基于双无迹卡尔曼滤波的锂电池SOC估算

Estimation of state of charge of lithium battery based on dual unscented Kalman filter

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.