【摘要】 为实现动力电池状态的精确估计,需要提高电池模型的精确性。对选定的电池模型进行在线参数辨识能够实时反映电池真实的工作状态。采用含遗传因子的递推最小二乘算法(FFRLS)对二阶RC模型进行参数辨识,并在Matlab/Simulink环境下搭建仿真模型用于验证辨识结果。仿真验证结果表明:由FFRLS算法得到的模型参数较为精确,可以作为模型参数在线辨识的一种有效手段。另外,FFRLS算法还能完成电池开路电压的估计,可作为估计电池SOC的参考,有利于了解电池性能状态。更多还原

【Abstract】 To achieve the accurate estimation of the state of power batteries,it is necessary to improve the accuracy of the battery model.Using the method of on-line parameter identification with selected battery model,the real battery state could be reflected in real time.In this paper,Forgetting factor recursive least square algorithm(FFRLS)was adopted to identify the parameters of Double-RC battery model,meanwhile,a simulate model with Matlab/Simulink was applied to verify identification result.The verified results indicated that the model parameters got from FFRLS was accurate and FFRLS was an effective method to identify model parameter online.Additional,the above-mentioned method could be used to estimate the OCV to understand the performance and state of batteries.更多还原