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internal short circuit evaluation and corresponding failure mode analysis for lithium-ion batteries

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Journal of Energy Chemistry 2021年第10期30卷 269-280,I0008页

作者： Lishuo Liu Xuning Feng Christiane Rahe Weihan Li Languang Lu Xiangming He Dirk Uwe Sauer Minggao Ouyang State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives(ISEA)RWTH Aachen UniversityJaegerstrasse 17/19Aachen 52066Germany Institute of Nuclear and New Energy Technology Tsinghua UniversityBeijing 100084China

internal short circuit(ISC)is the major failure problem for the safe application of lithium-ion batteries,especially for the batteries with high energy density.However,how to quantify the hazard aroused by the ISC,and what kinds of ISC will lead to thermal runaway are still unclear.This paper investigates the thermal-electrical coupled behaviors of ISC,using batteries with Li(Ni_(1/3)CO_(1/3)Mn_(1/3))O_(2) cathode and composite separator.The electrochemical impedance spectroscopy of customized battery that has no LiPF6 salt is utilized to standardize the resistance of ISC.Furthermore,this paper compares the thermal-electrical coupled behaviors of the above four types of ISC at different states-of-charge.There is an area expansion phenomenon for the aluminum-anode type of ISC.The expansion effect of the failure area directly links to the melting and collapse of separator,and plays an important role in further evolution of thermal runaway.This work provides guidance to the development of the ISC models,detection algorithms,and correlated countermeasures.

关键词： Energy storage Lithium-ion battery Battery safety internal short circuit Thermal runaway

An Online Adaptive internal short circuit Detection Method of Lithium-Ion Battery

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Automotive Innovation 2021年第1期4卷 93-102页

作者： Jian Hu Zhongbao Wei Hongwen He National Engineering Laboratory of Electric Vehicles School of Mechanical EngineeringBeijing Institute of Technology5 ZhongGuanCun South StreetHaidian DistrictBeijing 100181China

internal short circuit(ISC)is a critical cause for the dangerous thermal runaway of lithium-ion battery(LIB);thus,the accurate early-stage detection of the ISC failure is critical to improving the safety of electric vehicles.In this paper,a model-based and self-diagnostic method for online ISC detection of LIB is proposed using the measured load current and terminal voltage.An equivalent circuit model is built to describe the characteristics of ISC cell.A discrete-time regression model is formulated for the faulty cell model through the system transfer function,based on which the electrical model parameters are adapted online to keep the model accurate.Furthermore,an online ISC detection method is exploited by incorporating an extended Kalman filter-based state of charge estimator,an abnormal charge depletion-based ISC current estimator,and an ISC resistance estimator based on the recursive least squares method with variant forgetting factor.The proposed method shows a self-diagnostic merit relying on the single-cell measurements,which makes it free from the extra uncertainty caused by other cells in the system.Experimental results suggest that the online parameterized model can accurately predict the voltage dynamics of LIB.The proposed diagnostic method can accurately identify the ISC resistance online,thereby contributing to the early-stage detection of ISC fault in the LIB.

关键词： Lithium-ion battery internal short circuit Recursive least squares Extended Kalman filter

Thermal runaway evolution of a 280 Ah lithium-ion battery with LiFePO_(4) as the cathode for different heat transfer modes constructed by mechanical abuse

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Journal of Energy Chemistry 2024年第6期93卷 32-45,I0002页

作者： Zhixiang Cheng Chengdong Wang Wenxin Mei Peng Qin Junyuan Li Qingsong Wang State Key Laboratory of Fire Science University of Science and Technology of ChinaHefei 230026AnhuiChina

Lithium iron phosphate batteries have been increasingly utilized in recent years because their higher safety performance can improve the increasing trend of recurring thermal runaway accidents.However,the safety performance and mechanism of high-capacity lithium iron phosphate batteries under internal short-circuit challenges remain to be explored.This work analyzes the thermal runaway evolution of high-capacity LiFePO_(4) batteries under different internal heat transfer modes,which are controlled by different penetration modes.Two penetration cases involving complete penetration and incomplete penetration were detected during the test,and two modes were performed incorporating nails that either remained or were removed after penetration to comprehensively reveal the thermal runaway mechanism.A theoretical model of microcircuits and internal heat conduction is also established.The results indicated three thermal runaway evolution processes for high-capacity batteries,which corresponded to the experimental results of thermal equilibrium,single thermal runaway,and two thermal runaway events.The difference in heat distribution in the three phenomena is determined based on the microstructure and material structure near the pinhole.By controlling the heat dissipation conditions,the time interval between two thermal runaway events can be delayed from 558 to 1417 s,accompanied by a decrease in the concentration of in-situ gas production during the second thermal runaway event.

关键词： Lithium-ion battery safety Micro short-circuit cell Heat transfer modes internal short circuit Nail-penetration test

On-board Diagnosis of Soft short circuit Fault in Lithium-ion Battery Packs for Electric Vehicles Using an Extended Kalman Filter

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CSEE Journal of Power and Energy Systems 2022年第1期8卷 258-270页

作者： Ruixin Yang Rui Xiong Weixiang Shen National Engineering Laboratory for Electric Vehicles Department of Vehicle EngineeringSchool of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China Faculty of Science Engineering and TechnologySwinburne University of TechnologyMelbourneVic.3122Australia

The safety of lithium-ion batteries in electric vehicles(EVs)is attracting more attention.To ensure battery safety,early detection is necessary of a soft short circuit(SC)which may evolve into severe SC faults,leading to fire or thermal runaway.This paper proposes a soft SC fault diagnosis method based on the extended Kalman filter(EKF)for on-board applications in EVs.In the proposed method,the EKF is used to estimate the state of charge(SOC)of the faulty cell by adjusting a gain matrix based on real-time measured voltages.The SOC difference between the estimated SOC and the calculated SOC through coulomb counting for the faulty cell is employed to detect soft SC faults,and the soft SC resistance values are further identified to indicate the degree of fault severity.Soft SC experiments are developed to investigate the characteristics of a series-connected battery pack under different working conditions when one battery cell in the pack is short-circuited with different resistance values.The experimental data are acquired to validate the proposed soft SC fault diagnosis method.The results show that the proposed method is effective and robust in quickly detecting a soft SC fault and accurately estimating soft SC resistance.

关键词： Battery safety electric vehicles external short circuit fault diagnosis internal short circuit soft short circuit

Data-driven short circuit resistance estimation in battery safety issues

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Journal of Energy Chemistry 2023年第4期79卷 37-44页

作者： Yikai Jia Jun Xu Department of Mechanical Engineering and Engineering Science The University of North Carolina at CharlotteCharlotteNC 28223USA Vehicle Energy&Safety Laboratory(VESL) North Carolina Battery ComplexityAutonomous Vehicle and Electrification(BATT CAVE)Research CenterThe University of North Carolina at CharlotteCharlotteNC 28223USA School of Data Science The University of North Carolina at CharlotteCharlotteNC 28223USA

Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions.Cycling tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing samples.The samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel sizes.This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.

关键词： Lithium-ion battery Safety risk internal short circuit short circuit resistance Convolutional neural networks

Novel Lightweight and Protective Battery System Based on Mechanical Metamaterials

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Acta Mechanica Solida Sinica 2021年第6期34卷 862-871页

作者： Yao Huang Weihua Guo Jiao Jia Lubing Wang Sha Yin Vehicle Energy and Safety Laboratory(VESL) Department of Automotive EngineeringSchool of Transportation Science and EngineeringBeihang UniversityBeijing100191China Institute of Unmanned System Beihang UniversityBeijing100191China Key Laboratory Impact and Safety Engineering Ministry of Education and Department of Mechanics and Engineering ScienceFaculty of Mechanical Engineering and MechanicsNingbo UniversityNingbo315211ZhejiangChina

The challenges facing electric vehicles with respect to driving range and safety make the design of a lightweight and safe battery pack a critical issue.This study proposes a multifunctional structural battery system comprising cylindrical battery cells and a surrounding lightweight lattice metamaterial.The lattice density distribution was optimized via topological optimization to minimize stress on the battery during compression.Surrounding a single 18650 cylindrical battery cell,non-uniform lattices were designed featuring areas of increased density in an X-shaped pattern and then fabricated by additive manufacturing using stainless steel powders.Compression testing of the assembled structural battery system revealed that the stronger lattice units in the X-shaped lattice pattern resisted deformation and helped delay the emergence of a battery short circuit.Specifically,the short circuit of the structural battery based on a variable-density patterned lattice was∼166%later than that with a uniform-density lattice.Finite element simulation results for structural battery systems comprising nine battery cells indicate that superior battery protection is achieved in specially packed batteries via non-uniform lattices with an interconnected network of stronger lattices.The proposed structural battery systems featuring non-uniform lattices will shed light on the next generation of lightweight and impact-resistant electric vehicle designs.

关键词： Lightweight Lattices Metamaterials Structural battery Battery safety internal short circuit