• DocumentCode
    3413791
  • Title

    An adaptive algorithm of NiMH battery state of charge estimation for hybrid electric vehicle

  • Author

    Qiang, JiaXi ; Ao, Guoqiang ; He, Jianhui ; Chen, Ziqiang ; Yang, Lin

  • Author_Institution
    Sch. of Mech. Eng., Shanghai Jiaotong Univ., Shanghai
  • fYear
    2008
  • fDate
    June 30 2008-July 2 2008
  • Firstpage
    1556
  • Lastpage
    1561
  • Abstract
    An adaptive algorithm for battery state of charge (SOC) estimation is presented in this paper to solve the critical issue of calculating the remaining energy of battery in hybrid electric vehicle (HEV). To obtain a more accurate SOC estimation value, both coulomb-accumulation and open-circuit voltage contributions are considered in this study. The extended Kalman filter (EKF) theory which has good adaptability is used respectively in these two contributions. The adaptive control effectiveness is achieved in two aspects: one is the application of Kalman filter which can filter the noise of voltage and current measurement and the other is the open-circuit voltage correction when the battery is in steady state to compensate the deficiencies of coulomb-accumulation. The test results show this adaptive algorithm has high robust property, noise-immune ability and accuracy which is suitable for HEV application.
  • Keywords
    Kalman filters; hybrid electric vehicles; nickel; nonlinear filters; secondary cells; system-on-chip; HEV; Ni; adaptive control; coulomb-accumulation; extended Kalman filter; hybrid electric vehicle; noise-immune ability; open-circuit voltage; open-circuit voltage correction; state of charge estimation; voltage-current measurement; Adaptive algorithm; Adaptive control; Adaptive filters; Batteries; Current measurement; Hybrid electric vehicles; State estimation; Steady-state; Testing; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 2008. ISIE 2008. IEEE International Symposium on
  • Conference_Location
    Cambridge
  • Print_ISBN
    978-1-4244-1665-3
  • Electronic_ISBN
    978-1-4244-1666-0
  • Type

    conf

  • DOI
    10.1109/ISIE.2008.4677229
  • Filename
    4677229