基于无迹卡尔曼滤波算法的锂电池SOC估计

应用无迹卡尔曼滤波算法（UKF）进行锂电池的SOC估计,采用Thevenin二阶RC等效电路模型,对HPPC电池脉冲充放电实验数据进行Matlab处理,得到较为准确的模型.通过在Matlab中编写算法程序,对不同工况的估计值与实际值进行误差估算及对比分析,通过此算法进行SOC估计,得到该算法可有效降低系统误差并纠正SOC的初值偏差.

The non trace Calman filter （UKF） is applied to the SOC estimation of lithium battery. The Thevenin two order RC equivalent circuit model is used to process the HPPC battery pulse charge discharge experimental data by Matlab processing, and a more accurate model is obtained. By writing algorithm program in Matlab, the error estimation and comparison analysis of the estimated value and actual value of different states are carried out, and the SOC estimation is carried out by this algorithm. The algorithm can effectively reduce the system error and correct the initial value deviation of the SOC.