• DocumentCode
    1704603
  • Title

    Kalman filter based state-of-charge estimation for lithium-ion batteries in hybrid electric vehicles using pulse charging

  • Author

    Yatsui, Mori W. ; Bai, Hua

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Kettering Univ., Flint, MI, USA
  • fYear
    2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The battery is one of the most important energy storage components in EV/HEV. Failing to estimate the state of the charge accurately will bring the risk of overcharge or over discharge. The traditional Coulomb counting method will bring accumulated error over time, therefore high deviation occurs between the estimated and real state of charge. Different estimation strategies are compared in this paper, i.e., Coulomb counting method, open-circuit-voltage method and Kalman filter based state of charge estimation. Experimental results validate the effectiveness of Kalman filter during the on-line application.
  • Keywords
    Kalman filters; battery powered vehicles; hybrid electric vehicles; secondary cells; Coulomb counting method; EV-HEV; Kalman filter; energy storage components; hybrid electric vehicles; lithium-ion batteries; open-circuit-voltage method; pulse charging; state-of-charge estimation; Batteries; Battery charge measurement; Estimation; Kalman filters; Mathematical model; Resistance; System-on-a-chip; Coulomb Counting Method; Kalman Filter; Lithium-ion Battery; Open-circuit-voltage Method; Plug-in Hybrid Electric Vehicle; State of Charge;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicle Power and Propulsion Conference (VPPC), 2011 IEEE
  • Conference_Location
    Chicago, IL
  • ISSN
    Pending
  • Print_ISBN
    978-1-61284-248-6
  • Electronic_ISBN
    Pending
  • Type

    conf

  • DOI
    10.1109/VPPC.2011.6042988
  • Filename
    6042988