电动汽车锂离子电池模型参数辨识和荷电状态估算

doi:10.16180/j.cnki.issn1007-7820.2020.02.006

Abstract

Abstract:

For the problems of low accuracy and poor real-time performance in on-line estimation of lithium-ion battery charging state for electric vehicles, an effective method for accurate on-line estimation of charging state was established. The method of MAFF-RLS and EKF was used to estimate the state of charge for lithium-ion battery. The equivalent circuit model of lithium-ion battery was established, and the MAFF-RLS was applied to the parameter identification for the equivalent circuit model, which could effectively identify model parameters online. Based on the model parameter identification, the identified model parameters are used as the input of the state of charge estimation, and the EKF was used to estimate the real-time state of charge of the power battery. The experimental simulation showed that the combination of MAFF-RLS and EKF could improve the estimation accuracy of the state of charge, and the estimation error was within 2%.

Key words: electric vehicle, lithium-ion battery, model parameter identification, MAFF-RLS, SOC, EKF

CLC Number:

TN711.1

JIANG Qin,ZHANG Xuanxiong. Parameter Identification and State of Charge Estimation of Lithium Ion Battery Model for Electric Vehicles[J].Electronic Science and Technology, 2020, 33(2): 32-36.

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Parameter Identification and State of Charge Estimation of Lithium Ion Battery Model for Electric Vehicles

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