Electrochemical-thermal Model Research Articles

A system-level thermal-electrochemical coupled model for evaluating the activation process of thermal batteries

As the primary reserve batteries widely used in military domain, the intricate thermal-electrochemical behaviors and tiny time scale of the activation process make the development of thermal batteries a pain-stacking work, as lacking of the precise model to guide the design process. In this study, a system-level thermal-electrochemical model for evaluating the main technical indexes of LiSi/FeS2 thermal batteries during activation stage is built, which comprehensively considers the main physical and chemical processes such as combustion, heat transfer, phase change, ion transport, voltage variation and so on. The activation characteristics of two types of 5-cell thermal batteries are predicted by this model, and the activation voltages of the two batteries are tested to validate the model. The model possesses the high precision with error less than 5 % by comparing the simulation results of activation voltage with that of experiment results. Specifically, the model reveals that the instantaneous temperature of pyrotechnic pellet after combustion is around 1570 K, and the electrolyte becomes molten and its internal resistance sharply decreases to mΩ level when the temperature reaches its melting point. The variation process of activation voltage is mainly dominated by the geometry size of cell stack and the thickness ratio of pyrotechnic pellet to single cell, besides, the activation time can be considered to be the peak value time of activation voltage. Fuse strip has important effects on the activation process of thermal batteries, especially in the rapid increase period of activation voltage, and the heat transfer is the time-limited step of the activation process. The difference of internal resistance between the unactivated state and activated state of thermal batteries can reach 12 orders of magnitude. These results indicate that our model can perform well in evaluating the activation process of thermal batteries and guiding the optimal design.

Mitigating Heterogeneities in Lithium-Ion Battery Modules Under Fast Charging

Temperature control is essential for fast-charging performance of Li-ion battery. Cold temperature leads to sluggish ion transportation of electrolyte, brittle polymeric cell components, changes in solid electrolyte interface (SEI) properties and associated resistance build-up, and Li plating and dendrite growth [1]. High temperature boosts fast charging but can also accelerate battery degradation and increase the rise of battery thermal failure. This is caused by the increased rate of side-reactions, resulting in loss of cyclable lithium and higher rate of attrition of active materials at higher temperatures.Temperature and its gradient in a battery unit strongly affect performance and life of battery units [2]. It is recommended that pack temperature uniformity of a li-ion battery pack in electric vehicles shall be less than 3 ºC [3]. Battery thermal management systems (BTMS) are important for controlling battery pack temperature and minimizing temperature gradients to prevent thermal-related issues in Battery Energy Storage Systems (BESS). This thermal management goal is more critical for fast charging of battery modules made of large format, high-energy-density cells. Current BTMS in battery electric vehicles (BEVs) are inadequate in limiting the maximum temperature rise of the battery during extreme fast charge (i.e., 6C charge). To achieve fast-charge, the size of the battery thermal management system needs to increase from today’s BEV average size of 1–5 kW to around 15–25 kW [4].A combined experimental and modelling approach is employed to access thermal and electrochemical heterogeneities of a battery module under extreme fast charge conditions and develop corresponding mitigation approaches. The electrochemical-thermal model was built based on electrical characterization of 32 mAh pouch cells, including constant-current 1C to 9C rates of charging at varying temperatures. Predictive performance of the model in heat generation was validated by comparing results against measurements conducted using a microcalorimeter. Thereafter, the validated model is used to predict performance of a battery module consisting of six large format pouch cells. The large pouch cell has a capacity of 25 Ah and the identical electrode design of the 32 mAh cells. 3D simulation results suggest significant temperature and charge differences can be produced. The heterogeneous behavior was enlarged along charging. As shown in Figure 1, it was found that electrodes close to the tabs were preferentially charged.Cell electrochemical heterogeneity can be reduced by reducing cell temperature difference. Two potential solutions are investigated using the developed 3D model, including the enhancement of heat transfer within cells, such as increasing cell thermal conductivities with thicker current collectors, and the optimal design of thermal management systems. The feasibility of state-of-the-art thermal management strategies for fast charging is evaluated, including liquid cooling using cold plate devices and direct liquid cooling.

A New Multiphysics Modeling Framework to Simulate Large Battery Packs

Li-ion batteries are used in a wide variety of applications, ranging from consumer electronics to electric vehicles (EVs) and large-scale energy storage. There are also ongoing efforts to electrify air transportation. The system level issues such as safety, thermal effects, and cell balancing need to be addressed as use of batteries become widespread in the transportation sector. These issues can be studied experimentally, however, extensive experimental testing at system level involving large battery packs is impractical. Additionally, experimental testing alone cannot provide insights into these issues. This makes experimental characterization studies necessary as well, which are not feasible beyond the lab scale. Appropriate use of modeling and simulation can provide an attractive alternative to gain insights into the system level issues. Presently, simplified equivalent circuit and empirical models are typically used at pack level. Since these models do not capture various physical phenomena and electrochemical processes, they cannot provide necessary insights into these issues. There are many simulation studies on thermal management of battery packs, but these studies are limited to studying heat transfer and fluid flow without capturing their effect on the life and performance of batteries. At the scale of a single li-ion cell, there are physics-based models incorporating various processes, including transport processes, reaction kinetics, thermal effect, and degradation mechanisms. However, these models are typically not used to study battery packs. One such attempt reported in literature involved the use of thermal single-particle battery model at the pack level, but this study considered simplified thermal boundary conditions representing natural convection type heat transfer, a rather simplistic treatment for the heat leaving the batteries1. There have been other similar studies as well2-4. Since thermal management systems presently used in EVs and new designs developed by researchers involve far more complex heat transfer processes, a model capturing heat transfer processes in these thermal management systems in an accurate manner is necessary. Using an accurate physics-based electrochemical-thermal model at the battery pack level and combing it with a heat transfer model for battery thermal management system can enable studying battery performance, aging, and safety characteristics at the pack level. However, this type of simulation would be computationally prohibitively expensive, especially for large battery packs, like the ones used in EVs.In the present work, we first develop volume averaged heat transfer models for two different battery pack designs, one involving prismatic/pouch cells, and other involving cylindrical cells, like the Tesla EV battery pack. These volume averaged models are informed by full-order steady-state computational fluid dynamics (CFD) simulations, and later validated against full-order transient CFD simulations for a wide variety of operating conditions. The simulations conducted using volume averaged heat transfer models are at least two orders of magnitude faster than conventional simulations while maintaining the same level of accuracy. Next, the volume averaged heat transfer model for one of these battery pack designs and the recently reported volume averaged thermal tank-in-series battery model are used to develop a modeling framework for multiple cells connected in series to form a module, and multiple such modules connected in parallel forming a battery pack. This modeling framework enables fast simulation of large battery packs while considering complex battery physics in each individual battery and heat transfer in the thermal management system. This proposed approach can be used for any battery pack design and configuration. Using this modeling framework, we perform detailed analysis on the battery pack, including studying electrochemical and thermal behavior of individual batteries in the pack as well as pack level characteristics under different operating conditions. Finally, we also study effect of cell-cell to variations due to possible manufacturing variations and variations in the state of charge (SOC) of batteries across the battery pack.

Multi-scale electrochemical thermal model of Electric Double Layer Capacitor under galvanostatic cycling

Electric Double Layer Capacitors (EDLC) have a wide spectrum of application with internal heat generation which may lead to thermal runaway or accelerated aging. This study proposes a multi-scale electrochemical thermal model of EDLCs. Energy equation is solved for cylindrical EDLC device with averaged reversible heat generation rate calculated from local heat generation rate near single carbon nanoparticles derived from first principle. The numerical heat generation and temperature profile resemble experimental results with a prediction error less than 15%. The temperature is uniform across the jelly roll but shows a major drop across the air gap. The reversible heat generation profile is asymmetric and features a sharper peak for exothermic process compared with endothermic process. This is attributed to the relative fast heat dissipation from the EDLC device to the surrounding during exothermic process. Furthermore, detailed contribution of heat generation rate near the electrode/electrolyte interface is analyzed. Negative heat of mixing is observed at the start of charging. This can be attributed to the deviation of flux direction due to the existence of a curved surface. This comprehensive model can be used to study the detailed effect of nanoparticle phenomena on the heat generation and temperature profiles of commercial EDLC devices.

Faster and Healthier Charging of Lithium-Ion Batteries via Constrained Feedback Control

A constrained feedback control strategy designed on the basis of a simplified electrochemical–thermal model is considered for the fast and healthy charging of a lithium-ion battery cell. The constraints ensure avoidance of side reactions and operating modes that yield premature aging (healthier charging). They are enforced through a reference governor approach, hence requiring a low computational burden. A systematic approach is presented for model identification and control law design. The method is first validated on a detailed battery simulator based on the Doyle–Fuller–Newman model combined with a thermal model. Next, it is validated experimentally through battery-in-the-loop long-term aging campaigns, and the results show that the charging time is reduced by 22% while simultaneously ensuring a longer lifetime (26% less capacity degradation) compared to a 2C constant-current/constant-voltage (CCCV) approach. Compared to recommended C/2 CCCV, our method charges the battery 70% faster and degrades it similarly despite more demanding operating conditions.

Transient Modeling and Optimization of a PEM Electrolyzer for Solar Photovoltaic Power Smoothing

While renewable energy fuel has always had no cost, in the past the cost of the energy conversion technology was prohibitive. Today, due to improved efficiency in the technology and substantial increases in manufacturing volume the cost to generate electricity from the renewables and the cost to store this electricity in lithium-ion batteries for four hours has made these technologies more than competitive with traditional sources. As higher renewable energy penetrations occur the variability and intermittent nature of solar photovoltaic (PV) electricity can cause steep ramping of conventional power plants, so longer term energy storage (days, weeks, instead of hours) will be needed to increase the reliability of grid operation. In Florida cloud cover of a PV field can cause rapid fluctuations of PV output requiring a fast response to smooth out the PV electric power output. A polymer electrolyte membrane (PEM) electrolyzer can serve as a utility controllable load that can be available at all times and the produced hydrogen can be sold or converted back into electricity directly through a PEM fuel cell. To study the integration of renewable solar with hydrogen for increasing grid reliability, a multi-software power control method and a transient thermal electrochemical PEM electrolyzer model has been developed.One-dimensional ("through-plane") and two-dimensional ("through-plane" and "in-plane") un-steady state models using gPROMS 2.1.1. were developed. The model considers mass, energy, momentum and current balance equations. The thermal energy balance considers the heat transfer through the backing layer, the flowfield plates and the gas and liquid flows. Kinetic parameters used in the model were determined using parameter estimation of single cell steady state polarization curves [1]. The single cell unsteady state models were extended to a stack model by adding cells in series and parallel. Real-time PV data taken from a 8.9 MWAC solar farm from Orlando Utilities Commission’s Stanton Energy Center was scaled up to 75 MWAC to design the electrolyzer that would be sized with the typical utility PV installation in Florida. The 75 MW PV data was smoothed using a power control strategy developed in MATLAB. The developed multi-software power control method and the electrochemical dynamic stack model shows the effectiveness of an electrolyzer in smoothing the PV signal to increase the grid stability and flexibility. Results are presented of different size electrolyzers to minimize short term cloud cover spikes in power while maximizing hydrogen production and the effectiveness of the electrolyzer.[1] Vincenzo Liso, Giorgio Savoia, Samuel Simon Araya, Giovanni Cinti and Søren Knudsen Kær, “Modelling and Experimental Analysis of a Polymer Electrolyte Membrane Water Electrolysis Cell at Different Operating Temperatures”, Energies, 11 (2018) 3272. doi:10.3390/en11123273

(Digital Presentation) Temperature Rise during High-Power Pulses of Lithium-Ion Batteries

Lithium-ion batteries currently dominate the light-duty electric vehicle (EV) market due to their high energy density, low self-discharge, and high efficiency. Because of these advantages, Li-ion batteries are now being explored for next-generation EV applications like heavy trucks and aerial vehicles. The new applications present design challenges somewhat different from light-duty, road vehicles. For instance, aerial EVs during take-off and landing or heavy trucks on lengthy inclines/declines require high power (or regenerative) pulses for >1 minute. These long-duration, high power pulses may lead to significant temperature rise that could damage the battery and/or produce unsafe conditions resulting in thermal runaway. Accurate estimations of the temperature rise during these pulses are important for initial studies focused on assessing the validity of Li-ion batteries in these and other applications.This work starts by demonstrating how the accuracy of approximating the temperature rise using Joule heating – i.e., I2R, where I is the applied current and R is the electrochemical resistance – decays considerably for high power pulses. A 3-D thermal-electrochemical model of an NMC532-Graphite pouch cell is then used to explain the causes of the deviation. It is shown that a combination of transport in the electrolyte and self-heating cause variations in the resistance during the pulse, which invalidate the Joule heating approximation. Insights from these results are used to develop a correlation for the temperature rise during high power pulses. The correlation provides an improved estimation of the temperature using minimal experimental data for the area specific resistance of the cell.

Investigating Li Plating Distribution Caused By a Thermal Gradient through Modelling, Differential Voltage, and Post-Mortem Analysis

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 independently of the amount of lithium plated. The results shed light on the effects of thermal gradients on lithium plating behaviour in pouch cells and the challenges associated with quantifying plating with DVA.

(Digital Presentation) An Electrochemical-Thermal Coupled Thermal Runaway Multiphysics Model for Lithium Polymer Battery

With the rising energy demand, safe and efficient energy storage technologies have been increasing in importance. Lithium-ion batteries (LIBs) have been dynamically prevalent as energy storage and power sources for various electrical systems, from communication purposes to transportation applications. Lithium Polymer (LiPo) batteries are a subcategory of LIBs that use a solid or semisolid (gel) polymer to act as both a separator and electrolyte for the system. Compared to a conventional liquid electrolyte, gel polymer electrolyte is more thermally and electrochemically stable and relatively safer. Various companies produce a vast number of different LiPo batteries; however, a limited number of studies have been conducted concerning modeling and simulation. Besides exploring new materials for performance enhancement, engineering a reliable model is equally vital to exploit and optimize existing LiPo batteries' potential.In this study, a multiphysics model for a mobile Lithium Cobalt Oxide (LCO)-graphite- Poly(vinylidene fluoride - hexafluoropropylene) (PVdF-HFP) pouch LiPo battery was established to characterize the battery's behavior. The pseudo-2-dimensional electrochemical model and 3D thermal-thermal runaway model were coupled with temperature and heat generation variables. Working voltage and temperature during galvanostatic discharge were examined for the electrochemical-thermal model. In contrast, temperature as a function of time during an oven test was analyzed for thermal runaway models. The electrochemical-thermal and thermal runaway behavior was investigated using the simulation model, and validations were compared with experimental data. Overall, the models can be employed as a design tool to evaluate the component design and estimate the system performance of LiPo batteries for commercial applications.KEYWORDS: Multiphysics model, Lithium-polymer battery, Thermal runaway

Adaptive Ensemble-Based Electrochemical–Thermal Degradation State Estimation of Lithium-Ion Batteries

In this article, a computationally efficient state estimation method for lithium-ion (Li-ion) batteries is proposed based on a degradation-conscious high-fidelity electrochemical–thermal model for advanced battery management systems. The computational burden caused by the high-dimensional nonlinear nature of the battery model is effectively eased by adopting an ensemble-based state estimator using the singular evolutive interpolated Kalman filter (SEIKF). Unlike the existing schemes, it shows that the proposed algorithm intrinsically ensures mass conservation without imposing additional constraints, leading to a battery state estimator simple to tune and fast to converge. The model uncertainty caused by battery degradation and the measurement errors are properly addressed by the proposed scheme as it adaptively adjusts the error covariance matrices of the SEIKF. The performance of the proposed adaptive ensemble-based Li-ion battery state estimator is examined by comparing it with some well-established nonlinear estimation techniques that have been used previously for battery electrochemical state estimation, and the results show that excellent performance can be provided in terms of accuracy, computational speed, and robustness.

A composite electrochemical-thermal model for the determination of thermal profiles of lithium-ion cell for electric vehicle application

A composite electrochemical-thermal model for the determination of thermal profiles of lithium-ion cell for electric vehicle application

The Effects of Temperature and Cell Parameters on Lithium-Ion Battery Fast Charging Protocols: A Model-Driven Investigation

The risk of lithium plating is a key barrier to lithium-ion battery fast charging. Among other strategies, many alternative charging protocols have been proposed to reduce the plating propensity compared to the conventional constant current-constant voltage (CC-CV) protocol. However, conflicting results have been reported on their impacts on battery lifetime. This work investigates the performance of CC-CV and a boost charging protocol using an electrochemical-thermal model which accounts for nonlinear diffusion and reversible lithium plating. The relative performance of the protocols is found to ultimately depend on the solid phase and ion diffusion timescales. Boost charging is beneficial when both these timescales are short, i.e. in power cells in general or in energy cells at sufficiently high temperatures. The high concentration gradients that develop during the boost stage can sufficiently relax in the subsequent lower current stage to reduce the plating propensity in these cases. When the diffusion timescales are long, boost charging leads to increased plating heterogeneity (driven by the ion diffusion limitations) and slightly increased plating propensity (driven by the solid phase diffusion limitations). Our findings highlight the need to study alternative charging protocols at a wide range of conditions and on different cells before practical deployment.

Cylindrical Battery Fault Detection Under Extreme Fast Charging: A Physics-Based Learning Approach

High power operation in extreme fast charging significantly increases the risk of internal faults in Electric Vehicle batteries which can lead to accelerated battery failure. Early detection of these faults is crucial for battery safety and widespread deployment of fast charging. In this setting, we propose a real-time {detection} framework for battery voltage and thermal faults. A major challenge in battery fault detection arises from the effect of uncertainties originating from sensor inaccuracies, nominal aging, or unmodelled dynamics. Inspired by physics-based learning, we explore a detection paradigm that combines physics-based models, model-based detection observers, and data-driven learning techniques to address this challenge. Specifically, we construct the {detection} observers based on an experimentally identified electrochemical-thermal model, and subsequently design the observer tuning parameters following Lyapunov's stability theory. Furthermore, we utilize Gaussian Process Regression technique to learn the model and measurement uncertainties which in turn aid the {detection} observers in distinguishing faults and uncertainties. Such uncertainty learning essentially helps suppressing their effects, potentially enabling early detection of faults. We perform simulation and experimental case studies on the proposed fault {detection} scheme verifying the potential of physics-based learning in early detection of battery faults.

Research on the Early Warning Mechanism for Thermal Runaway of Lithium-Ion Power Batteries in Electric Vehicles

Lithium-ion power batteries are critical to the macrostrategy of new energy vehicles, and safety concerns such as thermal runaway remain a major bottleneck in the productization and industrialization of lithium batteries. Based on COMSOL Multiphasic, an electrochemical-thermal coupling model for lithium-ion power batteries is created, as well as a thermal model for thermal runaway. A comparative study on lithium-ion power batteries was conducted using this model under on-board conditions, high rate cyclic charging and discharging conditions, and thermal abuse conditions. The temperature rise rate, average temperature, current, and voltage of the lithium-ion power battery and their correlation with thermal runaway are investigated. The results show that the temperature rise rate can significantly characterize the occurrence of thermal runaway, and when the temperature rise rate exceeds 1°C/s, the lithium-ion power battery has a high probability of thermal runaway. In addition, when the average temperature exceeds 80°C, there is a potential risk of thermal runaway in Li-ion power batteries. The results of the study show that high temperatures take longer to trigger thermal runaway, and the battery is slower to warm up. The time it takes for thermal runaway to occur, the maximum temperature reached, and the maximum voltage are all strongly connected to the overcharge flow under overload abuse conditions. The shorter the time it takes for thermal runaway to occur and the greater the maximum temperature and voltage attained, the larger the overcharge current.

Simulation Study on Internal Short Circuits in a Li-Ion Battery Depending on the Sizes, Quantities, and Locations of Li Dendrites

The internal short circuit caused by the Li dendrite is well known to be a major cause for fire or explosion accidents involving state-of-the-art lithium-ion batteries (LIBs). However, post-mortem analysis cannot identify the most probable cause, which is initially embedded in the cell, because the original structure of the cell totally collapses after the accident. Thus, multiphysics modeling and simulation must be an effective solution to investigate the effect of a specific cause in a variety of conditions. Herein, we reported an electrochemical-thermal model to simulate the internal short circuit depending on Li dendrite’s sizes (1, 3, 5, 7, and 9 μm), quantities (1–9), relative locations (0, 25, 50, 100, and 150 μm), and external temperature (−10, 10, 30, and 50°C). Through monitoring the temperature change affected by the joule and reaction heats for each case, we suggested critical conditions that led to unavoidable thermal runaway. Thus, this model can be a steppingstone in understanding the correlation between internal short circuits and Li dendrites.

A comprehensive numerical study on electrochemical-thermal models of a cylindrical lithium-ion battery during discharge process

Modelling the electrochemical and thermal behaviours of cylindrical lithium-ion batteries (LIBs) is complicated by their multi-unit jellyroll structure. To evaluate the accuracy of cylindrical LIB models, eight electrochemical-thermal models (ECT) with different levels of fidelity and dimensionality (from one-dimensional (1D) to three-dimensional (3D) electrochemical and thermal models) are established for a Li[Ni8Co1Mn1]O2/graphite 18,650 type cylindrical LIB. The effect of different levels of model simplification on the predicted LIB thermal and electrochemical characteristics are compared under different discharge and cooling rates. Non-uniformity indexes are also introduced to compare the differences between the eight models for predicting electrochemical reactions and heat generation non-uniformity. The accuracy and computation time of different models are compared, and the applicable scope of different models is discussed comprehensively. Furthermore, the non-uniformity mechanism inside the battery are also analysed. The present work can be used to help other researchers select appropriate electrochemical thermal models under different applicable conditions and study the battery thermal management system.

An electrochemical-thermal coupling model for heat generation analysis of prismatic lithium battery

In this study, an electrochemical thermal coupling model of prismatic lithium battery was established to simulate the actual discharge process. The heat generation distribution and variation in porous electrodes and current collectors were analyzed and the relationship among the total heat generation, discharge rate and discharge time was proposed. The simulation result indicated that the heat generation distribution in the porous electrodes was non-uniform. The moving distance of the peak heat generation density became shorter with the increase of discharge rate. The heat generation density increased with the discharge time. In the porous area, the negative electrode was dominant, and the proportion of polarization heat was the highest. The heat generation of battery was non-uniformity distributed on the current collectors, which increased with the discharge rate and decreased with the progress of discharge. The heat generation expression proposed in this paper could accurately predict the relationship between the total heat generation and the discharge time under each discharge rate, which could provide theoretical support for the establishment of a battery thermal management system.

Modeling and dynamic characteristic simulation of air-cooled proton exchange membrane fuel cell stack for unmanned aerial vehicle

Air-cooled low-temperature proton exchange membrane fuel cell stack applied with metallic bipolar plate is considered as a promising power source for an unmanned aerial vehicle. This paper presents a coupled electrochemical thermal model for simulating its dynamic characteristic. The impact of the applied metallic bipolar plate on the stack thermal balance is considered; an environmental model estimating atmospheric temperature and pressure variations with altitude is included. Our theoretical analysis shows that with altitude increased from 0m to 4000m, the output electric power declined rate is 4.7–6.5% at the current density of 400–800 mA cm−2. To avoid severe stack degradation due to high stack operating temperature, minimum air stoichiometric ratio is required for maintaining stack thermal balance. When the altitude increases from 0 to 4000m, the minimum required air stoichiometric ratio decreases from 110 to 22 at the current density of 800 mA cm−2.

A statistical analysis of thermal characteristics of 55-Ah large-format LIB pouch cell with different tab-type, tab size, and tab position

The non-uniform temperature distribution in large-format lithium-ion batteries (LIBs) can lead to thermal runaway or performance degradation. This study develops a three-dimensional electrochemical–thermal model of a 55-Ah large-format LiFePO4/graphite pouch cell and statistically analyzes the effects of width, height, and attachment positions of the nominal tab (NT), lateral tab (LT), and counter tab (CT) on the temperature distribution. The temperature difference that occurs across the cell is analyzed separately for each design factor through design of experiments (DOE) and analysis of variance (ANOVA). Accordingly, wider tabs reduce the maximum temperature and temperature difference irrespective of the tab type. Taller tabs yield higher maximum temperatures, resulting in a larger temperature difference. Attaching tabs to the edge of the cell increases the maximum temperature and temperature difference. The locations of the negative NTs and CTs do not affect the temperature difference. However, the location of the negative LT increases the minimum temperature, thereby decreasing the temperature difference. The ANOVA revealed that the p-value of the width, height, and attachment position of the positive tab is lower than 0.05 which means the factors strongly influence the temperature difference for all tab-types. Also, the attachment position of the negative tab affects only the LT-type.

An electrochemical–thermal model of lithium-ion battery and state of health estimation

The performance of lithium-ion batteries deteriorates with the passage of time, estimating State-of-Health of batteries correctly is important. In this paper, an electrochemical-thermal model including the electric double layer model is developed. In the frequency domain, sensitivity analysis of the electrochemical processes during battery aging are carried out based on electrochemical impedance spectroscopy and distribution of relaxation time method. In the time domain, single parameter sensitivity analyses are performed. Methods of obtaining different types of parameters in the model are studied, and the electrochemical parameter values of the battery under different cycles are obtained. Finally, some key parameters with higher correlation with State-of-Health are selected to achieve State-of-Health estimation of the battery.