锂离子电池模型参数辨识与荷电状态估算

Parameter identification and SOC estimation of lithium-ion battery model

锂离子动力电池是巡检机器人常用动力源,机器人控制系统需根据电池的荷电状态(SOC)决策工作状态。建立了锂离子电池的二阶Thevenin等效电路模型,用遗忘因子递推最小二乘算法(FFRLS)完成模型在线参数辨识,并用扩展卡尔曼滤波算法(EKF)实现SOC值的估算仿真。在此基础上,设计开发了一套基于STM32微控制器的SOC估算系统,实现了机器人应用中的电池参数采集及SOC估算。

Generally,the lithium-ion battery is used as power source of inspection robot.The robot controlling system decides next working status by taking the SOC value as reference.The second-order Thevenin equivalent circuit model for lithium-ion battery was built,the FFRLS algorithm was used to complete online parameter identification of the model,and the EKF(extended Kalman filter)algorithm was used to realize the simulation for SOC estimation.A SOC estimation system was developed with STM32 microcontroller,and it could be used to collect battery parameters and estimate SOC value in the robot application.