• DocumentCode
    2016378
  • Title

    State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs

  • Author

    Zhang, Fan ; Rehman, M.Muneeb Ur ; Wang, Hongjie ; Levron, Yoash ; Plett, Gregory ; Zane, Regan ; Maksimovic, Dragan

  • Author_Institution
    CoPEC, ECEE Department, University of Colorado Boulder, Boulder, CO 80309, USA
  • fYear
    2015
  • fDate
    12-15 July 2015
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Cell balancing in large battery packs requires accurate state of charge (SOC) estimation for individual cells. This paper presents a low complexity sigma-point Kalman filter to estimate the state-of-charge (SOC) of Lithium-Ion battery cells. The proposed sigma-point Kalman filter is of 1st order, and can be easily implemented on a simple microcontroller around a dc-dc converter in a modular cell balancing system. The approach is verified experimentally on a battery pack containing twenty-one balancing converters and twenty-one 25 Ah Lithium-Ion cells under high-current (up to 100A) cycling.
  • Keywords
    Batteries; Estimation; Integrated circuit modeling; Kalman filters; Mathematical model; Noise; System-on-chip; BMS; Kalman filter; SOC; battery management; cell balancing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Modeling for Power Electronics (COMPEL), 2015 IEEE 16th Workshop on
  • Conference_Location
    Vancouver, BC, Canada
  • Type

    conf

  • DOI
    10.1109/COMPEL.2015.7236525
  • Filename
    7236525