摘要
作为电池管理系统技术的核心,SOC的估算已受到越来越多研究者的重视,能否准确估算SOC对电动汽车的发展具有非常重要的意义。针对传统的扩展卡尔曼滤波算法存在由于模型简化导致的在电流突变时对状态变量跟踪效果不佳的问题,文章在此基础上提出了强跟踪卡尔曼滤波算法。并在相同的条件下用两种算法对电池SOC进行了估算,仿真实验结果表明,与扩展卡尔曼滤波算法相比,在电流多变的工况下,强跟踪卡尔曼滤波算法具有较高的精度。
As the core of battery management system technology, SOC estimation has been paid more and more attention by researchers,it is of great significance to accurately estimate SOC for development of electric vehicles.In view of the problem that the traditional extended kalman filter has a poor tracking effect on state variables due to model simplification, this paper proposes a strong tracking kalman filter algorithm on this basis.The simulation results show that, compared with the extended kalman filter algorithm, the strong tracking kalman filter algorithm has higher accuracy under the condition of variable current.
作者
王汉林
WANG Han-lin(Electrical Engineering College,Guizhou University,Guiyang,Guizhou 550025)
出处
《新型工业化》
2019年第5期7-12,共6页
The Journal of New Industrialization
关键词
电池管理系统
SOC估算
扩展卡尔曼滤波算法
强跟踪卡尔曼滤波算法
Battery management system
SOC estimation
Extended Kalman filter algorithm
Strong tracking Kalman filter algorithm
