锂离子电池外部短路电压行为预测模型评价

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。

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

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.