• DocumentCode
    2928379
  • Title

    Research on SOC Hybrid Estimation Algorithm of Power Battery Based on EKF

  • Author

    Wu, Tiezhou ; Chen, Xueguang ; Xia, Fangzhen ; Xiang, Jianfeng

  • Author_Institution
    Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2011
  • fDate
    25-28 March 2011
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Accurate estimation of power battery SOC (state of charge) is the basis of HE V power control strategy. SOC estimation algorithm has a significant impact on the accuracy of SOC estimation. This paper described the basic concept of SOC, discussed the significance of SOC estimation algorithm, difficulties and the main factors affecting SOC estimation, proposed a hybrid battery SOC estimation method with combination of extended Kalman filtering algorithm and improved Ampere Hour (AH) Method based on analyzing existed algorithms. Experimental results show that the hybrid SOC estimation method can meet the accuracy requirement of HEV SOC estimation excellently and is superior to the individual EKF method.
  • Keywords
    Kalman filters; battery chargers; secondary cells; EKF; SOC hybrid estimation algorithm; ampere hour method; extended Kalman filtering algorithm; power battery; power control strategy; state of charge; Batteries; Battery charge measurement; Equations; Estimation; Kalman filters; Mathematical model; System-on-a-chip;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
  • Conference_Location
    Wuhan
  • ISSN
    2157-4839
  • Print_ISBN
    978-1-4244-6253-7
  • Type

    conf

  • DOI
    10.1109/APPEEC.2011.5748464
  • Filename
    5748464