摘要
在众多锂电池的荷电状态(SOC)估计方法中,离散滑模观测器(DSMO)具有较高的估计精度和鲁棒性。针对DSMO存在的抖振问题以及估计SOC过程中伴有的噪声问题,提出基于扩展卡尔曼滤波器的改进离散滑模观测器(IDSMOEKF)的方法。通过ADVISOR软件进行仿真分析,将IDSMOEKF算法与扩展卡尔曼滤波算法和滑模观测器法相比较,结果表明该算法最大误差不超过2.4%,估计精度和鲁棒性优于传统扩展卡尔曼滤波和滑模观测器法。
An improved discrete sliding mode observer based on extended Kalman filter（IDSMOEKF） is proposed in this paper.Simulation analysis is performed by ADVISOR software.Compared with the extended Kalman filter algorithm and the sliding mode observer method,the IDSMOEKF algorithm shows that the maximum error of the algorithm is less than 2.4%.
出处
《工业控制计算机》
2018年第8期67-68,70,共3页
Industrial Control Computer
