基于FFMILS-MIUKF算法的锂电池SOC估计

SOC estimation of Lithium battery based on FFMILS-MIUKF algorithm

准确估计SOC在防止锂电池过度充放电、提高锂电池能量利用率以及保障电池管理系统安全稳定运行方面具有重要意义。本文以三元锂电池为研究对象,提出一种基于多新息辨识理论的SOC估计方法,通过建立二阶RC等效电路模型,采用遗忘因子多新息最小二乘法(FFMILS)对模型参数进行在线辨识,结合多新息无迹卡尔曼滤波(MIUKF)算法估计锂电池的SOC,通过UDDS实验验证,并和EKF、UKF及MIUKF算法进行对比,实验结果表明,FFMILS-MIUKF算法估计锂电池SOC的误差控制在1.08%左右,其具有高精确性和快速收敛性。

Accurate estimation of SOC plays an important role in preventing excessive charge and discharge of lithium batteries,improving energy utilization rate of lithium batteries and ensuring safe and stable operation of battery management system.In this paper,a SOC estimation method based on multi-innovation identification theory is proposed for ternary lithium batteries.Adopting forgetting factor multi-innovation least square method for model parameter online identification by building a second order RC equivalent circuit model,multi-information unscented Kalman Filter algorithm was used to estimate the SOC of lithium batteries.Through Verified by UDDS experiment and were compared with EKF,UKF and MIUKF algorithm,the results indicate that FFMILS-MIUKF algorithm to estimate the error of the SOC control at around 1.08%,which has high accuracy and fast convergence.