摘要
动力电池是电动汽车的关键组成部分,其状态参数直接影响电动汽车的性能。电池的荷电状态和健康状态是反映电池运行状态的两个重要参数,由于电池的强非线性,准确地对电池状态的判断有助于电动汽车电池的故障诊断。基于MATLAB/Simulink仿真,建立二阶等效电路模型,通过电容的减少和内阻的增加判断电池的老化程度,采用自适应卡尔曼滤波对电池的SOC和SOH进行估算以此判断电池的工作状态。仿真结果表明,该方法能够实现在线估算,对单体电池进行早期故障诊断,精度较高,确保电动汽车的安全运行。
Power battery is one of the most crucial components in electric vehicle and its battery state parameters can directly affect the performance of vehicles.Battery state of charge and state of health are two of the most important parameters.However,due to the strong nonlinearity of battery,it is significant for fault diagnosis in electric vehicle to accurately estimate battery states.Based on MATLAB/Simulink software in this paper,second-order equivalent circuit battery model is built.The aging of battery,namely SOH,is mainly represented by the capacity degradation and the increase in the internal resistance.Adaptive Extended Kalman Filter is adopted to estimate SOC and SOH,and the simulation result shows it achieves online estimation and judgement of battery working state.It also can be used for fault diagnosis in the early stage of cell battery,and its high accuracy can ensure the security and performance of electric vehicles.
作者
言理
陈康伟
YAN Li;CHEN Kangwei(College of Electronic Information Engineering,Guangdong University of Petrochemical Technology,Maoming 525000,China;Maoming Company SINOPEC,Maoming 525000,China)
出处
《广东石油化工学院学报》
2021年第1期54-58,共5页
Journal of Guangdong University of Petrochemical Technology
基金
茂名市科技计划项目(2017318)
广东石油化工学院科研基金青年创新人才培育项目(2018qn26)。
关键词
电动汽车
动力电池
健康状态
自适应卡尔曼滤波
electrical vehicle
power battery
state of health
Adaptive Extended Kalman Filter
