Publications
180 results found
Kirkaldy N, Samieian MA, Offer GJ, et al., 2024, Lithium-ion battery degradation: Comprehensive cycle ageing data and analysis for commercial 21700 cells, Journal of Power Sources, Vol: 603, ISSN: 0378-7753
High quality open-source battery data is in short supply and high demand. Researchers from academia and industry rely on experimental data for parameterisation and validation of battery models, but experimental data can be expensive and time consuming to acquire, and difficult to analyse without expert knowledge. Here we present a comprehensive open-source dataset for the cycle ageing of a commercially relevant lithium-ion cell (LG M50T 21700) with an NMC811 cathode and C/SiOx composite anode. 40 cells were cycled over 15 different operating conditions of temperature and state of charge, accumulating a total of around 33,000 equivalent full cycles. Analysis of the ageing behaviour includes metrics such as capacity fade, resistance increase, and degradation mode analysis. The presentation of the dataset here is complemented by a statistical analysis of the cell performance, both at beginning of life and as a function of age. This provides a valuable resource for those working on battery performance and ageing.
Ruan H, Kirkaldy N, Offer G, et al., 2024, Diagnosing health in composite battery electrodes with explainable deep learning and partial charging data, Energy and AI, Vol: 16, ISSN: 2666-5468
Lithium-ion batteries with composite anodes of graphite and silicon are increasingly being used. However, their degradation pathways are complicated due to the blended nature of the electrodes, with graphite and silicon degrading at different rates. Here, we develop a deep learning health diagnostic framework to rapidly quantify and separate the different degradation rates of graphite and silicon in composite anodes using partial charging data. The convolutional neural network (CNN), trained with synthetic data, uses experimental partial charging data to diagnose electrode-level health of tested batteries, with errors of less than 3.1% (corresponding to the loss of active material reaching ∼75%). Sensitivity analysis of the capacity-voltage curve under different degradation modes is performed to provide a physically informed voltage window for diagnostics with partial charging data. By using the gradient-weighted class activation mapping approach, we provide explainable insights into how these CNNs work; highlighting regions of the voltage-curve to which they are most sensitive. Robustness is validated by introducing noise to the data, with no significant negative impact on the diagnostic accuracy for noise levels below 10 mV, thus highlighting the potential for deep learning approaches in the diagnostics of lithium-ion battery performance under real-world conditions. The framework presented here can be generalised to other cell formats and chemistries, providing robust and explainable battery diagnostics for both conventional single material electrodes, but also the more challenging composite electrodes.
Kallitsis E, Lindsay JJ, Chordia M, et al., 2024, Think global act local: The dependency of global lithium-ion battery emissions on production location and material sources, Journal of Cleaner Production, Vol: 449, ISSN: 0959-6526
The pursuit of low-carbon transport has significantly increased demand for lithium-ion batteries. However, the rapid increase in battery manufacturing, without adequate consideration of the carbon emissions associated with their production and material demands, poses the threat of shifting the bulk of emissions upstream. In this article, a life cycle assessment (LCA) model is developed to account for the cradle-to-gate carbon footprint of lithium-ion batteries across 26 Chinese provinces, 20 North American locations and 19 countries in Europe and Asia. Analysis of published LCA data reveals significant uncertainty associated with the carbon emissions of key battery materials; their overall contribution to the carbon footprint of a LIB varies by a factor of ca. 4 depending on production route and source. The links between production location and the gate-to-gate carbon footprint of battery manufacturing are explored, with predicted median values ranging between 0.1 and 69.5 kg CO2-eq kWh−1. Leading western-world battery manufacturing locations in the US and Europe, such as Kentucky and Poland are found to have comparable carbon emissions to Chinese rivals, even exceeding the carbon emissions of battery manufacturing in several Chinese provinces. Such resolution on material and energy contributions to the carbon footprint of LIBs is essential to inform policy- and decision-making to minimise the carbon emissions of the battery value chain. Given the current status quo, the global carbon footprint of the lithium-ion battery industry is projected to reach up to 1.0 Gt CO2-eq per year within the next decade. With material supply chain decarbonisation and energy savings in battery manufacturing, a lower estimate of 0.5 Gt CO2-eq per year is possible.
Li R, O'Kane S, Huang J, et al., 2024, A million cycles in a day: Enabling high-throughput computing of lithium-ion battery degradation with physics-based models, Journal of Power Sources, Vol: 598, ISSN: 0378-7753
High-throughput computing (HTC) is a pivotal asset in many scientific fields, such as biology, material science and machine learning. Applying HTC to the complex physics-based degradation models of lithium-ion batteries enables efficient parameter identification and sensitivity analysis, which further leads to optimal battery designs and operating conditions. However, running physics-based degradation models comes with pitfalls, as solvers can crash or get stuck in infinite loops due to numerical errors. Also, how to pipeline HTC for degradation models has seldom been discussed. To fill these gaps, we have created ParaSweeper, a Python script tailored for HTC, designed to streamline parameter sweeping by running as many ageing simulations as computational resources allow, each with different parameters. We have demonstrated the capability of ParaSweeper based on the open-source platform PyBaMM, and the approach can also apply to other numerical models which solve partial differential equations. ParaSweeper not only manages common solver errors, but also integrates various methods to accelerate the simulation. Using a high-performance computing platform, ParaSweeper can run millions of charge/discharge cycles within one day. ParaSweeper stands to benefit both academic researchers, through expedited model exploration, and industry professionals, by enabling rapid lifetime design, ultimately contributing to the prolonged lifetime of batteries.
Li Y, Gao X, Wang H, et al., 2024, Direct venting during fast charging of lithium-ion batteries, Journal of Power Sources, Vol: 592, ISSN: 0378-7753
Lithium-ion batteries pose high risks of failure when subjected to fast charging due to accumulated degradation from side reactions. Venting is a common failure behaviour that results in the release of gases and depressurization. However, the connection between fast-charging degradation and venting characteristics remains unclear. In this study, fast-charging experiments are conducted on LiNi0.6Mn0.2Co0.2O2 (NMC622)/graphite prismatic cells (51 Ah) with controlled cooling, followed by adiabatic thermal runaway tests. The degraded cell, after 4C charging, shows venting at a temperature 34.4 °C lower than a fresh cell. Gas analysis of the degraded anode-electrolyte partially reactive system in hot-box tests reveals that the reaction between plated lithium and electrolyte was a primary contributor to the additional gases. The fast-charging protocols are conducted under natural convection with less heat dissipation, causing battery swelling and venting without thermal runaway when subjected to excessive cycling at off-limit charge rates (5C and 5.6C). The temperature decreasing rates during rest after each charging process slow down or stabilize for a certain period, highlighting the role of exothermic side reactions. This experimentally demonstrates that venting failures can be directly triggered by the exothermic, gas generating reaction during fast charging. These findings inform future designs for safe and rapid battery charging.
Roy T, Goel S, Costa LT, et al., 2023, Strain induced electrochemical behaviors of ionic liquid electrolytes in an electrochemical double layer capacitor: Insights from molecular dynamics simulations., J Chem Phys, Vol: 159
Electrochemical Double Layer Capacitors (EDLCs) with ionic liquid electrolytes outperform conventional ones using aqueous and organic electrolytes in energy density and safety. However, understanding the electrochemical behaviors of ionic liquid electrolytes under compressive/tensile strain is essential for the design of flexible EDLCs as well as normal EDLCs, which are subject to external forces during assembly. Despite many experimental studies, the compression/stretching effects on the performance of ionic liquid EDLCs remain inconclusive and controversial. In addition, there is hardly any evidence of prior theoretical work done in this area, which makes the literature on this topic scarce. Herein, for the first time, we developed an atomistic model to study the processes underlying the electrochemical behaviors of ionic liquids in an EDLC under strain. Constant potential non-equilibrium molecular dynamics simulations are conducted for EMIM BF4 placed between two graphene walls as electrodes. Compared to zero strain, low compression of the EDLC resulted in compromised performance as the electrode charge density dropped by 29%, and the performance reduction deteriorated significantly with a further increase in compression. In contrast, stretching is found to enhance the performance by increasing the charge storage in the electrodes by 7%. The performance changes with compression and stretching are due to changes in the double-layer structure. In addition, an increase in the value of the applied potential during the application of strain leads to capacity retention with compression revealed by the newly performed simulations.
Li R, O'Kane SEJ, Wang A, et al., 2023, Effect of Solvent Segregation on the Performance of Lithium-Ion Batteries, ECS Meeting Abstracts, Vol: MA2023-02, Pages: 975-975
<jats:p> The pseudo two-dimensional (P2D) model is one of the most powerful tools in modelling lithium-ion batteries (LIBs) <jats:sup>1</jats:sup>, in that it can describe the complex electrochemical and thermal behaviours of LIBs with high fidelity yet maintain relatively high computing efficiency. To achieve that, many assumptions have been made, one of which is the single solvent assumption. However, most electrolytes used in LIBs uses multiple solvents to balance the requirements of conductivity, diffusivity and viscosity <jats:sup>2</jats:sup>. Therefore, the single solvent assumption indicates that all solvents move as a single entity.</jats:p> <jats:p>However, previous experimental studies have shown that Li<jats:sup>+</jats:sup> preferentially attracts cyclic carbonates (like ethylene carbonate, EC) rather than linear carbonates (such as ethyl-methyl carbonate, EMC) to form ion-solvent clusters <jats:sup>3</jats:sup>. During charge/discharge, ion-solvent clusters move between the positive and negative electrodes to constitute ionic current. At the electrolyte-electrolyte interface, Li<jats:sup>+</jats:sup> de-solvates from the clusters and intercalates into the electrode, or vice versa. Such process will induce concentration gradients of both solvents and lithium ions; the solvent concentration has been ignored in the P2D model. The simplification means the current P2D model fails to capture two important phenomena: (1) many electrolyte properties - including conductivity, diffusivity, and thermodynamic factors - are sensitive to the solvent concentration <jats:sup>4</jats:sup>; (2) the solvent components in the ion-solvent clusters are preferentially consumed by interfacial side reactions such as the growth of solid-electrolyte interface (SEI) <jats:sup>3</jats:sup>.</jats:p> <jats:p>To fill this gap, we add an extr
Gao X, Li Y, Offer GJ, et al., 2023, Battery Venting Caused By Fast Charging, ECS Meeting Abstracts, Vol: MA2023-02, Pages: 498-498
<jats:p> Lithium-ion batteries (LIBs) experience high risks of failure during unreasonable fast charging. Various degradation mechanisms inside the LIBs such as lithium (Li) plating, solid electrolyte interphase growth and electrolyte dry-out can undermine the electrochemical performance and induce massive gas generation alongside the operation. As a typical failure behaviour, venting occurs when the internal pressure of battery cell exceeds the safety threshold, releasing the gaseous products as well as depressurizing the cell. Recent studies<jats:sup>1–3</jats:sup> of thermal runaway (TR) tests after fast charging have found that accumulated plated Li can react with electrolyte at elevated external temperatures, decreasing both self-heating and onset temperatures of TR. Yet, how fast-charging degradation will affect battery venting behaviours remains unclear.</jats:p> <jats:p>To answer this question, in this study, a series of fast charging experiments under controlled cooling as well as adiabatic TR tests were conducted with 51 Ah LiNi<jats:sub>0.6</jats:sub>Mn<jats:sub>0.2</jats:sub>Co<jats:sub>0.2</jats:sub>O<jats:sub>2</jats:sub>/graphite prismatic LIBs. The results showed that the prismatic battery underwent severe Li plating with over 30% capacity fade after 10 cycles of 4C charging. In the adiabatic TR tests, the aged batteries after 4C charging exhibited lower self-heating temperature and venting temperature as compared to the fresh batteries, by 51 ℃ and 34.4 ℃ respectively. This can be explained by the additional gas generation from the reaction between plated Li and electrolyte in the fast-charged batteries. Gas analyses of 120 ℃ hot-box tests for the degraded anodes with the electrolyte showed that the vented gas at the early venting stage primarily consisted of carbon dioxide, carbon monoxide and ethylene. The same charging protocols were then conducted
White G, Hales A, Offer GJ, et al., 2023, (Invited) Methods for the Parameterisation of Battery Thermal Models, ECS Meeting Abstracts, Vol: MA2023-02, Pages: 974-974
<jats:p> Thermal properties are fundamental parameters in every battery cell model. They govern how heat moves through the cell or dissipates once it has been produced. Modelling the movement of heat in batteries is essential for safety and also for accurate predictions of temperature. Electrical/electrochemical models of the cell are highly sensitive to temperature making accurate thermal properties an essential requirement. However, measuring these properties is extremely difficult due to the complex structure inside a cell. Previous measurement methods suffered from fundamental flaws and often battery thermal models are either over simplified or overly complex. This presentation will present the challenges faced before novel methods are presented which address this. This includes a novel method developed for measuring thermal conductivity which uses state-of-the-art heat flux sensors to reduce errors from up to 50% down to 5.6%. These novel methods represent the future for thermal parameterisation of lithium-ion batteries which will lead to accurate electrical/electrochemical models and improved thermal safety.</jats:p> <jats:p> <jats:inline-formula> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="974fig1.jpg" xlink:type="simple" /> </jats:inline-formula> </jats:p> <jats:p>Figure 1</jats:p> <jats:p />
Offer GJ, Li S, Zhang C, et al., 2023, Inhomogeneous Degradation in Lithium-Ion Batteries: The Effect of Thermal Gradients, ECS Meeting Abstracts, Vol: MA2023-02, Pages: 3353-3353
<jats:p> Understanding lithium ion battery degradation is a consequence of multiple, tightly coupled and non-linear degradation mechanisms. The interplay between these degradation mechanisms, and how the cell is used, gives rise to path dependent behaviour, and hence data driven approaches to model behaviour and predict lifetime rapidly become prohibitively expensive. Therefore, a physics based approach to model degradation is desirable.</jats:p> <jats:p>In addition, all of the degradation mechanisms are a function of temperature, which adds another variable to the path dependency. To make matters worse, all cells experience internal thermal gradients during operation, which means the path dependency for different regions within a battery will be different. This leads to inhomogeneous degradation. After a few cycles, the degradation pathway of each region will then be affected not just by the thermal gradients and local current density but also by the state-of-health of that region, leading to complicated emergent behaviour.</jats:p> <jats:p>Solving a physics based model with multiple degradation mechanisms, in a detailed 3-dimensional thermally coupled discretised model is also prohibitively expensive. Therefore, in this paper we present a thermally coupled distributed equivalent circuit model, with degradation functions built in, so each node can degrade at different rates, as a function of the operating conditions at that node. We have reproduced experimental data previously published, showing the effect of thermal gradients on degradation for two different cooling strategies for a tab and surface cooled pouch cell. For the first time reproducing the positive feedback mechanism responsible for accelerated degradation for surface cooling.</jats:p> <jats:p>The results of this work show that thermal gradients cannot and should not be ignored, and degradation models that do not take
Hales A, Offer GJ, Marzook WWJ, et al., 2023, (Keynote) Thermal Performance Optimisation at Cell Level, to Achieve Better, Longer Lasting Battery Packs, ECS Meeting Abstracts, Vol: MA2023-02, Pages: 953-953
<jats:p> Temperature is a major issue in the operation of lithium-ion batteries, with both high and low temperatures causing problems. Cold batteries are inefficient, while hot batteries are at risk of thermal runaway and fire, making it crucial to maintain a safe and optimal temperature range. Temperature gradients can negatively impact battery performance, reducing accessible energy and increasing the degradation rate. This is a critical issue for electric vehicles (EVs), which can experience reduced driving range and deteriorating performance over time.</jats:p> <jats:p>Despite these challenges, current lithium-ion cell designs prioritize maximizing specific energy, which can negatively impact thermal performance. Thermal management systems are used to extract heat from poorly designed cells, but they are a significant parasitic load, demanding on average 8 kW in typical operation. Further, they can introduce uneven distribution of current throughout the battery pack, leading to diminished performance and accelerated degradation. The limited performance of these systems contributes towards range anxiety, which is a major barrier to the widespread adoption of electric vehicles in the UK, Europe, and the USA.</jats:p> <jats:p>To address these challenges, the authors propose the use of a new metric, the cell cooling coefficient (CCC). The CCC is a constant for a given cell and thermal management method (e.g. surface cooling or tab cooling), and is measured in W.K-1 (the reciprocal of thermal resistance). The CCC define a cell's ability to reject heat energy. The CCC is defined as the temperature gradient across a cell in idealized operating conditions, normalized against the heat generation rate in the same conditions. This allows for the comparison of geometrically dissimilar cells and can be used to optimize the thermal performance of lithium-ion cells.</jats:p> <jats:p>Experimen
Bonkile MP, Jiang Y, Kirkaldy N, et al., 2023, Coupled electrochemical-thermal-mechanical stress modelling in composite silicon/graphite lithium-ion battery electrodes, Journal of Energy Storage, Vol: 73, ISSN: 2352-152X
Silicon is often added to graphite battery electrodes to enhance the electrode-specific capacity, but it undergoes significant volume changes during (de)lithiation, which results in mechanical stress, fracture, and performance degradation. To develop long-lasting and energy-dense batteries, it is critical to understand the non-linear stress behaviour in composite silicon-graphite electrodes. In this study, we developed a coupled electrochemical-thermal-mechanical model of a composite silicon/graphite electrode in PyBaMM (an open-source physics-based modelling platform). The model is experimentally validated against a commercially available LGM50T battery, and the effects of C-rates, depth-of-discharge (DoD), and temperature are investigated. The developed model can reproduce the voltage hysteresis from the silicon and provide insights into the stress response and crack growth/propagation in the two different phases. The stress in the silicon is relatively low at low DoD but rapidly increases at a DoD >~80%, whereas the stress in the graphite increases with decreasing temperature and DoD. At higher C-rates, peak stress in the graphite increases as expected, however, this decreases for silicon due to voltage cut-offs being hit earlier, leading to lower active material utilisation since silicon is mostly active at high DoD. Therefore, this work provides an improved understanding of stress evolution in composite silicon/graphite lithium-ion batteries.
Li S, Marzook MW, Zhang C, et al., 2023, How to enable large format 4680 cylindrical lithium-ion batteries, Applied Energy, Vol: 349, Pages: 1-13, ISSN: 0306-2619
The demand for large format lithium-ion batteries is increasing, because they can be integrated and controlled easier at a system level. However, increasing the size leads to increased heat generation risking overheating. 1865 and 2170 cylindrical cells can be both base cooled or side cooled with reasonable efficiency. Large format 4680 cylindrical cells have become popular after Tesla filed a patent. If these cells are to become widely used, then understanding how to thermally manage them is essential. In this work, we create a model of a 4680 cylindrical cell, and use it to study different thermal management options. Our work elucidates the comprehensive mechanisms how the hot topic ‘tabless design’ improves the performance of 4680 cell and makes any larger format cell possible while current commercial cylindrical cells cannot be simply scaled up to satisfy power and thermal performance. As a consequence, the model identifies the reason for the tabless cell's release: the thermal performance of the 4680 tabless cell can be no worse than that of the 2170 cell, while the 4680 tabless tab cell boasts 5.4 times the energy and 6.9 times the power. Finally, via the model, a procedure is proposed for choosing the thermal management for large format cylindrical cell for maximum performance. As an example, we demonstrate that the best cooling approach for the 4680 tabless cell is base cooling, while for the 2170 LG M50T cell it is side cooling. We conclude that any viable large format cylindrical cell must include a continuous tab (or ‘tabless’) design and be cooled through its base when in a pack. The results are of immediate interest to both cell manufacturers and battery pack designers, while the developed modelling and parameterization framework is of wider use for all energy storage system design.
Li S, Zhang C, Zhao Y, et al., 2023, Effect of thermal gradients on inhomogeneous degradation in lithium-ion batteries, Communications Engineering, Vol: 2, ISSN: 2731-3395
Understanding lithium-ion battery degradation is critical to unlocking their full potential. Poor understanding leads to reduced energy and power density due to over-engineering, or conversely to increased safety risks and failure rates. Thermal management is neces-sary for all large battery packs, yet experimental studies have shown that the effect of thermal management on degradation is not understood sufficiently. Here we investigated the effect of thermal gradients on inhomogeneous degradation using a val-idated three-dimensional electro-thermal-degradation model. We have reproduced the effect of thermal gradients on degradation by running a distributed model over hundreds of cycles within hours and reproduced the positive feedback mechanism responsible for the accelerated rate of degradation. Thermal gradients of just 3 °C within the active re-gion of a cell produced sufficient positive feedback to accelerate battery degradation by 300%. Here we show that the effects of inhomogeneous temperature and currents on degradation cannot and should not be ignored. Most attempts to reproduce realistic cell level degradation based upon a lumped model (i.e. no thermal gradients) have suffered from significant overfitting, leading to incorrect conclusions on the rate of degradation.
Ruan H, Barreras JV, Steinhardt M, et al., 2023, The heating triangle: A quantitative review of self-heating methods for lithium-ion batteries at low temperatures, Journal of Power Sources, Vol: 581, Pages: 1-16, ISSN: 0378-7753
Lithium-ion batteries at low temperatures have slow recharge times alongside reduced available power and energy. Battery heating is a viable way to address this issue, and self-heating techniques are appealing due to acceptable efficiency and speed. However, there are a lack of studies quantitatively comparing self-heating methods rather than qualitatively, because of the existence of many different batteries with varied heating parameters. In this work, we review the current state-of-the-art self-heating methods and propose the heating triangle as a new quantitative indicator for comparing self-heating methods, towards identifying/developing effective heating approaches. We define the heating triangle which considers three fundamental metrics: the specific heating rate (°C·g·J−1), coefficient of performance (COP) (−), and specific temperature difference (°C·hr), enabling a quantitative assessment of self-heating methods using data reported in the literature. Our analysis demonstrates that very similar metrics are observed for the same type of self-heating method, irrespective of the study case, supporting the universality of the proposed indicator. With the comparison insights, we identify research gaps and new avenues for developing advanced self-heating methods. This work demonstrates the value of the proposed heating triangle as a standardised approach to compare heating methods and drive innovation.
Vadhva P, Boyce AM, Patel A, et al., 2023, Silicon-Based Solid-State Batteries: Electrochemistry and Mechanics to Guide Design and Operation., ACS Appl Mater Interfaces, Vol: 15, Pages: 42470-42480
Solid-state batteries (SSBs) are promising alternatives to the incumbent lithium-ion technology; however, they face a unique set of challenges that must be overcome to enable their widespread adoption. These challenges include solid-solid interfaces that are highly resistive, with slow kinetics, and a tendency to form interfacial voids causing diminished cycle life due to fracture and delamination. This modeling study probes the evolution of stresses at the solid electrolyte (SE) solid-solid interfaces, by linking the chemical and mechanical material properties to their electrochemical response, which can be used as a guide to optimize the design and manufacture of silicon (Si) based SSBs. A thin-film solid-state battery consisting of an amorphous Si negative electrode (NE) is studied, which exerts compressive stress on the SE, caused by the lithiation-induced expansion of the Si. By using a 2D chemo-mechanical model, continuum scale simulations are used to probe the effect of applied pressure and C-rate on the stress-strain response of the cell and their impacts on the overall cell capacity. A complex concentration gradient is generated within the Si electrode due to slow diffusion of Li through Si, which leads to localized strains. To reduce the interfacial stress and strain at 100% SOC, operation at moderate C-rates with low applied pressure is desirable. Alternatively, the mechanical properties of the SE could be tailored to optimize cell performance. To reduce Si stress, a SE with a moderate Young's modulus similar to that of lithium phosphorous oxynitride (∼77 GPa) with a low yield strength comparable to sulfides (∼0.67 GPa) should be selected. However, if the reduction in SE stress is of greater concern, then a compliant Young's modulus (∼29 GPa) with a moderate yield strength (1-3 GPa) should be targeted. This study emphasizes the need for SE material selection and the consideration of other cell components in order to optimize the performance of
Wu B, Ai W, Kirkaldy N, et al., 2023, (Invited) Multi-Scale Battery Modelling: Understanding Coupled Electrochemical and Mechanical Effects, ECS Meeting Abstracts, Vol: MA2023-01, Pages: 1634-1634
<jats:p> Lithium-ion batteries are a key enabler for a low-carbon future, however their performance and lifetime are influenced by complex and coupled electrochemical, thermal and mechanical factors across different length and time scales. In this talk, we explore the key degradation modes which limit battery lifetime and how multi-scale models can help describe these effects towards improved cell designs and device control. At the particle level, we explore how phase field fatigue models of cathode particles can be used to understand crack growth, leading to loss of active material [1]. Here, non-linear crack growth is observed due to the fatigue of material properties and crack merger, leading to a transition from slow to rapid crack growth rate. Use of these models can identify critical C-rates and particle sizes which mitigate cracking.</jats:p> <jats:p>At the continuum scale, we then investigate how these stresses evolve during cycling, with stress heterogeneities arising initially at the electrode-separator interface, but later propagating to the electrode-current collector interface [2]. We then extend this study to composite anodes of graphite and silicon, where highly non-linear behaviour is observed [3]. Here, the graphite phase provides the majority of the reaction current density at high state-of-charge operation, with this then shifting to the silicon phase at low state-of-charge operation, with hysteresis effects observed due to the silicon. This behaviour is attributed mostly to the different open circuit potentials of the two different phases. Finally, we explore how these effects propagate to the battery pack scale and highlight the divergence of material level performance from their real-world implementation [4].</jats:p> <jats:p>References</jats:p> <jats:p>[1] A coupled phase field formulation for modelling fatigue cracking in lithium-ion battery electrode partic
Zhuo M, Kirkaldy N, Maull T, et al., 2023, Diffusion-aware voltage source: An equivalent circuit network to resolve lithium concentration gradients in active particles, APPLIED ENERGY, Vol: 339, ISSN: 0306-2619
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Zhuo M, Offer G, Marinescu M, 2023, Degradation model of high-nickel positive electrodes: Effects of loss of active material and cyclable lithium on capacity fade, Journal of Power Sources, Vol: 556, Pages: 1-16, ISSN: 0378-7753
Nickel-rich layered oxides have been widely used as positive electrode materials for high-energy-density lithium-ion batteries, but the underlying mechanisms of their degradation have not been well understood. Here we present a model at the particle level to describe the structural degradation caused by phase transition in terms of loss of active material (LAM), loss of lithium inventory (LLI), and resistance increase. The particle degradation model is then incorporated into a cell-level P2D model to explore the effects of LAM and LLI on capacity fade in cyclic ageing tests. It is predicted that the loss of cyclable lithium (trapped in the degraded shell) leads to a shift in the stoichiometry range of the negative electrode but does not directly contribute to the capacity loss, and that the loss of positive electrode active materials dominates the fade of usable cell capacity in discharge. The available capacity at a given current rate is further decreased by the additional resistance of the degraded shell layer. The change pattern of the state-of-charge curve provides information of more dimensions than the conventional capacity-fade curve, beneficial to the diagnosis of degradation modes. The model has been implemented into PyBaMM and the source codes are openly available in the GitHub repository https://github.com/mzzhuo/PyBaMM/tree/pe_degradation.
Lander L, Tagnon C, Nguyen-Tien V, et al., 2023, Breaking it down: A techno-economic assessment of the impact of battery pack design on disassembly costs, Applied Energy, Vol: 331, Pages: 1-9, ISSN: 0306-2619
The electrification of the transport sector is a critical part of the net-zero transition. The mass adoption of electric vehicles (EVs) powered by lithium-ion batteries in the coming decade will inevitably lead to a large amount of battery waste, which needs handling in a safe and environmentally friendly manner. Battery recycling is a sustainable treatment option at the battery end-of-life that supports a circular economy. However, heterogeneity in pack designs across battery manufacturers are hampering the establishment of an efficient disassembly process, hence making recycling less viable. A comprehensive techno-economic assessment of the disassembly process was conducted, which identified cost hotspots in battery pack designs and to guide design optimisation strategies that help save time and cost for end-of-life treatment. The analyses include six commercially available EV battery packs: Renault Zoe, Nissan Leaf, Tesla Model 3, Peugeot 208, BAIC and BYD Han. The BAIC and BYD battery packs exhibit lower disassembly costs (US$50.45 and US$47.41 per pack, respectively), compared to the Peugeot 208 and Nissan Leaf (US$186.35 and US$194.11 per pack, respectively). This variation in disassembly cost is due mostly to the substantial differences in number of modules and fasteners. The economic assessment suggests that full automation is required to make disassembly viable by 2040, as it could boost disassembly capacity by up to 600 %, while substantially achieving cost savings of up to US$190 M per year.
Jiang Y, Zhang L, Offer G, et al., 2022, A user-friendly lithium battery simulator based on open-source CFD, Digital Chemical Engineering, Vol: 5, Pages: 1-14, ISSN: 2772-5081
The growing use of lithium-ion batteries (LIBs) for automotive and stationary storage applications has put increasingly stringent requirements on battery thermal management and battery safety. An open-source platform that can bridge battery electrochemical models and computational fluid dynamics (CFD) can be of great benefit for designing advanced battery thermal management systems and safety countermeasures by allowing the simulation and prediction of battery responses to various thermofluidic environments and thermal boundaries. Here we develop a user-friendly battery simulator based on the open-source CFD code OpenFOAM. The simulator contains the in-house solvers for the two mostly used physics-based battery models, the single particle model, and the pseudo-two-dimensional model. GUIs are also developed based on Qt for simulation automation and ease of use. To demonstrate the functionality of the developed simulator, the electrochemical performance and internal states of half LIB cells and full LIB cells with different chemistries at different operating conditions are simulated. The obtained results agree well with other existing battery simulators. Due to its native integration with OpenFOAM, the new battery simulator is readily extendable to incorporate various CFD models and other physics to meet the simulation needs of thermal management and safety design for LIBs.
Kirkaldy N, Samieian MA, Offer GJ, et al., 2022, Lithium-ion battery degradation: measuring rapid loss of active silicon in silicon-graphite composite electrodes, ACS Applied Energy Materials, Vol: 5, Pages: 13367-13376, ISSN: 2574-0962
To increase the specific energy of commercial lithium-ion batteries, silicon is often blended into the graphite negative electrode. However, due to large volumetric expansion of silicon upon lithiation, these silicon–graphite (Si–Gr) composites are prone to faster rates of degradation than conventional graphite electrodes. Understanding the effect of this difference is key to controlling degradation and improving cell lifetimes. Here, the effects of state-of-charge and temperature on the aging of a commercial cylindrical cell with a Si–Gr electrode (LG M50T) are investigated. The use of degradation mode analysis enables quantification of separate rates of degradation for silicon and graphite and requires only simple in situ electrochemical data, removing the need for destructive cell teardown analyses. Loss of active silicon is shown to be worse than graphite under all operating conditions, especially at low state-of-charge and high temperature. Cycling the cell over 0–30% state-of-charge at 40 °C resulted in an 80% loss in silicon capacity after 4 kA h of charge throughput (∼400 equiv full cycles) compared to just a 10% loss in graphite capacity. The results indicate that the additional capacity conferred by silicon comes at the expense of reduced lifetime. Conversely, reducing the utilization of silicon by limiting the depth-of-discharge of cells containing Si–Gr will extend their lifetime. The degradation mode analysis methods described here provide valuable insight into the causes of cell aging by separately quantifying capacity loss for the two active materials in the composite electrode. These methods provide a suitable framework for any experimental investigations involving composite electrodes.
Xie Y, Hales A, Li R, et al., 2022, Thermal management optimization for large-format lithium-ion battery using cell cooling coefficient, Journal of The Electrochemical Society, Vol: 169, Pages: 1-10, ISSN: 0013-4651
The surface cooling technology of power battery pack has led to undesired temperature gradient across the cell during thermal management and the tab cooling has been proposed as a promising solution. This paper investigates the feasibility of applying tab cooling in large-format lithium-ion pouch cells using the Cell Cooling Coefficient (CCC). A fundamental problem with tab cooling is highlighted, the CCC for tab cooling decreases as capacity increases. Coupling low CCCs with greater heat generation leads to significant temperature gradients across the cell. Here, the "bottleneck" that limits heat rejection through the tabs is evaluated. The thermal resistance of the physical tabs is identified to be the main contributor towards the poor heat rejection pathway. A numerical thermal model is used to explore the effect of increased tab thickness and results showed that the cell-wide temperature gradients could be significantly reduced. At the negative tab, increasing from 0.2 mm to 2 mm led to a 100% increase in CCCneg whilst increasing the positive tab from 0.45 mm to 2 mm led to an 82% increasing in CCCpos. Together, this is shown to contribute to a 51% reduction in temperature gradient across the cell in any instance of operation.
Vadhva P, Boyce AM, Hales A, et al., 2022, Towards optimised cell design of thin film silicon-based solid-state batteries via modelling and experimental characterisation, Journal of The Electrochemical Society, Vol: 169, Pages: 1-11, ISSN: 0013-4651
To realise the promise of solid-state batteries, negative electrode materials exhibiting large volumetric expansions, such as Li and Si, must be used. These volume changes can cause significant mechanical stresses and strains that affect cell performance and durability, however their role and nature in SSBs are poorly understood. Here, a 2D electro-chemo-mechanical model is constructed and experimentally validated using steady-state, transient and pulsed electrochemical methods. The model geometry is taken as a representative cross-section of a non-porous, thin-film solid-state battery with an amorphous Si (a-Si) negative electrode, lithium phosphorous oxynitride (LiPON) solid electrolyte and LiCoO2 (LCO) positive electrode. A viscoplastic model is used to predict the build-up of strains and plastic deformation of a-Si as a result of (de)lithiation during cycling. A suite of electrochemical tests, including electrochemical impedance spectroscopy, the galvanostatic intermittent titration technique and hybrid pulse power characterisation are carried out to establish key parameters for model validation. The validated model is used to explore the peak interfacial (a-Si∣LiPON) stress and strain as a function of the relative electrode thickness (up to a factor of 4), revealing a peak volumetric expansion from 69% to 104% during cycling at 1C. The validation of this electro-chemo-mechanical model under load and pulsed operating conditions will aid in the cell design and optimisation of solid-state battery technologies.
Marzook MW, Hales A, Patel Y, et al., 2022, Thermal evaluation of lithium-ion batteries: Defining the cylindrical cell cooling coefficient, Journal of Energy Storage, Vol: 54, Pages: 1-9, ISSN: 2352-152X
Managing temperatures of lithium-ion cells in battery packs is crucial to ensuring their safe operation. However, thermal information provided on typical cell datasheets is insufficient to identify which cells can be easily thermally managed. The Cell Cooling Coefficient (CCC) aims to fill this gap, as a metric that defines the thermal dissipation from a cell when rejecting its own heat. While the CCC has been defined and used for pouch cells, no similar measure has been proven for cylindrical cells. This work successfully defines and measures the CCC for cylindrical cells under base cooling (CCCBase), defined as the heat rejected through the base divided by the temperature difference from the base to positive cap. Using a non-standard, electrically optimised connection, the maxima for CCCBase of an LG M50T (21700) and Samsung 30Q (18650) cell are successfully measured to be 0.139 and 0.115 W K−1, respectively. Even though the 21700 has a higher CCCBase, indicating that the cell can be cooled more efficiently, comparing the CCCBase per area the 18650 can reject 13 % more heat for a given cooled area. A worked example demonstrates the equal importance of understanding heat generation alongside the CCC, for both cell design and down selecting cells.
Samieian MA, Garcia CE, Bravo Diaz L, et al., 2022, Large scale immersion bath for isothermal testing of lithium-ion cells, HardwareX, Vol: 12, Pages: 1-15, ISSN: 2468-0672
Testing of lithium-ion batteries depends greatly on accurate temperature control in order to generate reliable experimental data. Reliable data is essential to parameterise and validate battery models, which are essential to speed up and reduce the cost of battery pack design for multiple applications. There are many methods to control the temperature of cells during testing, such as forced air convection, liquid cooling or conduction cooling using cooling plates. Depending on the size and number of cells, conduction cooling can be a complex and costly option. Although easier to implement, forced air cooling is not very effective and can introduce significant errors if used for battery model parametrisation. Existing commercially available immersion baths are not cost effective (∼£3320) and are usually too small to hold even one large pouch cell. Here, we describe an affordable but effective cooling method using immersion cooling. This bath is designed to house eight large lithium-ion pouch cells (300mm x 350mm), each immersed in a base oil cooling fluid (150L total volume). The total cost of this setup is only £1670. The rig is constructed using a heater, chilling unit, and a series of pumps. This immersion bath can maintain a temperature within 0.5 °C of the desired set point, it is operational within the temperature range 5 – 55 °C and has been validated at a temperature range of 25 – 45 °C.
Xie Y, Wang S, Li R, et al., 2022, Inhomogeneous degradation induced by lithium plating in a large-format lithium-ion battery, JOURNAL OF POWER SOURCES, Vol: 542, ISSN: 0378-7753
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White G, Hales A, Patel Y, et al., 2022, Novel methods for measuring the thermal diffusivity and the thermal conductivity of a lithium-ion battery, APPLIED THERMAL ENGINEERING, Vol: 212, Pages: 1-12, ISSN: 1359-4311
Thermal conductivity is a fundamental parameter in every battery pack model. It allows for the calculation of internal temperature gradients which affect cell safety and cell degradation. The accuracy of the measurement for thermal conductivity is directly proportional to the accuracy of any thermal calculation. Currently the battery industry uses archaic methods for measuring this property which have errors up to 50 %. This includes the constituent material approach, the Searle’s bar method, laser/Xeon flash and the transient plane source method. In this paper we detail three novel methods for measuring both the thermal conductivity and the thermal diffusivity to within 5.6 %. These have been specifically designed for bodies like lithium-ion batteries which are encased in a thermally conductive material. The novelty in these methods comes from maintaining a symmetrical thermal boundary condition about the middle of the cell. By using symmetric boundary conditions, the thermal pathway around the cell casing can be significantly reduced, leading to improved measurement accuracy. These novel methods represent the future for thermal characterisation of lithium-ion batteries. Continuing to use flawed measurement methods will only diminish the performance of battery packs and slow the rate of decarbonisation in the transport sector.
Tomaszewska A, Doel R, Parkes M, et al., 2022, Investigating Li Plating Distribution Caused By a Thermal Gradient through Modelling, Differential Voltage, and Post-Mortem Analysis, ECS Meeting Abstracts, Vol: MA2022-01, Pages: 186-186
<jats:p> Relatively slow charging speeds are often quoted as a key barrier to customer acceptance of EVs. Currently, the charging rates are limited primarily by the risk of lithium plating. While traditionally lithium plating has been associated with low temperature charging, recent reports point to the fact that thermal heterogeneity can significantly affect the plating behaviour, sometimes making it more likely or accelerated in the warmer regions in a cell [1][2]. In EVs, through-plane thermal gradients often develop across individual pouch cells due to the widespread use of surface cooling, particularly during fast charging, when the heat generation rates are also increased. This work investigates the effects of such through-plane thermal gradients on the lithium plating behaviour using a multilayer 2D electrochemical-thermal model and high-rate cycling experiments. The results show that the thermal gradient can result in preferential plating in either the colder or warmer cell regions, depending on the average cell temperature and the activation energies of solid diffusion and lithium plating. While the diffusion rates are slower in the colder cell layers, warmer ones attract higher currents and either of these effects may dominate the plating behaviour. The experimental validation consists of differential voltage analysis, post-mortem visual examination and measurement of remaining capacity in coin cells harvested from Li-ion cells fast charged under uniform temperatures and under thermal gradients. The limitations of DVA as a technique to quantify lithium plating are highlighted. These stem from the fact that the quantification technique requires assuming that only lithium stripping and no de-intercalation takes place up to the differential voltage minimum. In reality, the current is divided between both reactions, and both the temperature and concentration of the metallic lithium may affect the rate of stripping, shifting the location of the minimum
O'Kane SEJ, Kirkaldy N, Offer GJ, et al., 2022, Lithium-Ion Battery Degradation: How to Diagnose It, ECS Meeting Abstracts, Vol: MA2022-01, Pages: 396-396
<jats:p> Many different degradation mechanisms occur in lithium-ion batteries, all of which interact with one another [1]. However, there are few fewer observable consequences of degradation than there are mechanisms [2]. It is possible to measure the different degradation modes: loss of lithium inventory (LLI), loss of active material (LAM), impedance change and stoichiometric drift [3].</jats:p> <jats:p>It is not always possible to link these observable consequences of degradation to any particular mechanism or combination of mechanisms. Many models of degradation exist [4], but these models have many parameters that cannot be measured directly. A recent modelling study [5] found the number of parameters that the model is sensitive to is greater than the number of observable degradation modes.</jats:p> <jats:p>However, the same model [5], despite including just four degradation mechanisms, found five possible degradation pathways a battery can follow. The model was built so that more mechanisms can easily be added later, so more pathways will be found.</jats:p> <jats:p>In this work, a new approach to diagnosing battery degradation is proposed, based on these pathways. Experimental data for the degradation modes can be identified as being consistent with a particular pathway. Once the correct pathway is found, the parameters that particular pathway is sensitive to can be fit to the data, feeding back into the model.</jats:p> <jats:p>[1] Jacqueline Edge <jats:italic>et al.</jats:italic>, <jats:italic>Phys. Chem.: Chem. Phys.</jats:italic> vol. 23, pp. 8200-8221, 2021.</jats:p> <jats:p>[2] Christoph Birkl <jats:italic>et al.</jats:italic>, <jats:italic>Journal of Power Sources</jats:italic> vol. 341, pp. 373-386, 2017.</jats:p> <jats:p>[3] Matthieu Dubarry &l
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