基于改进联合扩展卡尔曼算法的AGV车SOC估算研究

Research on SOC estimation of AGV vehicle based on improved joint extended kalman algorithm

结合自动引导车(AGV车)运行工况中充电电流大、间歇充电以及放电电流的特点,文章根据电池SOC估算的需求和锂离子电池的外特性,解决电池SOC估算的非线性和电流漂移问题,对电流突变情况下的SOC估算存在较大误差进行分析,提出了利用动态增益系数对Joint-EKF算法进行改进,提高Joint-EKF算法在电流突变时估算算法的跟踪性能和实时性。

Combined with the characteristics of high charging current, intermittent charging and discharging current in the operation condition of automatic guided vehicle(AGV), according to the demand for battery SOC estimation and the external characteristics of lithium ion battery, the problem of nonlinearity and current drift in battery SOC estimation was solved. The large error in SOC estimation under the condition of current mutation was analyzed, and the Joint EKF algorithm was improved by using dynamic gain coefficient, Improve the tracking performance and real-time performance of the Joint EKF algorithm when the current suddenly changes.