基于V_(min)-EKF的动力锂电池组SOC估计

Based-V_(min)-EKF SOC estimation for power Li-ion battery pack

动力电池组的荷电状态(SOC)是电动汽车能量控制的重要参数.针对串联锂电池组的SOC估计问题,建立电池组的Vmin状态空间模型,电池组内单体电池负载电压的最小值Vmin和电池组的SOC分别作为模型的观测变量和状态变量.应用扩展卡尔曼滤波算法,实现对SOC的动态估计.对模拟电动汽车的实际工况进行电池组放电实验,结果表明,该方法能实时准确地估计电池组SOC.

State-of-charge （SOC） of power battery pack is an important parameter for electrical vehicle. Aiming at SOC estimation for Li-ion battery pack of multi cells in series,a Vmin state space model of battery pack is proposed. The minimal cell load voltage of the battery pack is the model observation variable,and SOC is the model state variable. By applying extended Kalman filter,dynamic state estimation of SOC is realized. The experiment is made to simulate the behaviors of battery pack in the actual work conditon of electrical vehicle. The result shows that the accurate and real-time estimation of SOC can be obtained by using this approach.