纯电动汽车用锂离子电池的建模和模型参数识别

被引:23
作者
姜久春
文锋
温家鹏
郭宏榆
时玮
机构
[1] 北京交通大学电气工程学院
关键词
锂离子电池; 数学建模; 模型参数识别; 去极化; 最小二乘法拟合;
D O I
暂无
中图分类号
TM912 [蓄电池];
学科分类号
摘要
极化电压是电池状态估算的重要参数,但不能直接测量.采用阻容模型分析,指出极化电压模型阶次与极化深度密切相关,提出一种极化电压的快速识别方法,给出变电流放电情况下电池的去极化时间和容量的计算方法,并采用FUDS模拟工况对新、旧电池和不同厂家的电池进行测试,验证了该方法的有效性和可行性,为电池状态的准确估算提供了数据支持.
引用
收藏
页码:67 / 74
页数:8
相关论文
共 6 条
  • [1] Li-ion battery SOC estimation method based on the reduced order extended Kalman filtering
    Lee, Jaemoon
    Nam, Oanyong
    Cho, B. H.
    [J]. JOURNAL OF POWER SOURCES, 2007, 174 (01) : 9 - 15
  • [2] Rapid test and non-linear model characterisation of solid-state lithium-ion batteries[J] . Suleiman Abu-Sharkh,Dennis Doerffel.Journal of Power Sources . 2004 (1)
  • [3] Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs[J] . Gregory L. Plett.Journal of Power Sources . 2004 (2)
  • [4] Fuzzy logic modelling of state-of-charge and available capacity of nickel/metal hydride batteries
    Singh, P
    Fennie, C
    Reisner, D
    [J]. JOURNAL OF POWER SOURCES, 2004, 136 (02) : 322 - 333
  • [5] Modeling of lithium-ion batteries[J] . John Newman,Karen E. Thomas,Hooman Hafezi,Dean R. Wheeler.Journal of Power Sources . 2003
  • [6] Modeling of High Power Automotive Batteries by the Use of an Automated Test System .2 B. Schweighofer,K.M. Raab,G. Brasseur. IEEE Transactions on Instrumention and Measurement . 2003