Second-order RC modeling and parameter identification of electric vehicle power battery

doi:10.12028/j.issn.2095-4239.2019.0015

Abstract

Abstract: Establishing accurate power battery model is one of the key issues in the development of battery management system (BMS). Battery has strong non-linear characteristics, and its model parameters vary with various factors. In battery model parameter identifcation, the more variable factors are considered, the more accurate the identification results are, but the running speed of the model will be reduced, which will affect its practical application. Among all kinds of variable factors, state of charge (SOC) has the most significant impact on battery model parameters. Identifcation and application of battery model parameters under different SOC will improve the accuracy of battery model while maintaining good real-time performance. In this paper, the secondorder RC equivalent circuit model is used for power lithium batteries. The rebound voltage data of batteries under different SOC conditions are obtained through experiments. The least square ftting method is used to identify the model parameters under different SOC conditions. Furthermore, a real-time simulation model of model parameters varying with SOC is built, and the model is simulated and verifed by experiments. The results show that the model has high accuracy and realtime performance.

Key words: electric vehicle, battery management system, parameter identifcation, second order RC model

CLC Number:

TH132

LUO Yong, ZHAO Xiaoshuai, QI Pengwei, LIU Zengyue, DENG Tao, LI Peiran. Second-order RC modeling and parameter identification of electric vehicle power battery[J]. Energy Storage Science and Technology, 2019, 8(4): 738-744.

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