基于双UKF滤波器的锂电池SOC-SOH联合估计方法

Joint SOC-SOH Estimation Method for Lithium Batteries based on Dual UKF

为提高锂电池荷电状态(state of charge,SOC)及健康状态(state of health,SOH)的估计精度,以二阶RC等效电路模型为研究对象,基于无迹卡尔曼滤波器(UKF)的思想,提出SOC-SOH联合估计的双自适应UKF滤波器算法,该算法通过对状态方差阵和噪声方差阵的递推估算,确保了状态和噪声方差阵的实时更新,并且能及时反映SOH变化趋势。仿真实验结果验证了该算法的正确性和有效性。

To improve the precision of lithium battery SOC and SOH estimation,taking the second order RC equivalent circuit model as the research object,a joint SOH-SOC estimation method is adopted based on Unscented Kalman Filter(UKF).The proposed algorithm can ensure the real-time update of the status and noise covariance matrix,and reflect the variation trend of SOH in time.The Matlab/Simulink simulation results show that the algorithm is correct and effective.