纯电动汽车动力锂电池Nernst模型参数辨识  

Parameters Identification of Nernst Model for Power Lithium-ion Battery of Pure Electric Vehicles

作　　者：毕军[1] 康燕琼[1] 邵赛[1] 

机构地区：[1]北京交通大学,城市交通复杂系统理论与技术教育部重点实验室,北京100044

出　　处：《汽车工程》2015年第6期725-730,共6页Automotive Engineering

基　　金：中央高校基本科研业务费专项资金(2013JBM);北京市科技计划项目(Z111109073511001)资助

摘　　要：建立了电动汽车动力锂电池的Nernst经验模型,并利用遗忘因子递推最小二乘法对模型参数进行辨识。以北京市运营的纯电动环卫车的锂电池数据对所建立的模型和参数辨识算法进行验证,结果表明,所给出的方案是有效的,具有算法运算量少、模型结构简单和辨识精度较高等优点,适于电动汽车运行时对电池模型参数的在线辨识。A Nernst empirical model for the traction lithium-ion battery of electric vehicle is established, and the recursive least square algorithm with forgetting factors is adopted to identify model parameters. The model established and the parameter identification algorithm adopted are verified by using the lithium-ion battery data of re- fuse collecting electric vehicles operating in Beijing city. The results indicate that the scheme has advantages of less computation efforts, simple model and high identification accuracy, and is effective and suitable for online parameter identification of battery model in electric vehicle operation.

关 键 词：电动汽车 电池模型 参数辨识 最小二乘法 

分 类 号：U469.72[机械工程—车辆工程]