锂离子电池外部短路电压行为预测模型评价

doi:10.3901/JME.2023.02.199

机械工程学报 ›› 2023, Vol. 59 ›› Issue (2): 199-211.doi: 10.3901/JME.2023.02.199

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锂离子电池外部短路电压行为预测模型评价

燕润博, 孙立清, 杨瑞鑫, 熊瑞

北京理工大学机械与车辆学院北京 100081

收稿日期:2022-01-12 修回日期:2022-10-22 发布日期:2023-03-30
通讯作者: 杨瑞鑫(通信作者),男,1988年出生,助理教授,硕士研究生导师。主要研究方向为新能源汽车动力电池管理。E-mail:yangruixin@bit.edu.cn
作者简介:燕润博,男,2000年出生。主要研究方向为动力电池外部短路建模与低温加热。E-mail:3120190411@bit.edu.cn;孙立清,男,1967年出生,副教授,硕士研究生导师。主要研究方向为新能源汽车和车辆动力学。E-mail:sunlq@bit.edu.cn;熊瑞,男,1985年出生,教授,博士研究生导师。主要研究方向为电动载运工具与电化学储能系统。E-mail:rxiong@bit.edu.cn
基金资助:
国家重点研发计划（2021YFB2402002）、国家自然科学基金（52107222）和中国博士后科学基金（2021M690395）资助项目。

Evaluation of Model for External Short Circuit Voltage Behavior Prediction of Lithium-ion Batteries

YAN Runbo, SUN Liqing, YANG Ruixin, XIONG Rui

School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081

Received:2022-01-12 Revised:2022-10-22 Published:2023-03-30

摘要/Abstract

摘要： 锂离子电池外部短路瞬间产生大电流引发安全事故频繁发生，精确的模型是风险预警的基础。围绕外部短路故障，从不同初始荷电状态（State of charge，SOC）、不同温度两方面开展了Thevenin等效电路模型与单粒子电化学模型的电压预测精度评价与复杂性对比。结果表明，Thevenin模型精度随初始SOC降低而下降，随环境温度升高上升；单粒子模型精度受初始SOC影响较小，随温度升高先上升后下降。针对Thevenin模型短路中精度下降等问题，提出了应用电感元件的模型优化方法。模型方均根误差小于60 mV，精度提升了76%；针对单粒子模型在外部短路大电流中精度变差的问题，提出了使用双电层放电和锂离子扩散限制进行建模的模型优化方法。模型方均根误差小于40 mV，精度提升了64%。优化后的模型分析结果表明：Thevenin模型实时性高，单粒子模型弥补了电池漏液时Thevenin模型的失效，但计算复杂；前者可用在外部短路的前期诊断和预警中，后者可用在外部短路发生后的热管理或热安全研究中。

关键词: 锂离子电池, 电池安全, 外部短路, 模型性能评价, 模型优化

Abstract: The external short circuit of lithium-ion battery produces large current, which further leads to frequent safety accidents.An accurate model is the basis of risk early warning. Focusing on the external short-circuit faults. The voltage prediction accuracy evaluation and complexity comparison of Thevenin equivalent circuit model and single particle model electrochemical model are carried out from different aspects:different initial state of charge(SOC) and different temperatures. The results show that the accuracy of Thevenin model falls with the decrease of SOC and rises with the increase of temperature. The accuracy of single particle model is less affected by initial SOC, which first rises and then falls with the increase of temperature. Aiming at the problems of the accuracy decline of Thevenin model in short circuit, a model optimization method using inductance element is proposed. The root mean square error(RMSE) of Thevenin model is less than 60 mV, and the accuracy is improved by 76%. In order to solve the problem of poor accuracy of single particle model in the external short circuit high current, a model optimization method based on electric double-layer discharge and lithium ion diffusion limitation is proposed. The RMSE of the model is less than 40 mV and the accuracy is improved by 64%. The optimized model analysis results show that the Thevenin model has high real-time performance, and the single particle model makes up for the failure of Thevenin model caused by battery leakage, but the calculation is complex. The former can be used in the early diagnosis and early warning of external short circuit, and the latter can be used in the thermal management or thermal safety research after external short circuit.

Key words: lithium-ion battery, battery safety, external short circuit, model performance evaluation, model optimization

中图分类号:

TM912

燕润博, 孙立清, 杨瑞鑫, 熊瑞. 锂离子电池外部短路电压行为预测模型评价[J]. 机械工程学报, 2023, 59(2): 199-211.

YAN Runbo, SUN Liqing, YANG Ruixin, XIONG Rui. Evaluation of Model for External Short Circuit Voltage Behavior Prediction of Lithium-ion Batteries[J]. Journal of Mechanical Engineering, 2023, 59(2): 199-211.

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锂离子电池外部短路电压行为预测模型评价

Evaluation of Model for External Short Circuit Voltage Behavior Prediction of Lithium-ion Batteries

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