基于双卡尔曼滤波的锂电池SOC估计

针对电池SOC估计误差较大的问题,本文提出了双卡尔曼滤波算法。介绍了电池常用的等效模型和使用方向,以双RC模型为基础建立了电池系统的空间方程,使用混合脉冲功率特性测试法得到了模型参数值；推导了安时积分法和扩展卡尔曼滤波原理,在基础上提出了双卡尔曼滤波算法,对双卡尔曼滤波的原理和公式实现进行了详细推导；设计了电池组的充放电实验对算法进行验证,结果表明安时积分法估计误差随时间不断增大,扩展卡尔曼算法估计误差震荡很大,双卡尔曼滤波的估计精度较高,最大估计误差只有0.13%。

Estimation of SOC of Battery Based on Double Kalman Filter

Aimed at solving the problem of great estimation error, Double Kalman Filter is proposed. The commonly used battery equivalent model and direction for use is introduced. Space equation of battery system is built based on Double RC model, and model parameters are identified by Hybrid Pulse Power Characterization measurement. Priciple of Ampere-Hour Integral and Extended Kalman Filter are deduced, based on which Double Kalman Filter is put forward, and its principle and implementation is infered in detail. Charging and discharging test of battery pack is designed to verify the algorthm. The result shows that the error of Ampere-Hour Integral increases with time, the error of Extended Kalman Filter oscillate greatly, and the error of Double Kalman Filter is very small and its biggest value is 0.13%.