• DocumentCode
    2045412
  • Title

    An H∞ filter based approach for battery SOC estimation with performance analysis

  • Author

    Chen, Yuehang ; Huang, Dagui ; Feng, Daiwei ; Wei, Kaiming

  • Author_Institution
    School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China
  • fYear
    2015
  • fDate
    2-5 Aug. 2015
  • Firstpage
    1613
  • Lastpage
    1618
  • Abstract
    State of charge(SOC) estimation is key to the battery management system used on electric vehicles. Recent studies often focus on the extended Kalman filter method for its theoretically optimal estimation property, but its effectiveness heavily depends on the priori information of noises and high precise battery models, therefore it is unable to deal with complex noises, and tend to fail on extreme environments. A new SOC estimation method using H∞ filter algorithm is presented to estimate SOC online. The algorithm is implemented on a computer, where its performance under different parameters is analysed, and a comparison with Kalman filter showed its robustness against colored noise.
  • Keywords
    Batteries; Estimation; Integrated circuit modeling; Kalman filters; Mathematical model; Noise; System-on-chip; H∞ filter; battery; state of charge;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
  • Conference_Location
    Beijing, China
  • Print_ISBN
    978-1-4799-7097-1
  • Type

    conf

  • DOI
    10.1109/ICMA.2015.7237726
  • Filename
    7237726