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磷酸铁锂电池模型参数辨识与SOC估算
引用本文:侯幽明,陈其工,江明. 磷酸铁锂电池模型参数辨识与SOC估算[J]. 安徽机电学院学报, 2011, 0(2): 55-58
作者姓名:侯幽明  陈其工  江明
作者单位:安徽工程大学安徽省检测技术与节能装置重点实验室,安徽芜湖241000
摘    要:根据磷酸铁锂电池的特性,从电池电化学角度分析,建立电池的等效电路模型。通过实验方法测得电池开路电压与SOC关系和电池模型的参数,利用卡尔曼滤波法来估算电池初始荷电状态(SOC_0).实验与仿真表明,该算法可以有效的估算出SOC初始值,并可以将误差控制在10%之内.

关 键 词:磷酸铁锂电池  电池模型  电荷状态  卡尔曼滤波  安时计量

Research on SOC estimation and parameter identification of the LiFePO_4 Li-ion battery
HOU You-ming,CHEN Qi-gong,JIANG Ming. Research on SOC estimation and parameter identification of the LiFePO_4 Li-ion battery[J]. Journal of Anhui Institute of Mechanical and Electrical Engineering, 2011, 0(2): 55-58
Authors:HOU You-ming  CHEN Qi-gong  JIANG Ming
Affiliation:(Anhui Key Laboratory of Detection Technology and Energy Saving Devices, Anhui Polytechnic University,Wuhu 241000,China)
Abstract:According to the characteristic analysis of the LiFePO_4 Li-ion battery,the battery model was established from the electrochemical angle.The experiment proudes the relationship between E_(OC) and SOC,and the parameters of battery model.The algorithm of kalman filter was used to estimate the initial value of SOC(SOC_0).The electrochemical experiment and simulation shows that the algorithm could estimate the initial value of SOC more efficiently and the error could be controlled by less than ten percent.
Keywords:lithium iron phosphate battery  battery model  state of charge(SOC)  kalman filter  ah counting
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