基于DAUKF的锂电池SOC值和SOH值的估算研究

为提高锂离子电池荷电状态(state of charge,SOC)值和健康状态(state of health,SOH)值的估算精度,基于二阶戴维南等效电池模型,提出双自适应无迹卡尔曼滤波(double adaptive unscented Kalman filter,DAUKF)算法。通过AUKF1和AUKF2这2个滤波器,可以同时计算出电池的SOC值和电池内阻,内阻既可以更新电池的模型参数,又可依靠函数关系,估算出电池的SOH值。仿真结果表明,DAUKF能够准确估算出SOC值和SOH值,精度保持在2%以内,由此验证了该方法的可行性和精确性。

Estimation of SOC and SOH Values of Lithium Battery Based on DAUKF

In order to improve the estimation accuracy of values of state of charge(SOC)and state of health(SOH)of Li-ion batteries,a double adaptive unscented Kalman filter algorithm is proposed based on the second-order Thevenin equivalent battery model.Through AUKF1 and AUKF2 filters,the SOC and internal resistance of the battery can be calculated at the same time.The internal resistance can not only update the model parameters of the battery,but also rely on the function relationship to estimate SOH value of the battery.The simulation experiment results show that DAUKF can estimate values of SOC and SOH accurately,and the accuracy can be kept within 2%.The feasibility and accuracy of this method are verified,which is of great significance to the safe use and life extension of lithium battery in electric vehicle.