Growth Of Solid Electrolyte Interphase Layer Research Articles

Is silicon worth it? Modelling degradation in composite silicon–graphite lithium-ion battery electrodes

The addition of silicon into graphite lithium-ion battery anodes has the potential to increase cell energy density. However, understanding the complex degradation behaviour in these composite systems remains a research challenge. Here, we developed a coupled electrochemical–mechanical model of a composite silicon/graphite electrode, including stress-driven crack formation and solid electrolyte interphase layer growth for each material, validated with experimental degradation data from an LG M50T cell. The model reveals self-limiting loss of silicon due to decreasing stress in the silicon as the silicon activity shifts to a lower state-of-charge. Higher C-rates can lead to lower degradation due to lower phase utilisation as voltage cut-offs are reached earlier. Increasing silicon content can reduce the stress in the silicon by distributing reaction current density over more material. Using this model, we explored whether the extra capacity from silicon is generally ‘worth’ the faster degradation compared to graphite-only electrodes. The model shows if you use the silicon, you lose it, as the higher initial capacity is rapidly lost with regular high depth-of-discharge events. However, silicon does have value if it enables full graphite utilisation without range anxiety; if high depth-of-discharge events are minimised then graphite’s superior longevity can be utilised while exploiting silicon’s high specific capacity. The model is integrated into PyBaMM (an open-source physics-based modelling platform); providing the research community and industry with the capability to reproduce our results and further explore the dynamic lifetime behaviour of composite electrodes.

(Invited) Dendrite Formation in Lithium Electrodeposition – Insights from Experiments and Modeling

High-energy density batteries are essential for powering future electric vehicles and electric aircrafts. The Li-metal anode offers the highest theoretical specific energy among practically available anode materials; however, a major hurdle in the progress towards rechargeable Li-metal batteries is the dendritic electrodeposition of Li metal during the battery charging process. The physicochemical mechanisms behind Li dendrite formation have been a topic of rich and fervent research, but many questions remain presently unanswered. Among these, a key question of significance to battery charging is: at what time instant is Li dendritic growth initiated? In the present talk, this question will be addressed through a combination of experiments and modeling. Chronopotentiometry during galvanostatic Li electrodeposition coupled with in situ optical microscopy reveals that the first emergence of Li dendrites corresponds to the time instant when the surface overpotential reaches a maximum.1 Electrochemical impedance spectroscopy shows that the increase in the surface overpotential preceding this maximum is due to gradual growth of the solid electrolyte interphase (SEI). This SEI layer growth induces Li+ concentration depletion at the electrode-SEI interface, promoting amplification of surface asperities and thus dendrites that rupture the SEI. A transport model incorporating Li+ diffusion across a growing SEI layer is developed, and shown to predict Li dendrite onset times that are in good agreement with experimental observations over a wide range of current densities, temperature, and initial SEI thicknesses.2 A key conclusion of our work is that liquid-phase mass transport limitations, often characterized by the Sand’s equation, do not reliably predict the onset of Li dendrites.3 Rather, transport characteristics and associated instabilities within solid-phase surface films on Li are predominantly responsible for dendrite formation. Our work provides clues for how dendrite formation could be arrested for enabling rechargeable Li-metal anodes for use in next-generation batteries.

Cycle-dependent morphology and surface potential of germanium nanowire anode electrodes.

Germanium nanowire (GeNW) electrodes have shown great promise as high-power, fast-charging alternatives to silicon-based electrodes, owing to their vastly improved Li ion diffusion, electron mobility and ionic conductivity. Formation of the solid electrolyte interphase (SEI) on the anode surface is critical to electrode performance and stability but is not completely understood for NW anodes. Here, a systematic study characterizing pristine and cycled GeNWs in charged and discharged states with SEI layer present and removed is performed using Kelvin probe force microscopy in air. Correlating changes in the morphology of the GeNW anodes with contact potential difference mapping at different cycles provides insight into SEI layer formation and growth, and the effect of the SEI on battery performance.

Optimal Charging Protocols to Restrict Lithium-Ion Battery Degradation

Lithium-ion batteries degrade due to several mechanisms that occur during cell operation. These mechanisms can be parasitic reactions that lead to loss of lithium inventory or loss of active material. Some examples of these side reactions include the growth of the solid-electrolyte interphase (SEI) layer, transition metal dissolution and deposition, lithium plating, solvent oxidation, etc. Thermal effects and mechanical fatigue on the electrodes also lead to cell aging and capacity fade.For widespread implementation of lithium-ion batteries for electric vehicles, batteries should last approximately 10 years.1 Fast charging has also been heavily researched for accelerating this prevalent circumstance. However, charging at high currents can severely degrade the cell, affecting the cell’s lifetime. Algorithms that optimize charging can be effective to reduce cell aging. Physics-based battery models can be used to design these algorithms by restricting phenomena that occur in the cell that causes cell aging. For example, lithium plating can be prevented by restricting the overpotential of the reaction.In our previous work, we have shown optimal charging profiles where the intercalation induced stresses, lithium plating and the SEI layer growth was restricted using reformulated physics-based models using model-based control 2 - 3 In this talk, we show different optimal charging protocols for restricting different mechanisms, and analyze the interplay between them to predict optimal charging profiles. References M. T. Lawder, P. W. C. Northrop, and V. R. Subramanian, J. Electrochem. Soc., 161, A2099–A2108 (2014).B. Suthar, P. W. C. Northrop, R. D. Braatz, and V. R. Subramaniand, J. Electrochem. Soc., 161, F3144–F3155 (2014).M. Pathak, D. Sonawane, S. Santhanagopalan, R. D. Braatz, and V. R. Subramanian, ECS Trans., 75, 51–75 (2017).

The Importance of a Moving Boundary Approach for Modeling the SEI Layer Growth to Predict Capacity Fade

One of the contributing factors to the aging of lithium-ion batteries is the growth of the solid-electrolyte interphase (SEI) layer. The growth of the SEI layer leads to the irreversible loss of lithium available for cycling and increases the resistance of the battery. Physics-based models in literature model the kinetically limited or solvent diffusion-limited growth. In such models, the interface resistance is a constant, and the contribution to the overpotential of the intercalation reaction from the SEI layer is considered to be ohmic. In this study, we propose a model that describes the growth of the SEI layer on the electrode surface as a moving interface. The transport of lithium ions and the solvent in the electrolyte are affected by this moving interface. The equations that govern the species transport and the potential drop across the SEI layer are derived from dilute solution theory and solved by transforming the coordinates of the moving boundary. The ion transport induces changes in the conductivity across the SEI layer, which affects the potential drop that arises due to its growth. The effects of this potential on capacity fade are studied over cycling the battery.

Solid Electrolyte Interphase Growth in Lithium Metal Cells With Normal Electrolyte Flow

In high energy density lithium metal batteries (LMBs), dendrite and solid electrolyte interphase (SEI) growth reduce safety and longevity, respectively. A stable SEI layer enables high efficiency cycling but continued SEI growth can lead to reduced capacity and coulombic efficiency. In this paper, we develop a steady-state model that predicts the effect of small advective electrolyte flow towards the lithium metal electrode on SEI growth during charging. For a fixed current density, increasing the electrolyte flow rate improves the coulombic efficiency and decreases SEI layer growth rate. Decreasing the charging current density at a constant flow rate also decreases the SEI layer growth rate. Low flow rates (μm/s) can increase coulombic efficiency by up to 6%. The sensitivity of the coulombic efficiency to plating and SEI layer reaction rates is also explored.

Analysis of the lithium-ion battery capacity degradation behavior with a comprehensive mathematical model

The influence of transition metal deposition on the capacity of lithium-ion batteries (LIBs) can not be ignored. The current model lacks a comprehensive analysis of the coupling phenomenon. Based on the classic P2D model, we propose a comprehensive capacity degradation model of LIBs, with a complete description of the side effects of transition metal dissolution in the positive electrode, solid electrolyte interphase (SEI) formation, and metal deposition in the negative electrode. Simulations are implemented and compared for the evolution of the battery capacity as cycling progressed in different cases of only SEI layer growth, SEI growth couples with Li plating, SEI growth couples with Mn dissolution and deposition, and all the three factors fully couples. The capacity degradation behavior is revealed from the perspective of lithium-ion inventory, diffusion coefficient, and porosity. The results show that the plating of Li leads to a significant decrease of the lithium-ion concentration, which is the prime for the attenuation of capacity. The growth of SEI alone has little effect on the capacity, which maintains 95.9% even after 2500 cycles. Although the dissolved content of Mn is just ppm scale, it can accelerate the growth of SEI layer and thus obviously affect the battery capacity. • Presenting a comprehensive lithium-ion battery model. • A lithium-ion battery model to predict capacity degradation. • Revealing the coupling relationship of side reactions. • Clarifying the influence level of each side reaction on capacity degradation. • The model fully reflects the behavior of Mn-ions.

Rate Capability Testing of Graphite Electrode Material

The paper deals with the investigation of natural graphite electrode materials for lithium-ion batteries. These negative electrode materials operate on the intercalation principle where graphite plays a host role for lithium ions. There is a solid electrolyte interphase (SEI) layer which origins from electrode-electrolyte interphase. The SEI layer is a fundamental part of lithium-ion battery system and its quality defines and highly affects the overall quality of lithium-ion battery itself. Growth of the SEI layer is connected with the formation of new compounds. The process formation of SEI layer is linked to energy consumption (energy loss). What is most important is the fact that the growth of SEI layer consumes the significant amount of lithium ions provided from a limited positive electrode (cathode) source. In this work, the lithiation method was employed to reduce these undesirable side effects of the SEI growth.

Regulating lithium-ion flux in the solid electrolyte interphase layer to prevent lithium dendrite growth on lithium metal anode

High theoretical capacity and lowest electrochemical potential make lithium metal anode the most suitable anode material for lithium-ion batteries (LIBs). However, Lithium dendrite growth on lithium metal anode hinders proper discharge capacity and practical cycle life of LIBs. It dues to high lithium-ion flux in the solid electrolyte interphase (SEI) layer versus low diffusion in anode structure. Herein, we employ argon and oxygen plasma to modify commercial polypropylene separator surface to negatively functionalize the separator surface and discuss the influence of increasing surface negative charge on lithium dendrite growth and formation of SEI layer. Comparing electrochemical and battery performance of unmodified and plasma modified separators demonstrates, increased negative surface charge prevents lithium dendrite growth and makes a uniform and thin SEI layer due to lowering lithium-ion flux in the SEI layer. More precisely, we conduct that coulombic interaction between plasma modified separator's surface and electrolyte's cations (anions) can regulate lithium-ion flux in the SEI layer, preventing lithium dendrite growth and making thin homogeneous SEI layer on lithium metal anode structure.

Flowing Electrolyte Metal Batteries

Flowing electrolyte metal batteries (FEMBs) are a new class of energy storage devices with metal anodes and flowing electrolytes. In this presentation, electrochemical models predict that flowing electrolyte can accelerate diffusion-limited transport, reducing impedance, increasing stability, and improving coulombic efficiency and cycle life. Electrolyte flow toward the metal electrode reduces and, for flow velocities above a critical speed, changes the sign of the electrolyte impedance, allowing faster charging without exceeding voltage limits. The critical flow rate is very slow (~μm/s) and directly proportional to the charging current density. Concentration of diffusion flux at dendrite tips is responsible for accelerated dendrite growth in metal batteries, so introduction of creeping electrolyte flow normal to electrodes levels ion concentration and eliminates dendrites above the critical speed. Creeping normal flow also significantly reduces solid electrolyte interphase (SEI) growth rate [1]. Creeping Poiseuille and Couette flows that are parallel to the electrodes have no impact on impedance or SEI layer growth, but do reduce dendrite growth, albeit much less effectively than normal flow [2]. Both creeping normal and parallel flows eliminate/reduce dendrite growth, so introducing electrolyte flow, in general, is a promising method to control dendrite growth. As dead Li formation is tied to dendrite growth, and as creeping normal flow eliminates dendrites and reduces SEI layer growth [3], creeping normal flows significantly improve coulombic efficiencies, and cycle life. The low flow rates indicate potential for practical applications.[1] Parekh, Mihir N., Christopher D. Rahn, and Lynden A. Archer. "Controlling dendrite growth in lithium metal batteries through forced advection." Journal of Power Sources 452 (2020): 227760.[2] Parekh, Mihir N., and Christopher D. Rahn. "Reducing Dendrite Growth in Lithium Metal Batteries by Creeping Poiseuille and Couette Flows." Journal of the Electrochemical Society (2020).[3] Parekh, Mihir N., and Christopher D. Rahn. “Solid electrolyte interphase growth on lithium metal electrodes with normal electrolyte flow.’’ Journal of the Electrochemical Society (Submitted). Figure 1

A New Modeling Approach to Simulate the SEI Layer Growth in Lithium-Ion Batteries to Predict Capacity Fade

Lithium-ion batteries degrade as they are cycled due to different phenomena that occur inside the cell that lead to the loss of their capacity. One of the dominant mechanisms that leads to capacity fade is the growth of the solid-electrolyte interphase (SEI) layer due to the reduction of the electrolyte solvent on the electrode surface 1. This passive layer ideally prevents the electrolyte from interacting with the electrode, preventing further reduction of the electrolyte. However, the growth of the SEI layer during cycling leads to the irreversible loss of lithium available for cycling and increases the resistance of the battery.Physics-based models to study the growth of the SEI layer for predicting capacity fade are reported in the literature.2 -8 Adding the SEI layer growth mechanism to battery models can help predict the capacity fade of a cell under different charging protocols and drive cycles for EV and PHEV batteries 2. The different models that exist in literature consider the growth to be kinetic-limited 3 , 4 , diffusion-limited 5, or a combination of both 6 , 7 , 8. In previous studies, the relationship between the growth of the SEI layer and the interface resistance is assumed to be linear and the contribution of the same to the overpotential of the intercalation reaction is assumed to be ohmic. This is because the transport of lithium ions through the SEI layer is not included in these models.In this work, we propose a model that describes the growth of the SEI layer on the graphite anode as a moving interface. The mass transport of both lithium ions and the solvent in the electrolyte are modeled which are affected by this moving interface. The transport during kinetic-limited and diffusion-limited growth are analyzed for different C-rates as the battery is cycled. The ion transport also induces changes in the conductivity across the SEI layer which affects the potential that arises due to its growth. This important effect and its influence on capacity fade is studied by simulating battery cycling using the proposed model. These studies help improve the fundamental understanding of the impact of different battery design parameters and operating conditions on capacity loss and cell lifetime. Acknowledgement This work at the University of Texas at Austin was supported by U.S. DOE Office of Electricity award DEAC05-76RL01830 through PNNL subcontract 475525. References P. Arora, R. E. White, and M. Doyle, J. Electrochem. Soc., 145, 3647–3667 (1998).M. T. Lawder, P. W. C. Northrop, and V. R. Subramanian, J. Electrochem. Soc., 161, A2099–A2108 (2014).P. Ramadass, B. Haran, R. White, and B. N. Popov, J. Power Sources, 123, 230–240 (2003).G. Ning and B. N. Popov, J. Electrochem. Soc., 151, 1584–1591 (2004).H. J. Ploehn, P. Ramadass, and R. E. White, J. Electrochem. Soc., 151, 456–462 (2004).M. Safari, M. Morcrette, A. Teyssot, and C. Delacourt, J. Electrochem. Soc., 156, 145–153 (2009).X. G. Yang, Y. Leng, G. Zhang, S. Ge, and C. Y. Wang, J. Power Sources, 360, 28–40 (2017).N. Kamyab, J. W. Weidner, and R. E. White, J. Electrochem. Soc., 166, A334–A341 (2019).

Modelling capacity fade in silicon-graphite composite electrodes for lithium-ion batteries

Silicon-based composite electrodes in lithium ion batteries attract increasing attention because of their high theoretical capacity. Here, numerical simulations are used to better understand the interplay between electrochemical and morphological behavior of the silicon-graphite (1:2.7) composite electrode during galvanostatic cycling. Finite element methodology is used to solve a one-dimensional model based on the porous electrode and concentrated solution theory. Porosity changes in the silicon electrode and solid electrolyte interphase layer growth are also included in the model. The simulation results show that at lower rates, the electrode with high initial porosity is being fully utilized before the lower cut-off potential is reached. When comparing the computational results with experimental observations, it can be seen that the main reason for capacity fade is the increase in tortuosity in the diffusion pathway of lithium ions due to cracking of the silicon composite electrode upon electrochemical cycling.

Electrically Conductive Shell-Protective Layer Capping on the Silicon Surface as the Anode Material for High-Performance Lithium-Ion Batteries.

Rational design and construction of effective silicon (Si) electrode structures to relieve large volumetric changes that occur during the charge/discharge process remain significant challenges for the development of robust lithium-ion batteries (LIBs). Herein, we propose an electrically conductive poly[3-(potassium-4-butanoate)thiophene] (PPBT) capping layer on the Si surface (Si@PPBT) to serve as the active material and be used in conjunction with a common polymer binder as an approach to tackle issues emanating from volumetric changes. The PPBT protective shell layer provides the system with tolerance toward variations in active material volume during cycling, improves the dispersion of Si nanoparticles in the binder, enhances the electrolyte uptake rate, and provides a strong adhesion force between the Si/carbon additives/current collector, thereby helping to maintain electrode integrity during the charge/discharge process. The π-conjugated polythiophene backbone structure also allows the Si core to maintain electrical contact with carbon additives and/or polymer binder, enabling the formation of effective electrical transport bridges and stabilizing solid electrolyte interphase layer growth. The integrated Si@PPBT/carboxymethyl cellulose (CMC) anode exhibited high initial Coulombic efficiency (84.9%), enhanced rate capability performance, and long cycling stability with a reversible capacity of 1793 mA h g-1 after 200 cycles, 3.4 times higher than that of pristine Si anodes with the same CMC binder (528 mA h g-1). The results suggest that the Si@PPBT design presents a promising approach to promote the practical use of Si anodes in LIBs, which could be extended to other anode materials exhibiting large volume changes during lithiation/delithiation.

Review of Capacity Fade Models for Lithium-Ion Batteries - Numerical Implications of SEI Layer Growth

Lithium-ion battery applications, such as EVs and PHEVs, require long battery life. However, capacity fade always occurs due to unwanted side reactions including electrolyte oxidation at the positive electrode, lithium deposition at the negative electrode, electrolyte decomposition processes, and formation of the Solid-Electrolyte Interphase (SEI) layer1. To model the capacity fade, different models have been proposed in the literature2-4. In this presentation, we model the capacity fade by assuming the SEI layer formation to be the dominant mechanism. We address how to efficiently simulate SEI layer growth and modify the simulation approach for the solid phase equations if needed. Even within SEI layer models, several different expressions have been used in many papers5-8. In most cases, the solid particles are assumed to be spherical, and the intercalation process is modeled using Fick’s law of diffusion in the radial direction. For solving the solid-phase diffusion in the radial-dimension, many efficient methods to reformulate and simulate have been proposed in the past9-12. The SEI forming side reaction with the Single Particle Model (SPM) is first studied. The partial differential equation of the SPM is discretized using the finite difference method in radial direction and solved in time using the numerical method of lines approach. An assumption of a parabolic profile in the radial direction is another efficient approximation9-12. After this, we combine the SEI layer model with the pseudo two-dimensional model to predict the performance of the battery. Acknowledgements The authors thank the Department of Energy (DOE) for providing partial financial support for this work, through the Advanced Research Projects Agency (ARPA-E) award number DE-AR0000275. References P. Arora, R. E. White, M. Doyle, J. Electrochem. Soc., 145, 3647-3667 (1998).J. Park, J. H. Seo, G. Plett, W. Lu, A. M. Sastry, Electrochem. Solid-State Lett., 14, A14 (2011).Y. Dai, L. Cai, R. E. White, J. Electrochem. Soc., 160, A182 (2013). X. Lin, J. Park, L. Liu, Y. Lee, A. M. Sastry, J. Electrochem. Soc., 160 (10) A1701-A1710 (2013).M. Safari, M. Morcrette, A. Teyssot, and C. Delacourt, J. Electrochem. Soc., 156(3), A145-A153 (2009).P. Ramadass, B. S. Haran, P. M. Gomadam, R. H. White, and B. N. Popov, J. Electrochem. Soc., 151, A196 (2004).M. B. Pinson, M. Z. Bazant, J. Electrochem. Soc., 160 (2) A243-A250 (2013).H. Ekström, G. Lindbergh, J. Electrochem. Soc., 162 (6) A1003-A1007 (2015).C. Y. Wang, W. B. Gu, and B. Y. Liaw, J. Electrochem. Soc., 145, 3407 (1998).W. B. Gu, C. Y. Wang, and B. Y. Liaw, J. Electrochem. Soc., 145, 3418 (1998).P. W. C. Northrop, V. Ramadesigan, S. De and V. R. Subramanian, J. Electrochem. Soc., 158 (12) A1461-A1477 (2011).V. Boovaragavan, V. Ramadesigan, and V. R. Subramanian, J. Electrochem. Soc., 157 (7) A854-A860 (2010).

Li-ion battery ageing model parameter: SEI layer analysis using magnetic field probing

With the growing usage of lithium-ion (Li-ion) batteries in various applications from stationary applications to automotive industries, their ageing mechanism and its influencing factors have become a big concern today. Ageing may be defined as deterioration in the performance of the battery due to irreversible physical and chemical changes like internal resistance rise, electrolyte decompositions, electrodes cracking and solid electrolyte interphase (SEI) modification/growth. The aim of this research article is to study and analyse the behaviour of SEI layer growth at the anode using a novel non-invasive magnetic field probing (MFP). A 3-d model based upon well-known John Newman’s pseudo 2-d approach has been developed in COMSOL Multiphysics®. It is observed that the magnetic field response (MFR) is inversely related to SEI growth. Anode’s state of charge (SoC) response with SEI layer and MFR is also studied.

Improving Battery Safety for Electric Vehicles through the Optimization of Battery Design Parameters

Battery safety is crucial to electric vehicles (EVs). Battery degradation is closely related to battery safety. Degraded battery cells can cause potential safety issues. In order to improve battery safety, it is essential to reduce battery degradation. Battery degradation is mainly caused by side reactions, which can cause solid electrolyte interphase (SEI) layer growth. This paper aims to reduce degradation and improve battery safety by optimizing battery design parameters. The proposed framework develops a reduced-order electrochemical battery model to predict battery performance as well as SEI layer growth. Battery design parameters (i.e., electrode thickness, particle size, conductivity, and electrode porosity) are optimized to improve battery health and reduce battery capacity loss during cycling. The simulation results show that battery health has been improved from 46% to 68% and battery capacity loss has been reduced more than 22% during the first 100 cycles.

Formation and Growth Mechanisms of Solid-Electrolyte Interphase Layers in Rechargeable Batteries

Battery technology is advancing rapidly with new materials and new chemistries; however, materials stability determining battery lifetime and safety issues constitutes the main bottleneck. Electrolyte degradation processes triggered by electron transfer reactions taking place at electrode surfaces of rechargeable batteries result in multicomponent solid-electrolyte interphase (SEI) layers, recognized as the most crucial yet less well-understood phenomena impacting battery technology. Electrons flow via tunneling from the bare surface of negative electrodes during initial battery charge causing electrolyte reduction reactions that lead to SEI nucleation, but the mechanisms for further growth beyond tunneling-allowed distances are not known. Our first-principles computational studies demonstrate that radical species are responsible for the electron transfer that allows SEI layer growth once its thickness has evolved beyond the electron tunneling regime. In addition, the composition, structure, and propertie...

Aging formula for lithium ion batteries with solid electrolyte interphase layer growth

Hybrid Electric Vehicle (HEV) current profiles are dynamic, consisting of repeated charge and discharge pulses. Accurate prediction of the battery response to these inputs requires models with open circuit voltage and Butler–Volmer kinetic nonlinearities. This paper derives a nonlinear, electrolyte-enhanced, single particle model (NESPM) that includes aging due to solid electrolyte interphase layer growth. The model is validated with experimental full charge, discharge, HEV cycle, and aging data from 4.5 Ah graphite/LiFePO4 cells. The NESPM is capable of operating up to 3C constant charge–discharge cycles and up to 25C and 10 s charge–discharge pulses within 35–65% state of charge (SOC) with less than 2% error. The NESPM aging model is then simplified to obtain explicit formulas for capacity fade and impedance rise that depend on the battery parameters and current input history. The formulas show that aging increases with SOC, operating temperature, time, and root mean square (RMS) current. The formula predicts that HEV current profiles with the (i) same average SOC, (ii) small SOC swing, (iii) same operating temperature, (iv) same cycle length, and (v) same RMS current, will have the same cell capacity fade.

Differential Thermal Voltammetry for Tracking of Degradation in Lithium-Ion Batteries

Over the lifetime of a lithium-ion battery, various irreversible degradation mechanisms such as for example excessive Solid Electrolyte Interphase (SEI) layer formation and mechanical fracture of the electrodes can lead to uneven capacity loss in the cathode and anode. This can result in a stoichiometric drift effect whereby the measured cell potential may be within the safe operating range specified by the cell manufacturer but the individual electrodes are at a thermodynamically unstable regime leading to an accelerated capacity fade (Figure 1).Stoichiometric drift can be measured for individual electrodes using a reference electrode however this is not available in commercial cells. Information from Slow Rate Cyclic Voltammetry (SRCV) measurements can be used to observe stoichiometric drift when reference electrode is not present, however, this is a time consuming procedure which can take up to several hours or days to complete depending on the sweeping rate. Differential Thermal Voltammetry (DTV) has been proposed as a novel in-situ diagnosis technique to measure stoichiometric drift as a faster complement to the SRCV.DTV uses the temperature profile of the cell to infer the same data as the SRCV but more applicable to real world systems (Figure 1). The peaks in the DTV curve represent phase transformation and in carefully controlled conditions, it may be possible give an indication of the entropy changes of the individual electrodes. DTV can be completed in minutes, can easily be computed in-situ, only requires voltage and temperature measurements and does not require iso-thermal conditions.Simulations were carried out on a 1D thermally coupled electrochemical battery model with degradation modes. The cell used in this study was a 4.8 Ah lithium-ion polymer cell, with Nickel-Manganese-Cobalt oxide (NMC) based cathode and carbon/graphite anode. Results show that shifts in the location of the SRCV peaks can indicate stoichiometric drift and that the same information can be inferred through the novel in-situ diagnosis technique but at a rate of order of magnitude faster than the SRCV measurements.The simulations were experimentally validated on commercial 4.8 Ah Kokam lithium-ion polymer cells placed through various accelerated aging processes: load cycling and constant voltage storage at high and room temperatures. It can be demonstrated that different operating/storage conditions induce various degradation mechanisms in the battery. For example, a high temperature operation will promote faster SEI layer growth hence loss of cyclable lithium and increased internal resistance associated with a thicker SEI and a high C-rate cycling will induce mechanical fractures of the electrodes resulting in loss of electro-active material. Throughout the experiment, the cells were regularly analysed using Electrochemical Impedance Spectroscopy, SRCV and DTV to characterise the degradation for each type of operating conditions and to check for the validity of the novel methodology.By using the novel diagnosis technique, the stoichiometric drift of the battery can be measured sufficiently fast in order to provide useful information regarding the battery condition and to extend the battery life by reducing the operating voltage window according to stoichiometric drift of battery electrodes. Figure 1: (right) Potentials of a lithium-ion battery against stoichiometric ratios of lithiations for a carbon anode and NMC cathode. (left) Comparison of experimental SRCV and DTV results for a 4.8Ah lithium polymer Kokam cell at various stages of capacity fade.

Multiphysics modeling of lithium ion battery capacity fading process with solid-electrolyte interphase growth by elementary reaction kinetics

A pseudo two-dimensional mathematical model is developed for a lithium ion battery, integrating the elementary reaction based solid-electrolyte interphase (SEI) growth model with multiple transport processes. The model is validated using the experimental data. Simulation results indicate that the operating temperature has great effect on the SEI layer generation and growth. Under different charging–discharging rates, it is found that high charging–discharging rate can intensify the battery capacity fading process. Different cooling conditions are then applied and show that enhanced surface convective cooling condition can effectively slow down the battery capacity fading. After that, the effect of electrolyte salt concentration and exchange current density are studied. It is found that raising the electrolyte salt concentration can improve the diffusion property of lithium ions, and stabilize the battery performance under lithium ion consumption induced resistance rising. It also suggests that improving exchange current density could greatly decrease the lithium ion battery capacity fading.