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Volume 40 Issue 6
Jun.  2014
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Journal of Beijing University of Aeronautics and Astronautics  > 2014  >  40(6): 855-860.
Xu Ying, Shen Ying. Improved battery state-of-charge estimation based on Kalman filter[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(6): 855-860. doi: 10.13700/j.bh.1001-5965.2013.0414(in Chinese)
Citation: Xu Ying, Shen Ying. Improved battery state-of-charge estimation based on Kalman filter[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(6): 855-860. doi: 10.13700/j.bh.1001-5965.2013.0414(in Chinese)
shu

Improved battery state-of-charge estimation based on Kalman filter

doi: 10.13700/j.bh.1001-5965.2013.0414

  • School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • Received Date: 11 Jul 2013
  • Publish Date: 20 Jun 2014
    Abstract
  • Set in the research in the battery management system of electric vehicle, the state of charge, as well as the main factors to their nonlinear dynamic relationship, was illustrated and a second-order RC equivalent cell model was established based on the key technology of battery state of charge estimation. After taking the influence of temperature on the battery internal resistance into account, the state of charge of the battery was estimated with Kalman filter algorithm, the improved Ah counting method and the open-circuit voltage method, combined with the online thermal model parameters identification. MATLAB simulation shows that the average error was 2.46% compared with the conventional Kalman filter algorithm, which verifies the feasibility and reliability.

     

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    • References(8)
  • [1]
    吴红杰,齐铂金, 郑敏信,等.基于Kalman滤波的镍氢动力电池SOC估算方法[J].北京航空航天大学学报,2007,33(8):945-948 Wu Hongjie,Qi Bojin,Zheng Minxin,et al.Ni-MH battery state-of-charge estimation based on Kalman filter[J].Journal of Beijing University of Aeronautics and Astronautics,2007,33(8):945-948(in Chinese)
    [2]
    He H,Xiong R, Fan J.Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach[J].Energies,2011,4(4):582-598
    [3]
    Lee J, Nam O,Cho B H.Li-ion battery SOC estimation method based on the reduced order extended Kalman filtering[J].Journal of Power Sources,2007,174(1):9-15
    [4]
    Di Domenico D, Fiengo G,Stefanopoulou A.Lithium-ion battery state of charge estimation with a kalman filter based on a electrochemical model[C]//Proceedings of the IEEE International Conference on Control Applications. New York:Institute of Electrical and Electronics Engineers Inc,2008:702-707
    [5]
    Wu T,Liu L, Xiao Q,et al.Research on SOC estimation based on second-order RC model[J].Telkomnika:Indonesian Journal of Electrical Engineering,2012,10(7):1667-1672
    [6]
    魏学哲,邹广楠, 孙泽昌.燃料电池汽车中电池建模及其参数估计[J].电源技术,2004,28(10):605-608 Wei Xuezhe,Zou Guangnan,Sun Zechang.Modelling and parameter estimation of Li-ion battery in a fuel cell vehicle[J].Journal of Power Sources,2004,28(10):605-608(in Chinese)
    [7]
    李哲,韩雪冰, 卢兰光,等.动力型磷酸铁锂电池的温度特性[J].机械工程学报,2011,47(18):115-120 Li Zhe,Han Xuebing,Lu Languang,et al.Temperature characteristics of power LiFePO4 batteries[J].Journal of Mechanical Engineering,2011,47(18):115-120(in Chinese)
    [8]
    徐杰. 基于卡尔曼滤波的动力电池组SOC精确估计[D].杭州:杭州电子科技大学,2009 Xu Jie.State of charge accuate estimation based on Kalman filtering for power battery[D].Hangzhou:Hangzhou Dianzi University,2009(in Chinese)
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