摘要
锂电池荷电状态(SOC)估算是电池管理系统的重要内容之一。为了提高SOC估算精度,以二阶RC等效电路为模型,采用双无迹卡尔曼滤波(DUKF)算法对电池模型参数和SOC进行在线联合估算。通过恒流放电测试、动态应力测试(DST)和不同初始SOC值的鲁棒性测试,验证了所提方法的准确性和稳定性。
The estimation of battery state of charge(SOC)is one of the essential contents of the battery management system(BMS).In order to improve the accuracy of SOC estimation,dual unscented Kalman filter(DUKF)algorithm was used for the online joint estimation of the battery model parameters and SOC by taking second-order RC equivalent circuit as the model.The accuracy and stability of the proposed method were verified by constant current discharge test,dynamic stress test(DST)and robustness tests with different initial SOC values.
作者
邹琳
刘佳俊
马国庆
郎锦峰
ZOU Lin;LIU Jiajun;MAGuoqing;LANG Jinfeng(School of Mechanical and Electrical Engineering,Wuhan University of Technology,Wuhan Hubei 430070,China)
出处
《电源技术》
CAS
北大核心
2021年第4期450-454,共5页
Chinese Journal of Power Sources
关键词
荷电状态
无迹卡尔曼滤波
联合估算
等效电路模型
state of charge
unscented Kalman filter
joint estimation
equivalent circuit model