• DocumentCode
    2911940
  • Title

    Battery state-of-charge estimation based on H filter for hybrid electric vehicle

  • Author

    Yan, Jingyu ; Xu, Guoqing ; Xu, Yangsheng ; Xie, Benliang

  • Author_Institution
    Inst. of Adv. Integration Technol., Chinese Acad. of Sci., Shenzhen
  • fYear
    2008
  • fDate
    17-20 Dec. 2008
  • Firstpage
    464
  • Lastpage
    469
  • Abstract
    State-of-charge (SOC) estimation is the most difficult problem in battery management system, which is one of the key component of electric vehicle and hybrid electric vehicle. Suffered from the non-zero mean noise and uncertain model parameters in practice, the conventional current integral and Kalman filter estimation methods can not achieve the required accuracy, even causing nonconvergent results. The essential difficulties to apply current integral and Kalman filter to solve SOC estimation problem in colored noise and time-variant battery system are analyzed. Hinfin filter, an estimator designed to handle the estimation problem in noised and uncertain situation, is then applied to calculate SOC online. The simulation experiment based on a typical battery model verifies the availability and efficiency of the proposed method.
  • Keywords
    Kalman filters; battery management systems; estimation theory; hybrid electric vehicles; Hinfin filter; Kalman filter estimation methods; battery management system; battery state-of-charge estimation; conventional current integral estimation methods; electric vehicle; hybrid electric vehicle; nonzero mean noise; uncertain model parameters; Automotive engineering; Battery charge measurement; Battery management systems; Colored noise; Current measurement; Filters; Hybrid electric vehicles; Robotics and automation; State estimation; Working environment noise; Battery management; H filter; State of charge; system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
  • Conference_Location
    Hanoi
  • Print_ISBN
    978-1-4244-2286-9
  • Electronic_ISBN
    978-1-4244-2287-6
  • Type

    conf

  • DOI
    10.1109/ICARCV.2008.4795563
  • Filename
    4795563