基于扩展卡尔曼滤波法的锂离子电池荷电状态估算方法研究

State of Charge Estimation for Lithium-Ion Batteries Based on the Extended Kalman Filter

电池的荷电状态(SOC)定义为电池当前容量与额定容量的比值,是电池能量管理系统的重要参数,准确获取电池SOC能够提高能量管理系统工作效率,延长电池组寿命.然而现有测量指标不能直接反映电池的荷电状态,需要进行SOC估算.开路电压法和电流积分法可粗略计算电池SOC,但会随着时间产生累积误差,严重影响蓄电池SOC估算的精确性.本文基于扩展卡尔曼滤波方法对磷酸铁锂蓄电池的SOC进行预估,并与传统方法进行了比较,结果表明,该方法能减小SOC估算误差,有效提高蓄电池SOC估算的准确性,且速度快,适合在线预测.

The state of charge（SOC）of batteries is defined as the ratio between the current capacity of the battery and its rated capacity.The ratio is one of the most important parameters of the battery management system（BMS）.To obtain the accurate SOC can help to extend the battery lifetime and improve the efficiency of the energy management system.As there are no direct measurements available currently,SOC estimation is needed.The SOC can be roughly obtained by measuring its open-circuit voltage or counting current integration,however,this inaccurate SOC estimation may decrease the output power capability,consequently it leads to irreversible damage to the battery.This paper presents a method for the SOC estimation based on the extended Kalman filter（EKF）and a comparison is made with the conventional techniques in SOC estimation of lithium-ion phosphate battery.The simulation results show that this method can reduce the estimation error,increase the estimation accuracy of SOC,and it is a faster method,which is suitable for on-line prediction.