode-Level State and Cyclable Lithium With Electrolyte Dynamics

This paper presents a provably convergent battery estimation scheme based on a single particle model with electrolyte dynamics (SPMe), by proposing a systematic methodology to estimate critical information such as electrode-level states, electrolyte dynamics, and cyclable lithium. Electrode-level state estimation suffers from weak observability originating from two standalone electrode dynamics, which is then aggravated by the addition of electrolyte dynamics. This lack of observability can be alleviated by exploiting lithium inventory conservation enabled by Kalman decomposition, allowing one to separate out the unobservable subspace. Assuming the knowledge of cyclable lithium, a nonlinear state observer with provable convergence can be constructed for the SPMe model, using voltage and current measurements. To relax this strong assumption, a sensitivity-based parameter estimation scheme is also deployed to track cyclable lithium – a crucial physical variable for capacity fade. Ultimately, the estimation framework can perform finer monitoring and diagnosis of battery charge and health down to the level of individual electrode and the electrolyte. Experimental validation demonstrates <1% estimation error for cyclable lithium inventory. Solid phase lithium concentration estimates, especially in the negative electrode, can be sensitive to disturbances in cyclable lithium.

Characterization of Cycle-Aged Commercial NMC and NCA Lithium-ion Cells: I. Temperature-Dependent Degradation

Lithium-ion batteries are widely used in applications from consumer electronic devices to stationary energy storage. Appropriate management of batteries is challenging due to limited data on their performance and materials degradation. Previous studies have focused on characterization of single cells under specific operating conditions. In the present work, commercial 18650 lithium-ion cells with LiNixMnyCo1-x-yO2 (NMC) and LiNixCoyAl1-x-yO2 (NCA) positive electrodes were characterized by a wide range of electrochemical and materials techniques after cycling at 15, 25, or 35 °C to ∼80% capacity. The NCA cells exhibit weak temperature dependence in their cycle aging and materials degradation. The NMC cells exhibited increased capacity fade and materials degradation as ambient temperature decreased. All cells exhibited loss of lithium inventory as their primary degradation mode. However, the NCA cells only showed evidence of solid electrolyte interphase (SEI) growth whereas the NMC cells showed signs of Li plating at 15 °C, transitioning to SEI growth at 35 °C. The NMC cells displayed signs of loss of active material at the positive electrode at lower temperatures, suggesting that Li plating is correlated to additional processes that increase the rate of degradation. These results highlight the importance of avoiding broad generalizations about Li-ion battery temperature dependence.

Developing rapid electrochemical relithiation protocols for scalable relithiation of lithium-ion battery cathode materials

The recent and ongoing boom in electric vehicle sales has caused the circularity of the supply chain for electric vehicle battery materials to come under a great deal of scrutiny. Innovative recycling processes, or direct recycling, that offer the possibility of reducing the cost of recycling are one possible solution to regaining resources from end-of-life (EoL) electric vehicle batteries. Electrochemically shuttling lithium back into the cathode, or electrochemical relithiation, is a possible technique for restoring lithium content to NMC materials (EoL) in a direct recycling process. This study provides essential understanding towards developing an electrochemical relithiation protocol that will restore lithium loss in intercalation cathode materials that reach EoL by loss of lithium inventory (LLI) as opposed to other degradation mechanisms like loss of active material (LAM), cation mixing or phase transition. Electrochemically aged NMC cathode materials have been prepared and characterized to establish the extent of EoL material structural degradation and lithium loss. A model-informed experimental process is used to identify the optimal electrochemical relithiation protocol to minimize the time taken to relithiate EoL materials and maximize the amount of lithium restored. Protocols were evaluated based on their ability to enable rapid lithium intercalation, maintain structural uniformity in the EoL material and fully restore lithium content. An optimal protocol was identified at elevated temperatures utilizing a novel scanning voltage step.

Influence of atmospheric pressure on the aging mechanism of LiCoO2/graphite cells

With the application of lithium-ion battery (LIB) in the field of electric aircraft, the aging behavior and mechanism of LIB under low-pressure environment have become an important topic. In this paper, the aging characteristics of LiCoO2/graphite cells under low pressure are investigated. The results show that the decrease of pressure leads to the degradation of cell capacity. With the pressure decreases from 96 kPa to 30 kPa, the capacity loss rate of the cell increases from 0.5 % to 17.4 %. Coulomb efficiency and differential voltage analysis indicate that low pressure accelerates the loss of lithium inventory. The X-ray computed tomography shows that the cell cycled under low pressure exhibits more significant deformation. The disassembly photos demonstrate that the side reactions of the cell are more obvious under low pressure. The scanning electron microscopy and elemental analysis results confirm that the thickness of solid electrolyte interface film increases with the decrease of pressure. These phenomena indicate that the intensification of battery deformation and internal side reactions under low pressure leads to a decrease in the electrochemical kinetics and long-term cycling ability of the battery.

Degradation study for 18650 NMC batteries at low temperature

This research focuses on the identification and quantification of lithium-ion battery degradation indicators at low temperatures. We studied the cycling aging of 18,650 commercial NMC lithium-ion batteries at 10 °C. For this purpose, we carried out life cycle tests and performed Galvanostatic Intermittent Titration Technique (GITT) tests in the voltage range for the charge and discharge processes for different States of Health (SoH). The diffusion time constant and the ohmic overpotential were determined from GITT for different SoH. As the batteries degrade both parameters increase. A degradation mechanism associated with faradaic effects (increase in ohmic drop overpotential) and a thermodynamic effect associated with changes in the active material (diffusional time constant) is observed. Furthermore, we performed Electrochemical Voltage Spectroscopy studies through Incremental Capacity (IC) curves. IC curves peaks and valleys are associated with battery phase transformations due to aging phenomena. Each peak has a unique peak height, area, and position associated with a degradation mode. This research focuses on the IC curves derived from the discharge capacities at 3A and OCP (Open Circuit Potential) to study the thermodynamic and faradaic effects separately. The peak at 3.6 V and 3.4 V for the 3A and OCP studies, respectively, is the main feature for the detection of the degradation mechanism. The valley in the OCP curves intensifies with the decrease in SoH and is shifted to lower potentials, an effect that is not observed in the 3A curves. So, we could associate this with thermodynamic effects, Loss of Lithium Inventory (LLI) and Loss of Active Material (LAM) of both the positive electrode and the negative electrode.

The impact of intermittent overcharging on battery capacity and reliability: Electrochemical performance analysis and failure prediction

Due to the inconsistencies among cells within the battery pack and the potential faults in battery management system, intermittent overcharging occurs during the long-term operation of cells. However, the impact of such occurrences on battery capacity and reliability has not been fully revealed. This study investigates the changes in electrochemical performance of the battery after conventional cycling and intermittent overcharge cycling and the causes of the changes through reference performance tests and material characterization techniques. The results indicate that the presence of intermittent overcharging accelerates capacity degradation and impedance rise in cells, which primarily result from secondary particles cracking, Li+/Ni2+ mixture, and transition metals dissolution, ultimately leading to the loss of cathode active material and lithium inventory. Moreover, the cells suddenly fail after about 100 cycles of intermittent overcharging, with the cause identified as the cumulative gas production resulting from side reactions between cathode and electrolyte, which eventually pushes the valve to bend, cutting off the internal electrical circuit. To predict battery failure caused by intermittent overcharging, a method is proposed by monitoring abnormal changes in surface temperature, charging capacity, and charging current during the overcharging stage, thereby enhancing the reliability of cells in practical applications.

Experimental studies of effects of temperature gradients on performance of pouch type large format NMC/C lithium-ion battery

Cell to pack design concept for energy storage in automotive applications leads to a substantially increased cell size that results in temperature gradients over the surface induced by non-uniform heat transfer linked to the cooling system design, which influences the cell performance. In this paper, temperature gradient effects on life performance of a large-format cell are experimentally investigated, using a developed device that can actively control appropriate gradients in the longitudinal direction and simultaneously measure the heat generation rate (HGR). Performances under uniform and non-uniform temperature conditions (MMM: uniform temperature, LMH: low-mean-high, HLH: high-low-high) are compared and quantified. At beginning of life (BOL), the low-temperature regions in the HLH and LMH conditions dominantly limit the cell capacity, and the HLH condition suppresses the HGR at high C-rates. During aging, the cell experiences a larger capacity fade and HGR increase under the HLH than MMM condition. The analyses of half coin cell, differential capacity (dQdV), dynamic resistance and impedance reveal that the attributing mechanisms are mainly the loss of Cathode active material, potentially the loss of lithium inventory, and the increase of impedances, indicating the electrochemically promoted side reactions and corrosions in the high-temperature regions of the HLH condition.

Elucidating Failure Mechanisms in Li-ion Batteries Operating at 100 °C

Rechargeable batteries that function at temperatures as high as 100 °C are desired for drilling instruments, autoclavable medical electronics, and space exploration. However, at 100 °C and beyond, lithium-ion batteries (LIBs) exhibit rapid capacity fade that prevent their use in many applications. Here, an in-depth study of the failure mechanisms was undertaken for LIBs operating at 100 °C containing graphite anodes, LiNi0.33Mn0.33Co0.33O2 (NMC111) cathodes, and organic electrolytes containing lithium hexafluorophosphate (LiPF6) and lithium tetrafluoroborate (LiBF4) salts. Electrochemical methods including differential analyses (dV/dQ) of galvanostatic cycling, electrochemical impedance spectroscopy (EIS), and linear polarization (LP) revealed that capacity loss was caused by a loss of lithium inventory in the cell due to film-forming reactions that siphon capacity. We hypothesized that capacity fade results from continual degradation and reformation of the anode solid electrolyte interphase (SEI), causing low coulombic efficiencies and poor cycle life. Crucially, electrode replacement of either the graphite or NMC111 with lithiated electrodes enabled full capacity recovery after high-temperature cycling, revealing that the electrode materials themselves were not inherently unsuitable for use at 100 °C. Overall, this study identifies the failure mechanisms of LIBs cycling at 100 °C, which are expected to guide the development of electrolyte formulations that improve electrode interphase stability and hence the performance of LIBs operating as high as 100 °C.

Experimental Study on High-Temperature Cycling Aging of Large-Capacity Lithium Iron Phosphate Batteries

Large-capacity lithium iron phosphate (LFP) batteries are widely used in energy storage systems and electric vehicles due to their low cost, long lifespan, and high safety. However, the lifespan of batteries gradually decreases during their usage, especially due to internal heat generation and exposure to high temperatures, which leads to rapid capacity degradation. In-depth research is needed on the degradation characteristics of large-capacity LFP batteries under high temperatures. To study the degradation characteristics of large-capacity LFP batteries at high temperatures, a commercial 135Ah LFP battery is selected for 45°C high-temperature dynamic cycling aging experiments and 25°C reference performance experiments. A detailed analysis of the degradation process is conducted by examining the patterns of changes in charge-discharge voltage curves, capacity, internal resistance, open circuit voltage (OCV), and incremental capacity curve. The study uncovers that the OCV displays diverse degradation patterns at different states of charge (SOC). Furthermore, it identifies the loss of lithium inventory and active material as the fundamental factors contributing to the degradation observed during high-temperature cycling. This study provides references for developing battery life prediction algorithms and designing long-cycle-life battery cells.

The Implications of Particle Morphology on the Capacity Retention, Side Reactions, and Impedance Build-Up of Nickel-Rich NCMs upon Cycling in Full-Cells: Poly- vs. Single-Crystalline NCM851005

The rising interest in single-crystalline NCMs (LiMO2, M = Ni, Co, Mn) has generated numerous publications which feature promising results in terms of cycle-life improvement when compared to the conventional polycrystalline analogues. To elucidate the effect of the two morphologies on the capacity retention and the internal resistance, this study aims to discriminate the effect of different degradation phenomena of polycrystalline and single-crystalline NCM851005 (LiNi0.85Co0.10Mn0.05O2) in coin full-cells cycled against graphite anodes. The impact of the particle morphology is analyzed over the course of more than 200 charge/discharge cycles for two temperatures of 25 and 45 °C, applying 4.1 or 4.4 V as upper cutoff voltages. The morphology-dependent surface area changes, resulting mainly from the tendency of polycrystalline NCMs towards particle cracking upon calendering, charging, and extended cycling, are quantified via krypton-gas physisorption, and the consequences of particle cracking regarding the amount of gas evolution, transition-metal dissolution, loss of lithium inventory, and resistance build-up are evaluated. In particular, the pronounced cathode impedance build-up of polycrystalline NCMs, investigated by electrochemical impedance spectroscopy using a micro-reference electrode in full-cells, exposes the impact of particle cracking and the induced electronic resistances within a secondary agglomerate on the rate capability.

An Identifiability Study of Lithium-Ion Battery Capacity Fade Using an Electrode-Specific Cell OCV Model

To achieve more accurate aging diagnosis and more effective management of lithium-ion batteries, it is essential to distinguish among the symptoms caused by different degradation mechanisms and be able to model them. So far, a lot of work has been focused on building mechanistic aging models for certain parameters of a cell model, but thorough examination of the extent to which these parameters can affect the detailed voltage response, and in turn be identified from such measurements, is scarce in literature. Moreover, capacity fade and power fade are often entangled in existing studies using a finite-current discharging/charging setup.As an initial step to unravel such intricate parametric influences and identifiability, we adopt a cell OCV (open circuit voltage) model and ignore polarization due to kinetic effects to focus on degradation manifested in the full-cell OCV curve and total capacity only. This cell OCV model , which is adapted from [1], is parametrized by two electrode OCP (open circuit potential) curves and three independent parameters: the cyclable lithium inventory, and the amount of anode and cathode active materials, all of which are directly related to capacity fade. We visualize and quantify the different impacts of LLI (loss of lithium inventory) and LAM (loss of active materials) on different segments of the cell OCV curve and on total capacity using gradients and Fisher information. Moreover, we use mutual information in a Bayesian setup to identify the amount and kind of measurements required to identify these parameters given a priori knowledge of them. Along the way, we also clarify the differences between electrode SOC (state of charge) and electrode lithium stoichiometry, and their implications for using electrode OCP and determining electrode capacity, which can at times cause confusion.Finally, we demonstrate how some of the degradation patterns outlined in [2], [3] can be cast among the continuum of capacity fade scenarios characterized by this simple cell OCV model. In particular, we show how incorporating electrode coulombic efficiencies into the model unifies and simplifies existing results about accounting for side reaction effects on cyclable lithium inventory [3]–[5].

Mechanical Impacts from Cycling on Silicon Calendar Aging Measurements

Much of the silicon anodes for lithium ion batteries literature concentrates on the volume expansion of silicon leading to poor cycle life. Recently, the poor calendar life of silicon has become more of a focus. Calendar aging is typically measured by long periods of open circuit voltage (OCV) that are intermittently interrupted with a reference performance test (RPT) to quantify performance and capacity fade. The United States Advanced Battery Consortium LLC protocol calls for an RPT once a month with daily voltage pulses to keep the state of charge the same during the rest. If the solid electrolyte interphase (SEI) is unstable and there is substantial volumetric changes during cycling, as is the case with silicon, the frequency and amount of cycling interruption may impact how calendar life is quantified. It was hypothesized that an SEI that equilibrates during a rest may be disrupted enough during RPT cycling that the SEI passivation is decreased and the start of the next rest will result in greater irreversible lithium inventory consumption to rebuild the SEI that was lost during cycling. To test this, a specially designed variable OCV-RPT protocol was applied to silicon – NMC622 full cells. It was found that for all rest durations, time since assembly, rather than cycling, dominated capacity fade, indicating that calendar aging is likely primarily governed by chemical SEI degradation during rest rather than mechanical SEI degradation during RPTs.This research was supported by the U.S. Department of Energy’s Vehicle Technologies Office under the Silicon Consortium Project, directed by Brian Cunningham, and managed by Anthony Burrell. This work was conducted in part by the Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Sandia National Laboratories is a multimission Laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Voltage Differential Analysis during Power Discharge Operation in Energy Storage Systems

Constant Power Discharge (CPD) is a lucrative operating mode for grid-tied ESS in many energy markets. The CPD mode corresponds to an increasing current drawn as the ESS discharges. The operation can be modeled with an aged anode and cathode open circuit potentials (OCPn/p+RRC) model that can let us identify electrode-level (eSOH) parameters and resistance growth even though we do not have slow discharge with Constant Current. This identification process from realistic ESS field data, namely constant power discharge, will enable continuous eSOH diagnostics and lead to real-time and operando quantification of loss of active material and loss of lithium inventory (LAM and LLI, respectively).In addition, the timing of when the cell groups' differential voltage peaks occur when the battery system is under constant power operations inform us about the imbalance among cell groups in a module of a battery system, as shown in the figure. Using the time separation among cell differential voltage peaks as a metric of cell imbalance can improve cell balancing algorithms that measure cell imbalance using maximum or minimum voltage, which can be directly affected by the power limits of the battery system.The efficacy of the proposed algorithms is evaluated for multi-cell modules consisting of NMC/graphite cells, operating as part of a large-scale grid-connected energy storage system. Ultimately, by enabling improved diagnostics of the state of health of individual cells in a battery system and improved cell balancing algorithms, this work will enhance the performance and safety of large-scale lithium-ion battery systems. Figure 1

Utilizing Bayesian Optimization to Facilitate Differential Voltage Analysis of Lithium Ion Batteries

Differential voltage analysis (DVA) is a non-destructive, in situ method for analyzing degradation in lithium ion (Li-ion) batteries, and can be used to identify major modes of performance degradation, such as loss of lithium inventory (LLI) and loss of active material (LAM). Using the cycling voltage derivative with respect to capacity of half cells and full cells, DVA can be used to estimate which mode is the main contributor to degradation. Analysis of the signature peaks in the half cell to the full cell can reveal the degradation mode of full cell. Shifts in the peak can indicate LLI, while intensification and narrowing of peaks can indicate LAM. Analyzing the peak changes after cycling allows quantitative determination of how much cell aging has occurred, and what mode is involved in the cell aging process. However, the process of analyzing peak changes manually is inefficient and time consuming. In this work, we utilize a Bayesian optimization approach to facilitate the process of fitting full cell DVA data with pristine half-cell data. The Bayesian optimization algorithm finds the best deformation of pristine half-cell data to fit full-cell data automatically and efficiently for multiple chemistries. The only manual procedures for each fitting are reading data files into the program and determining a coarse bound. The rest is automated and takes less than ten minutes for each fitting. The fitting accuracy is comparable to manual fitting and significantly less time consuming. This method facilitates battery aging analysis and can be generalized to different kinds of data sets as well.

Accelerated Prediction and Analysis of Lithium-Ion Battery Lifetime Using Efficient Electrochemical Models

Lithium-ion batteries degrade over their lifetime due to several parasitic reactions that occur in the cell. These reactions lead to loss of lithium inventory, loss of active material, mechanical and thermal damage to the cell’s component. Predicting cell aging and capacity fade is crucial for battery management systems (BMS) to monitor and control the battery's state of health. Physics-based models are valuable in battery management systems (BMS) to monitor the battery’s state of health and predict battery failure. BMS algorithms require fast codes that can predict and estimate battery parameters in real-time and control the battery’s performance under different loads.1 Common reduced-order models, such as the SPM (Single Particle Model) consider approximations that may not be valid as the cell ages. The Tanks-in-Series model is a model developed by Subramaniam et al., where the governing equations from the full-order ‘pseudo-2-D’ (p2D) model are volume-averaged over each cell region.2 This ensures that the physics captured by the mass and charge conservation equations are maintained without loss of accuracy while providing simulation solutions at a few milliseconds. The Tanks-in-Series model is ideal for predicting cell aging due to its reduced computation speed and predictability beyond other reduced-order models.This work combines the Tanks-in-Series model with governing equations for several degradation mechanisms, including the growth of the SEI layer, lithium plating, particle cracking, etc. A comprehensive analysis of capacity fade predictions is shown, with comparisons to predictions from the P2D model. References V. Ramadesigan et al., J. Electrochem. Soc., 159, R31–R45 (2012).A. Subramaniam et al., J. Electrochem. Soc., 167, 013534 (2020).

High-Voltage Degradation of Ni-Rich Cathode Materials in All-Solid-State Batteries

Lithium-ion battery (LIB) has been widely used as electrochemical energy storage devices in a variety of fields in our daily lives. In particular, recently there are strong market demands in the energy storage systems and electric vehicles, mainly due to its high energy and power densities. However, the customers’ strong needs for the safer and longer-lasting battery than commercial ones have sparked special interest in all-solid-state lithium battery (ASSB), which has a great possibility of replacing the conventional LIB that uses liquid electrolyte solution. Though much effort has been made for its practical applications, there are still a number of critical issues involved in the electrode/cell design, fabrication, scale-up, efficient operating conditions, etc. Upper cut-off voltage is one of the most important parameters, having a determinative effect on the energy density and cycling stability of the ASSB esp. when one uses Ni-rich layered oxide cathodes. Actually, the upper cut-off voltage is treated with high priority also in the LIB systems. In the case of the LIB, the secondary particle cracking is followed by gap-filling with electrolyte during the repetitive high voltage charging, giving additional electrochemical active area. Whereas, the particle cracking in the ASSB usually leads to the isolation of the primary particles. In addition, it is reported that the interface between active materials and solid electrolyte is degraded in a complex manner due to simultaneous chemical side reactions (e.g. cathode electrolyte interphase (CEI) formation) and mechanical breakdown (e.g. contact loss between electrolyte and particle), different from that of the LIB. Therefore, an analysis of cathode degradation in the ASSB needs to be dealt with in a different way from that in the LIB.In this work, the degradation of ASSB, consisting of sulfide-based solid electrolyte and Ni-rich cathode, undergoing the high voltage charge cycling is systematically studied using the electrochemical techniques. For this purpose, first, the deterioration tendency of reversible capacity and cell resistance was analyzed in constant current-constant voltage (CC-CV) charging mode at different upper cut-off voltages (CC charging) and the following charging times (CV charging). In addition, the effect of charging rate on the degradation trend was investigated in terms of the duration time that the cathode potential stays higher than a specific potential value in CC charging mode. It was confirmed that there are particular degradation tendencies of capacity and resistance for upper cut-off voltage and duration time, and the empirical relations were accordingly derived. Notably, the degradation trends between capacity and resistance were observed differently, strongly indicative of different governing factor for each degradation process. In the experiments at various charging rates, the lower charging rate led to larger degradation of the cathode. It is suggested that the application of a driving force for irreversible phase transition (i.e., from H2 to H3) for longer time at lower charging rate is the most probable reason.In order to more clearly understand the governing factors affecting high voltage cathode degradation, the degradation trends of capacity and resistance at the aforementioned operating conditions were thoroughly investigated using incremental capacity-differential voltage (IC-DV) analysis and electrochemical impedance spectroscopy (EIS), respectively. From the IC-DV analysis, it proved that the loss of active materials (LAM) is accelerated at higher cut-off voltage, longer duration time, and lower charging rate, indicating that the LAM might be one of the governing factors for capacity degradation. It is notable, by the way, that the interfacial resistance of the cathode was considerably increased at high voltage charging and implies the loss of lithium inventory (LLI) due to the CEI formation could be another major degradation mode. Accordingly, we tried to estimate the contribution of LLI to total degradation from the comparison of half-cell and full-cell analyses. On the other hand, from the EIS analysis, it was found that the increasing rate of the interfacial resistance was far higher than the decreasing rate of capacity. This tells us that the degradation of the cathode|electrolyte interface is mainly responsible for the resistance or power degradation at high voltage charging. In this presentation, the deterioration modes of ASSB at various high voltage charging conditions are explained in terms of the interface and bulk of the cathode. Moreover, the strategy to minimize the degradation at high voltage charging will be discussed.

Ageing of High Energy Density Automotive Li-Ion Batteries: The Effect of Temperature and State-of-Charge

Lithium ion batteries (LIB) have become a cornerstone of the shift to electric transportation. In an attempt to decrease the production load and prolong battery life, understanding different degradation mechanisms in state-of-the-art LIBs is essential. Here, we analyze how operational temperature and state-of-charge (SoC) range in cycling influence the ageing of automotive grade 21700 batteries, extracted from a Tesla 3 long Range 2018 battery pack with positive electrode containing LiNixCoyAlzO2 (NCA) and negative electrode containing SiOx-C. In the given study we use a combination of electrochemical and material analysis to understand degradation sources in the cell. Herein we show that loss of lithium inventory is the main degradation mode in the cells, with loss of material on the negative electrode as there is a significant contributor when cycled in the low SoC range. Degradation of NCA dominates at elevated temperatures with combination of cycling to high SoC (beyond 50%).

Quantitative Analysis of Origin of Lithium Inventory Loss and Interface Evolution over Extended Fast Charge Aging in Li Ion Batteries.

During the extreme fast charging (XFC) of lithium-ion batteries, lithium inventory loss (LLI) and reaction mechanisms at the anode/electrolyte interface are crucial factors in performance and safety. Determining the causes of LLI and quantifying them remain an essential challenge. We present mechanistic research on the evolution and interactions of aging mechanisms at the anode/electrolyte interface. We used NMC532/graphite pouch cells charged at rates of 1, 6, and 9 C up to 1000 cycles for our investigation. The cell components were characterized after cycling using electrochemical measurements, inductively coupled plasma optical emission spectroscopy, 7Li solid-state nuclear magnetic resonance spectroscopy, and high-performance liquid chromatography/mass spectrometry. The results indicate that cells charged at 1 C exhibit no Li plating, and the increase of SEI thickness is the dominant source of the Li loss. In contrast, Li loss in cells charged at 9 C is related to the formation of the metallic plating layers (42%) the SEI layer (38.1%) and irreversible intercalation into the bulk graphite (19%). XPS analysis suggests that the charging rate has little influence on the evolution of SEI composition. The interactions between competing aging mechanisms were evaluated by a correlation analysis. The quantitative method established in this work provides a comprehensive analytical framework for understanding the synergistic coupling of anodic degradation mechanisms, forecasting SEI failure scenarios, and assessing the XFC lithium-ion battery capacity fade.

Accurate LLI and LAMPE Estimation Using the Mechanistic Modeling Approach with Layered Oxides

In the past decade and half since their introduction, multiple frameworks of mechanistic models were made available to enable the quantification of loss of lithium inventory and loss of active materials. They usually come either with capacity/state of charge- or lithiation-based matching for the electrodes. While both approaches were believed to be equivalent, the present work will show that they are not when used with materials that are not fully delithiated at end-of-charge because they differ on how they account for inaccessible lithium. Herein, we will explain these discrepancies and propose new equations to improve both types of frameworks.