基于无迹卡尔曼滤波的锂电池SOC估算方法研究

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

锂电池荷电状态(SOC)的准确估算是制约电动汽车发展的关键技术。基于Thevinin模型建立状态空间方程组,将无迹卡尔曼滤波(UKF)应用到锂电池SOC估算中,通过无迹变换(UT)的方式避免对非线性状态方程的线性化,在不增加系统求解复杂度的前提下提高滤波精度,实现非线性条件下锂电池SOC的准确估算。仿真实验结果表明,UKF估算锂电池SOC的整个过程误差控制在1%以内,其精度明显高于拓展卡尔曼滤波(EKF)的4%,实现了锂电池SOC估算精度的提高,更适用于电动汽车锂电池SOC的估算。

The accurate estimation of lithium battery state of charge(SOC) is the key technology for restricting the development of electric vehicles. Based on the Thevinin model, the state-space equations were established. The unscented Kalman filter(UKF) was applied into the lithium battery SOC estimation, avoiding the linearization of the nonlinear state equation through the way of unscented transform(UT) and improving the filter accuracy to achieve accurate estimation of lithium battery SOC in nonlinear conditions without increasing the system's complexity. The simulation results show that UKF way controls the error of estimating lithium battery SOC less than 1% in the whole process and the accuracy significantly higher than the 4% of expansion Kalman filter(EKF), and this way is more suitable for the electric vehicle lithium battery SOC estimation.