电动汽车锂电池自放电行为的温度特性  

Temperature characteristics of self-discharge behavior of lithium battery in electric vehicles

作　　者：王恩童 刘宗锋 卢纪丽[2] 李瑞川 赵鲁华[1] WANG En-tong;LIU Zong-feng;LU Ji-li;LI Rui-chuan;ZHAO Lu-hua(Shandong University of Science and Technology, Qingdao Shandong 266590, China;Zaozhuang University, Zaozhuang Shandong 277160,China;Rizhao Haizhuo Hydraulic Co.,Ltd.,Rizhao Shandong 276800,China)

机构地区：[1]山东科技大学,山东青岛266590 [2]枣庄学院,山东枣庄277160 [3]日照海卓液压有限公司,山东日照276800

出　　处：《电源技术》2019年第8期1319-1321,1347,共4页Chinese Journal of Power Sources

基　　金：国家“十三五”重点研发项目(2017YFD0700204);山东省重点研发计划项目(2016GGX105008);枣庄市科学技术发展计划项目(2016NS20);山东科技大学教学拔尖人才项目(BJRC20170505)

摘　　要：针对锂电池在不同温度下自放电电量难以直接测量的问题,提出以电压、温度作为间接特征参数构建锂电池放电量的预测模型,间接实现自放电电量的预测。在实验数据分析的基础上,通过高斯曲线对电压与放电量的非线性关系进行拟合,实现温度一定的情况下以电压为特征参数的锂电池放电量的预测;在高斯曲线拟合的基础上,以最小二乘法多项式拟合温度与高斯拟合参数的关系,构建以温度为特征参数的放电量预测模型。基于温度、电压与放电量的关系,间接实现自放电电量的预测。最后通过实验数据验证并评估构建的预测模型,结果表明温度在-40~55℃时,自放电预测值与实际值变化趋势相同,且最大平均相对误差在6%以内,具备较好的预测精度。In order to predict the self-discharge capacity of lithium battery under different temperatures, a prediction model with voltage and temperature as the indirect characteristic parameters was established. The self-discharge capacity of the battery could be predicted indirectly using the proposed model. The nonlinear relationship between the discharge and the voltage was fitted by the least square Gaussian curve based on the experimental data. On this basis, the relationship between temperature and Gaussian fitting parameters was fitted by the least square polynomial, then the prediction model with the characteristic parameters of temperature was established. The self-discharge capacity could be predicted indirectly based on the relationship among temperature, voltage and discharge capacity. The results show that the maximum average relative error is less than 6%when the temperature is from -40 ℃ to 55 ℃. So the prediction model can correctly predict the self-discharge capacity.

关 键 词：电动汽车 自放电电量 间接特征参数 最小二乘法拟合 温度 

分 类 号：TM912.9[电气工程—电力电子与电力传动]