• DocumentCode
    587396
  • Title

    State of charge estimation of lithium-ion battery using Kalman filters

  • Author

    Baba, Akiya ; Adachi, Shuichi

  • Author_Institution
    Dept. of Appl. Phys. & Physico-Inf., Keio Univ., Yokohama, Japan
  • fYear
    2012
  • fDate
    3-5 Oct. 2012
  • Firstpage
    409
  • Lastpage
    414
  • Abstract
    In this paper we propose an accurate state of charge (SOC) estimation method for a lithium-ion battery for hybrid electric vehicle (HEV) and electric vehicles (EV) use. Although it is important to accurately determine the SOC of a battery to achieve maximum efficiency and safety, none of the existing methods has achieved this perfectly. To address this issue, a model-based approach using a cascaded combination of two Kalman filters, “Series Kalman Filters,” is proposed and implemented. Its validity is verified by performing a series of simulations under a basic HEV operating environment.
  • Keywords
    Kalman filters; hybrid electric vehicles; secondary cells; hybrid electric vehicle; lithium-ion battery; series Kalman filters; state of charge estimation; Accuracy; Batteries; Estimation; Hybrid electric vehicles; Kalman filters; System-on-a-chip; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications (CCA), 2012 IEEE International Conference on
  • Conference_Location
    Dubrovnik
  • ISSN
    1085-1992
  • Print_ISBN
    978-1-4673-4503-3
  • Electronic_ISBN
    1085-1992
  • Type

    conf

  • DOI
    10.1109/CCA.2012.6402456
  • Filename
    6402456