Power Li-ion Batteries Research Articles

SOC Estimation of Li-Ion Power Battery Based on Strong Tracking UKF with Multiple Suboptimal Fading Factors

SOC Estimation of Li-Ion Power Battery Based on Strong Tracking UKF with Multiple Suboptimal Fading Factors

N-doped lithium titanium oxide for high power Li-ion rechargeable batteries with excellent cyclability

Lithium titanate, Li4Ti5O12 (LTO) is being explored as an anode in Li-ion batteries owing to its minimal structural change during lithiation/delithiation and excellent capacity retention at higher current rates. However, the lack of stable cyclability at higher applied currents owing to low electronic conductivity, restricts its widespread applications. Solid state anionic doping represents a convenient strategy to improve the intrinsic electronic conductivity of the LTO material. Hence, a facile and scalable solid state‐inspired protocol has primarily been devised aimingthe large-scale production of nitrogen-doped LTO. The structural analysis demonstrates the diffusion of nitrogen into the lattice without damaging the intrinsic microstructure of LTO. The 2% nitrogen-doped LTO as a working electrode in Li-ion half-cell, displays enhancement in Li-storage capacity by 30%. Moreover, it exhibits excellent rate performance (131 mAhg−1 @ 5C) and ultra-long cycling stability upto 1000 cycles retaining 82 % capacity. Further, full cell study of N@LTO with LiCoO2 exhibits specific capacities of more than 155 mAh/g at a 0.05C rate. Overall, the enhancement in performance attributes to N doping which is likely to improve not only the electrical conductivity but also the ion transport capabilities. Hence the N@LTO will have potential in high power Li-ion batteries.

Soc Estimation of Li-ion Battery Based on Adaptive CKF Algorithm

A second-or der RC equivalent circuit model was established to improve the estimation accuracy of state of charge (SOC) of power Li-ion batteries, and the model parameters were identified by the recursive least square method with forgetting factor (FFRLS). On this basis, an adaptive cubature kalman filter (ACKF) algorithm was proposed to adaptively modify the process noise covariance matrix and the measurement noise covariance matrix to improve the SOC estimation accuracy. Finally, the SOC estimation algorithm was verified by MATLAB simulations. The results show that compared with UKF and CKF algorithms, the proposed algorithm has higher estimation accuracy and robustness, and can meet the application requirements.

Experimental study on flow control system of an electric pump-fed cycle for thrust control

An electric pump-fed cycle can enable the electrical control of pump revolutions and rapidly vary the propellant flow rate. This paper proposes the pump control method as a flow control system of an electric pump-fed cycle. In order to evaluate the applicability of the designed flow control system, the test equipment that simulates an electric pump-fed cycle was constructed, including the Li-ion battery power system and communication instruments. The designed PID controller demonstrated rapid flow stabilization and robustness compared to the system without a controller. Meanwhile, under the initial pressurized condition in the run tank that simulated an engine start-up sequence, the controller response delay occurred was more than 500 ms. In addition, the dynamic loads, such as the water hammer effects and overshoot, were identified. The start-up sequence of an EP cycle was adjusted to alleviate those issues. Consequently, the supply stabilizing time and overshoot were adjusted to 400 ms and 1.7 %, respectively. This study can be the first step in utilizing an electric pump-fed cycle for the thrust control technology in the upper stage of a mission.

Monolithically-stacked thin-film solid-state batteries

The power capability of Li-ion batteries has become increasingly limiting for the electrification of transport on land and in the air. The specific power of Li-ion batteries is restricted to a few thousand W kg−1 due to the required cathode thickness of a few tens of micrometers. We present a design of monolithically-stacked thin-film cells that has the potential to increase the power ten-fold. We demonstrate an experimental proof-of-concept consisting of two monolithically stacked thin-film cells. Each cell consists of a silicon anode, a solid-oxide electrolyte, and a lithium cobalt oxide cathode. The battery can be cycled for more than 300 cycles between 6 and 8 V. Using a thermo-electric model, we predict that stacked thin-film batteries can achieve specific energies >250 Wh kg−1 at C-rates above 60, resulting in a specific power of tens of kW kg−1 needed for high-end applications such as drones, robots, and electric vertical take-off and landing aircrafts.

Novel approach for liquid-heating lithium-ion battery pack to shorten low temperature charge time

The charging time for Li-ion power battery in hybrid electric vehicles (HEVs) and pure electric vehicles (EVs) is elongated at low temperature compared to that at the room temperature, which will deteriorate the customer using experience. Therefore, shortening the low-temperature charging time of battery is the critical technology to promote the popularization of electric vehicles. Many techniques have been proposed to shorten the low-temperature charging time, but these technologies often lead to problems such as the increase of vehicle energy consumption, the high temperature of the battery pack system (BPS) at the end of charging and the poor BPS temperature uniformity during charging. To tackle these problems, this paper proposes an optimization simulation model for charging control strategy combined with thermal model (SCCS-ThM) and BPS offline parameters based on a liquid heating thermal management system (LHTMS). The BPS offline parameters determine the charging power threshold under different ambient temperature and the different state of capacity (SoC). The temperature rise and the temperature differences of the BPS during charging are calculated with the thermal model. The optimization model obtains the optimal charging strategy by simulating the potential feasible charging strategies. The battery pack charge time is reduced by introducing a pre-heating stage prior to charging. The pre-heating period which minimizes overall charge time, including the pre-heating time, is determined using the thermal model. The experimental results show that for an initial battery pack temperature of −10 °C, overall charge time is minimized by starting to charge after the battery pack has been heated to 1 °C. With the same charging energy, the optimal charging strategy shortens the charging time by 16 % and reduces battery coolant heater energy consumption by 15 %. Besides, the maximum temperature at the end of charging and the maximum temperature difference during the whole charging process are 36 °C and 6 °C respectively, which are better than the original charging strategy.

Detection of jelly roll pressure evolution in large-format Li-ion batteries via in situ thin film flexible pressure sensors

Mechanical pressure develops in Li-ion batteries (LIBs) during operation and is critical to battery performance and safety. Detecting pressures in situ is essential to elucidate the operating mechanisms. However, the feasibility and scalability of the current methods face challenges in practical in-situ measurements given the harsh battery internal environment and shell obstruction, especially for large-format LIBs. This study develops an in-situ measurement method for the mechanical pressure of electrode stacks, referred to as jelly rolls, by using embedded thin-film flexible pressure sensors. Pressure sensors are placed inside a prismatic power LIB, and the pressure behaviors are detected. The experiments demonstrate that this method can be used to inspect the mechanical behavior of the jelly roll over a long operation time. The mechanical pressure generated by the volume expansion of the jelly roll is related to the lithiation and delithiation of the graphite cathode. Both reversible and irreversible pressures can be observed using this method, their evolution characteristics are related to spatial location, charging/discharging rate, external pressure, and electrode stack assembly. The proposed method is promising in detecting the pressure state of LIBs and assisting in the evaluation of battery engineering design, manufacturing, and operation monitoring.

Structural, morphological, optical, electrical and dielectric features based on nanoceramic Li4Ti5O12 filler reinforced PEO/PVP blend for optoelectronic and energy storage devices

Polymer nanocomposite films had been fabricated by the solution casting process using the organic matrix of polyethylene oxide/polyvinylpyrrolidone (PEO/PVP: 50/50 wt%) blend and various filling levels of lithium titanium oxide nanoparticles (Li4Ti5O12 NPs). The TEM and XRD techniques indicated the phase purity of the cubic Li4Ti5O12 NPs with a crystallite size of about 69 nm. The FTIR spectra revealed that the complexation/miscibility between the PEO/PVP blend components were existed through the formation hydrogen bonding between the main functional groups of these polymers and also the loaded NPs fundamentally behaved as geometrical incarceration for the structure of PEO/PVP matrix, due to the formation of polymer-nanoparticles interactions. The SEM images indicated observable variations in the size of PEO spherulites, formed aggregations and pores of host matrix on 1 wt% Li4Ti5O12 NPs and additional 3 and 5 wt%. The optical features of nanocomposites such as optical energy band gap and refractive index were evaluated through the UV/vis. absorbance spectra, where the redshift for the main absorption edge of the filled films implied that Li4Ti5O12 NPs had been successfully embedded into the PEO/PVP matrix. The maximum refractive index and the lowest optical bandgap energy were obtained for the nanocomposite sample (5 wt%). The AC electrical conductivity σac and the dielectric response of the prepared samples were studied, where the loaded NPs increased the values of σac, dielectric loss, and dielectric constant of the PEO/PVP blend and the dielectric constant of the nanocomposite films decreased with increasing the applied frequency. The electrical modulus formalism (M*) and impedance formalism (Z*) were used to analyze the impedance data. The enhancements in the optical and electrical characteristics make these nanocomposite materials appropriate for many uses such as integral thin film capacitors, flexible nanodielectrics for organoelectronic devices, high power Li-ion batteries, optical band gap tuner and many optoelectronic devices.

Estimation of state of charge for hybrid unmanned aerial vehicle Li-ion power battery for considering rapid temperature change

State of Charge (SOC) estimation of power battery is essential for hybrid Unmanned Aerial Vehicle (UAV) systems. During the flight of a hybrid UAV, the ambient temperature changes rapidly. The battery parameters also change with the temperature, which deteriorates the accuracy of SOC estimation. Given the above problems, this paper proposes a bipolar equivalent circuit model of a Li-ion battery and its R, C parameter identification method based on the particle swarm optimization algorithm, considering the impact of rapid changes in ambient temperature on battery parameters during the flight of a hybrid UAV. On this basis, a Fast Temperature Correction Adaptive Particle Filter (FTC-APF) SOC estimation method is proposed. This method not only considers the rapid change of temperature to update the actual capacity, Open Circuit Voltage (OCV), and Dual Polarization (DP) model parameters in real time but also weakens the impact of the uncertainty noise generated by external disturbances or sensors on the SOC estimation of Li-ion battery by predicting the process noise and updating the observation noise. The experimental results show that, compared with the existing research, the proposed method effectively achieves the accurate estimation of SOC of the hybrid UAV lithium-ion battery under the condition of rapid temperature change.

Rapid Detection Technology for Performance and State of Li-ion Power Batteries

Power li-ion batteries are often used in fields such as electric vehicles due to their high energy density, long cycle life, and low self-discharge. To ensure safe, stable, and reliable operation of power li-ion batteries, accurate and effective detection of battery performance is crucial. Conventional detection methods of battery capacity, remaining life, and other battery performance parameters usually require complete charge-discharge cycle data, resulting in long detection times and low efficiency. Therefore, how to achieve rapid detection of battery performance has become a hot research topic with engineering demands. There have been certain research achievements in the rapid detection technology of power li-ion battery performance. This article elaborates on the significance of rapid detection of li-ion power battery performance, summarizes key technologies and technical characteristics related to rapid detection based on current research achievements, and provides reference to the rapid detection of li-ion power battery performance.

Fabricating and Probing Forsterite Li-ion Battery Anode Electrodes

In an effort to minimize irreversible capacity loss and volume expansion, research on Si nanocomposite materials with a SiO<sub>x</sub>/Mg<sub>2</sub>SiO<sub>4</sub>/SiO<sub>x</sub> structure through a magnesiothermic reduction process (MTR) has attracted much attention from researchers. Mg<sub>2</sub>SiO<sub>4</sub>(forsterite) has been shown to improve the initial coulombic efficiency (ICE) by minimizing the irreversible capacity loss due to pulverization and highvolume expansion of the Si-based anode complexes. In this study, forsterite was synthesized as the main phase by Mg vapor control in the MTR process. We used an electrophoretic deposition system to investigate the intrinsic electrochemical properties of forsterite, which served as a buffer for the improvement of ICE, associated with the lithiation/delithiation process. Importantly, a stable specific capacity of up to 200 mAh/g was achieved during the charging/discharging process, demonstrating its potential use as an anode electrode. We also found that no significant capacity was found by alloying with Si. In other words, there is a lithium storage mechanism unique to forsterite which is not related to the Si alloying reaction in the storage mechanism. The results presented here are the first demonstration of a forsterite lithium-ion battery; forsterite has only been considered as a buffer layer of the Si/SiO composite structure. Furthermore, the finding is of crucial importance as it provides the basis for various approaches to develop reversible and high power li-ion battery anodes by synthesizing the Si composite through MTR.

Structured Cathodes Enabled By Freeze Tape Casting for High Energy Density/High Power Li Ion Batteries

The development of new cathode architectures that will enable low-tortuosity and speed up the Li ion dynamics is imperative to achieve high energy density and high-power Li ion batteries. To address this barrier, bi-layer cathode configurations were developed and tested. The bottom layer was densified through calendering. Freeze tape casting (FTC) of aqueous based slurries was applied on top of the densified cathode layer. The structure and porosity of the ice-templated layer were optimized to maximize the overall loading of the active material. The electrochemical performance at several C-rates and the interfacial resistance of the cathode were evaluated and modeled. The results were compared against non-structured cathodes. The developed FTC application techniques can be scaled using a high throughput FTC configuration. This research was sponsored by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office (VTO) (Program Manager: Peter Faguy).

In-Situ Derived Bi Alloys for High Performance and High Power Li-Ion Batteries: Effects of Conversion Family, Mesomatrix, and Electrolyte

Despite the fact that the first commercial rechargeable Li battery was based on a Li-Al alloy in the 1970s, extensive investigation of Li alloys for next generation high performance Li-ion batteries has taken place only since Fuji’s initiation of the renaissance in the 1990s [1-2]. Although the majority of this research has been directed towards Si, Sn, Ge and Al [3-4], Bi possesses interesting properties that make it unique amongst the lithium alloys. The heavy pnictogen is of relatively low toxicity with a broad range of applications from Pb replacement in solders to formulations in antacids. In spite of its high molecular weight LixBi exhibits very high volumetric capacity and exceptional Li+ diffusion in its second lithiated phase, Li3Bi [5]. The 0.8 V alloying potential of Bi vs Li/Li+ allows for a more advantageous selection of electrolyte salts and solvents than the aforementioned Si, Ge, and Al. Coupled with its superionic Li+ diffusivity, the higher alloying potential of Bi also provides a larger safety window against Li plating from overpotentials and enables fast charge. While the considerable volume expansion of Bi impedes sustained capacity retention—as with all other Li alloy metals—the volume change from complete lithiation is significantly smaller than that of the popular Si: 108% for Li3Bi compared to 208% for Li13Si4 at a comparable 3.25 Li+ insertion. Combined, these positive attributes present the opportunity to meet the high-rate and volumetric energy capability needs in the next generation of Li-ion batteries.In this work, we explore the effectiveness of BiF3 as an electrochemical precursor to generating a Bi nanocomposite with excellent cycling efficiency extending beyond 250 cycles. An understanding of the nanocomposite’s effectiveness is derived from observations of Bi crystallite sizes produced from the conversion of BiF3, Bi2O3, and Bi2S3. Through electrochemical and physical characterization of these conversion materials, the size of the post-conversion Bi product was found to be not a result of processing conditions but rather the choice of conversion material. The resulting Bi crystallite size post-conversion shows a correlation between the in-situ derived crystallite size and the ionic conductivity of the resulting Li salt matrix. The resulting Bi crystallite size also provides evidence for the inverse relationship between the in-situ derived crystallite size and cyclability that is consistent with theory. For further development, alternative matrices to C were explored in order to preserve the high volumetric capacity of LixBi. Metal sulfides proved a more effective and volumetrically efficient C substitute, with the former exhibiting gravimetric capacities comparable to the latter. Electrolyte formulations derived from use in Bi/C nanocomposites were also tested and proved effective in stabilization of the Li–Bi alloying mechanism in our BiF3 compositions for further cycling improvements. Finally, we demonstrate the ability of BiF3-derived LixBi alloy thin films to delithiate with an 80% utilization at >100C rate despite the presence of a LiF nanomatrix.Through the development of BiF3 nanocomposites using carbon or sulfide matrices in conjunction with an alloy-specific optimized electrolyte, we are able to demonstrate the exceptional cycling of the LixBi alloy (Fig. 1 a,b black) relative to using pure Bi metal in a composite (Fig. 1a,b blue). This presentation will outline the optimization of this alloy family from a holistic perspective and discuss future pathways based on the foundations established here, inclusive of the minimization of the LiF matrix, and in context with the other relatively few publications on this interesting alloy [6-9].

A novel Long-term degradation trends predicting method for Multi-Formulation Li-ion batteries based on deep reinforcement learning

In the design phase of Li-ion batteries for electric vehicles, battery manufacturers need to carry out cycle life tests on a large number of formulations to get the best one that meets customer demands. However, such tests take considerable time and money due to the long cycle life of power Li-ion batteries. Aiming at reducing the cost of cycle life tests, we propose a prediction method that can learn historical degradation data and extrapolate to predict the remaining degradation trend of the current formulation sample taking the initial stage of partial cycle life test results as input. Compared with existing methods, the proposed deep reinforcement learning based method is able to learn degradation trends with different formulations and predict long-term degradation trends. Based on the deep deterministic policy gradient algorithm, the proposed method builds a degradation trend prediction model. Meanwhile, an interactive environment is designed for the model to explore and learn in the training phase. The proposed method is verified with real test data from battery manufacturers under three different temperature conditions in the formulation design stage. The comparisons indicate that the proposed method is superior to traditional degradation trend prediction methods in both accuracy and stability.

Novel fast ionic conductor ceramic composite separator for high-performance safe Li-ion power batteries

The ceramic composite separators coated with silica or alumina particles have been used in power batteries due to their better electrolyte wettability and better thermal stability compared with bare polymer separators. However, these oxide ceramics are Li+ ion insulators, which increase internal resistance and hinder the improvement of rate capability of batteries. Herein, we report a strategy to further improving the performance of lithium-ion batteries (LIBs) by using fast ionic conductor ceramic composite separator as an alternative to traditional ceramic coated separators. Lithium lanthanum titanate (LLTO), a fast ionic conductor with excellent room temperature bulk conductivity, are coated on the common polyethylene (PE) separators. Our results demonstrate that such a novel LLTO-coated separator possess excellent electrolyte wettability and thermal stability; and the assembled NCM523/graphite lithium-ion pouch cells with LLTO-coated separator show better rate capability and cyclic performance with 88.7% capacity retention after 1000 cycles at room temperature compared with the pouch cells with Al2O3-coated separators. The fast ionic conductor ceramic composite separators will be a potential competitor to the next-generation novel separators for high-performance Li-ion power batteries.

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.

Heat pipe/phase change material coupled thermal management in Li-ion battery packs: Optimization and energy-saving assessment

• The stability of an improved HP/PCM coupled TM is studied for multi battery cycles. • PCM is used to “shift load” during discharging and “fill valley” during charging. • The intensity of “load shifting” is proposed and discussed under various conditions. • The maximum energy-saving rate of optimized active–passive TM can reach 81.80%. To lower the energy consumption of Li-ion power battery packs thermal management, this paper investigates an improved heat pipe/phase change material coupled thermal management in a 55-Ah Li-ion battery pack, in which fans can be utilized to strengthen the air condensing effect of the heat pipe. The purpose of this paper is to optimize heat pipe/phase change material coupled thermal management and assess its energy-saving potential for long-time running. Based on the numerical calculation with a 2-dimension coupled resistance-capacity model, the role of phase change material is defined comprehensively, and a multi-cycle process is investigated for long-time temperature control stability. Further multi-objective optimization is conducted to minimize both thickness of phase change material and power of fans under the worst working condition. Finally, the energy-saving effects of optimized coupled thermal management under different discharge–charge conditions are assessed. Results demonstrate that phase change material is used to “shift load” during discharging and “fill valley” during charging, and the intensity of “load shifting” has been discussed. For long-time running, battery surface temperature fluctuates upward and then steadily when heat accumulated during discharging equals to heat-releasing during charging. Furthermore, it also shows that the maximum energy-saving rate reach up to 81.80% by active–passive thermal management. In conclusion, heat pipe/phase change material coupled thermal management possesses considerable energy-saving potential after optimization and is promising to utilize in battery temperature control field with lower carbon emissions.

Periodically aligned channels in Li[Ni0.5Co0.2Mn0.3]O2 cathodes designed by laser ablation for high power Li ion batteries

Lithium-ion batteries are widely used in electric vehicles (EVs) owing to their high energy density and cycling stability. However, achieving high driving mileage per charging time under high electrode mass loading remains a significant challenge for high performance EVs. Herein, a new strategy to improve the rate capability of thick electrodes is proposed based on the laser ablation, which generates periodically aligned channels in the electrodes. To investigate the effect of porosity and interfacial area on the power performance, Li[Ni0.5Co0.2Mn0.3]O2 cathode-based laser-processed electrodes (LPEs) are fabricated by adjusting the spacing and depth of channels. Comparing the relative capacity of C16C/C0.25C, LPEs shows improved value of 19.83%, whereas the conventional electrodes (CEs) of 0.08%. Furthermore, the rate capability of LPEs is superior to that of CEs under the same mass loading, arising from the formation of the channels rather than the mass loss evolved during the laser ablation. The exceptional rate capability of LPEs is attributed to the alleviated activation/concentration polarization, enhanced Li-ion diffusion kinetics, and reduced tortuosity. The laser ablation is an effective strategy, as it can be compatible with any cathode and anode materials.

Prediction and prevention of over-temperature risk of Li-ion power batteries based on the critical heat transfer coefficient and intervention time

• The critical heat transfer coefficient ( h cr ) is defined to indicate that the heat dissipation capability is equal to the heat generated by the battery. • A quantitative criterion ( h < h cr ) is proposed to predict the over-temperature risk of batteries. • The intervention time ( τ intv ) is specified as the time when the battery reaches the over-temperature threshold. • A response surface analysis is conducted to determine intervention methods to prevent over-temperature risk. In recent years, research on high-performance battery thermal management systems (BTMSs) has increased to improve the safety and reliability of electric vehicle (EV) batteries. However, some underlying concepts have not been clearly explained. For example, which conditions are considered safe, and what about not？ This study focuses on the prediction and prevention of battery over-temperature risk using the finite element method. The critical heat transfer coefficient ( h cr ) is proposed as a quantitative criterion for risk prediction since it provides sufficient information on the battery operation, such as the dynamic operating parameters and the battery’s safety temperature. The intervention time is specified, and intervention methods are suggested to prevent risky conditions. Three parameters were found to have a substantial impact on risk prevention, namely, the equivalent heat transfer coefficient ( h ), representing the maximum heat transfer capacity of the heat dissipation system, the ambient temperature ( T ab ), representing the coolant temperature of the heat dissipation system, and the discharge current rate ( C rate ), representing the current level during discharge. A response surface analysis was performed using the maximum operating temperature of the battery ( T max ) as the response variable and three influencing factors as the input variables. The results show that safety zones can be found for each of the three influencing factors. For example, for the case considered in this work, the optimum T ab is around 281.15 K and should not exceed 305.15 K; the C rate should be below under 5C and should never exceed 8C; h should be greater than 50 W·m −2 ·K −1 . Suggestions are provided for choosing risk prevention methods according to the response characteristics of T max . The proposed method provides a novel approach for the research and design of intelligent BTMSs.

One-Dimensional Modeling and Experimental Analysis of Nail Penetration Thermal Runaway for Large Capacity Li-Ion Power Battery

This paper takes a certain type of large-capacity pure electric vehicle NCM li-ion power battery as the object, and analyzes and studies the process of nail penetration thermal runaway(TR). With the aid of AMEsim one-dimensional simulation software, considering the structure composition of the cell, the heat generation mechanism of each side reaction and the three heat transfer modes of thermal radiation, heat conduction and convective heat transfer between the cells, box and the environment, the thermoelectric characteristics of the battery module (six cells) are modeled. The TR behavior of the battery module during nail penetration is simulated and analyzed, and the experiment of the battery module is carried out according to Chinese new regulation GB 38031−2020. The experimental results verify the accuracy of the established model and the reliability of the simulation results, and provide technical reference for the design and development of battery thermal management such as the prediction of TR temperature and the safety of preventing TRP of battery pack.