• DocumentCode
    2655612
  • Title

    A joint model and SOC estimation method for lithium battery based on the sigma point KF

  • Author

    He, Zhiwei ; Liu, Yuanyuan ; Gao, Mingyu ; Wang, Caisheng

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Hangzhou Dianzi Univ., Hangzhou, China
  • fYear
    2012
  • fDate
    18-20 June 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Lithium-ion batteries have been widely used in electric vehicles (EV). The working state of the battery is very important to the safety of an EV. Online estimation of the state of charge (SOC) is essential in obtaining the battery working conditions. In order to achieve an accurate estimation of the SOC, the battery model should be adjustable when the battery is aged. A joint battery model and SOC estimation method based on the sigma point kalman filter (SPKF) is presented. A combined battery model is used to depict the relationship between the open circuit voltage (OCV) and the SOC of the battery. The main battery model parameter for estimation is the internal resistance and it is jointly estimated with the SOC online. Experimental results show that the SPKF based joint estimation method is effective.
  • Keywords
    Kalman filters; battery powered vehicles; lithium; secondary cells; EV; OCV; SOC estimation method; SPKF based joint estimation method; electric vehicles; joint battery model; lithium-ion battery; open circuit voltage; sigma point Kalman filter; state of charge estimation method; Batteries; Estimation; Joints; Kalman filters; Mathematical model; Resistance; System-on-a-chip; SOC; joint estimation; sigma point kalman filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transportation Electrification Conference and Expo (ITEC), 2012 IEEE
  • Conference_Location
    Dearborn, MI
  • Print_ISBN
    978-1-4673-1407-7
  • Electronic_ISBN
    978-1-4673-1406-0
  • Type

    conf

  • DOI
    10.1109/ITEC.2012.6243505
  • Filename
    6243505