基于卡尔曼滤波的锂离子蓄电池组SOC估算方法研究

Lithium-ion Battery Pack SOC Estimation Method Study Based on Kalman Filter

针对电动汽车锂离子蓄电池组SOC估算精度问题,采用卡尔曼滤波算法进行估算。建立电池组的状态空间模型,根据实际工况进行模型参数辨识,并实时校正电池组实际容量和库伦效率,通过仿真验证此模型的可行性和精度。仿真结果表明,该方法能够实时估算电池组SOC,最大误差仅为1.8%。卡尔曼滤波算法能够大大提高电池组SOC估算精度,通过改进此算法将能够适应电动汽车复杂行驶工况的安全保障要求。

Using Kalman filter to estimate Lithium-ion battery pack SOC, aiming to improve the SOC estimation accuracy. Establishing the state space model for the battery pack, according to the actual working conditions to identify model parameters, correcting the battery pack actual capacity and coulombic efficiency in real time, and verifying the feasibility and accuracy of the model through the simulation. The simulation results show that this method can estimate battery pack SOC in real time, and the maximum error is only 1.8%.Kalman filter can greatly improve the battery pack SOC estimation precision, and improving Kalman filter will be able to adapt to the requirements of electric vehicle complex running conditions and security.