车用磷酸铁锂电池荷电状态的LPV模型卡尔曼滤波算法

Kalman Filter Based on LPV System for SOC(State of Charge)of LiFePO4 Dynamic Battery

动力电池是混合动力汽车产业化发展的关键技术之一,其中电池的荷电状态(State of Charge,简称SOC)估算则是电池管理系统中的重要技术,同时也是发动机和电机动力分配的一个重要参数。文章以磷酸铁锂电池作为研究对象,在进行电池特性试验的基础上提出一种基于LPV模型的卡尔曼滤波算法,与安时计量法相结合,实现磷酸铁锂电池SOC的实时估算。利用MATLAB/Simulink软件建立该算法的模型并进行仿真,结果验证该算法的可行性和精确性。

Dynamic battery is one of the key technologies for the hybrid automobile industry. SOC（ state of charge）of batteries is an important parameter of the power distribution for engines and electric motors. This paper takes the LiFePO4 dynamic batteries as the research object, and puts forward Kalman Filter method based on LPV system after experiencing the characteristics of batteries, which achieves the estimation of SOC with Ah counting method. The model of this algorithm is set up in MATLAB/Simulink. The result of simulation oroves the feasibility and accuracy of this method.