扩展卡尔曼滤波在锂电池SOC估算中的应用

The SOC estimation of lithium-ion batteries based on EKF

电动汽车发展是我国新型汽车发展的大方向之一,而储能电池的发展更是电动汽车发展的重中之重。锂电池SOC在线估算是在不妨碍锂电池正常工作的前提下通过检测电池的参数来间接估算电池荷电状态的一种方法,它是电池组管理和维护的重要依据,可以有效地避免电动汽车行驶时锂电池可能出现的各种故障。主要通过建立Thevenin电池等效电路模型并使用扩展Kalman滤波迭代算法对单节锂电池电池的荷电状态进行在线估算,先采用实验仪进行恒流放电实验得到阻抗曲线,再通过分析曲线数据利用Matlab解方程组得到Thevenin电池模型参数。经过实验测试,证明在恒流充放电的条件下,该算法在线估计SOC具有较好的精度,在锂电池充电至电量已满时达到的最大误差小于5%。

The development of electric vehicle,especially the development of battery is a important aspect about the development of new cars.Estimating the SOC of lithium-ion batteries on line means indirectly estimating the state of charge by detecting the parameters of the battery without stop its works.It is an important basis for batteries management and maintenance.This paper through building the Thevenin model and using EKF to estimate the state of charges.Then I through a constant current discharge experiment to obtain the impedance curve.Finally analyzing the data by using Matlab solve the equations for obtain Thevenin model’s curve data.The experiments results show that the EKF algorithm has a good accuracy for on line estimation,and the maximum error is less than 5%when the lithium-ion battery complete the charge