基于安时积分和粒子滤波修正的锂电池SOC估计

SOC estimation of lithium-ion battery based on algorithm of AH with PF correction

针对安时积分(AH)法的累积误差问题和卡尔曼滤波算法对系统噪声的限制,提出了粒子滤波(PF)修正安时积分误差的方案,并基于钴酸锂电池测试数据和电池等效电路模型,对算法进行仿真验证。通过与传统的AH和卡尔曼滤波法对比得出:基于AH和PF修正的方法荷电状态(SOC)估计效果较好,平均误差与标准误差均控制在2%以内。

Aiming at problems of accumulate-errors of Ampere-hour integral（ AH） method and limitation of Kalman filtering algorithm on noise,a scheme of correction accumulate-errors of AH with particle filtering（ PF） is given. Based on LCO battery testing data and model for battery equivalent circuit,the algorithm is verified by using simulation. Compared with AH method and Kalman filtering algorithm,the algorithm of AH with PF correction is better on estimation of state of charge（ SOC）,average error and standard error are both less than 2 %.