• DocumentCode
    2899734
  • Title

    State of charge estimation of cells in series connection by using only the total voltage measurement

  • Author

    Xinfan Lin ; Stefanopoulou, Anna G. ; Yonghua Li ; Anderson, R. Dyche

  • Author_Institution
    Dept. of Mech. Eng., Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    704
  • Lastpage
    709
  • Abstract
    The voltage of lithium ion batteries is usually monitored to prevent overcharge and overdischarge. For battery packs consisting of hundreds of cells, monitoring the voltage of every single cell adds significant cost and complexity to the battery management system (BMS). Reducing voltage sensing by only measuring the total voltage of multiple cells in series connection is desirable if the state of charge (SOC) of individual cells can be correctly estimated. Such goal cannot be achieved by an extended Kalman filter, because the cell SOCs are not observable in the linearized battery string model. In this paper, an observer based on solving simultaneously multiple nonlinear equations along the trajectory of SOC evolution is used for the estimation problem. Existence of the solution depends on the nonlinearity of the battery voltage-SOC relationship. The observer is applied to a LiFePO4/graphite battery string with 2 cells, where the individual cell SOCs are observable in low and high SOC ranges. Experimental results show good convergence of SOC and voltage estimation, indicating that this new methodology can be applied to, at least, halve the voltage sensing in a battery pack.
  • Keywords
    Kalman filters; battery management systems; graphite; iron compounds; lithium; lithium compounds; nonlinear filters; secondary cells; voltage measurement; BMS; Li; LiFePO4-C; SOC; battery management system; battery packs; battery voltage; charge estimation; extended Kalman filter; graphite battery string; lithium ion batteries; series connection; state of charge; voltage estimation; voltage measurement; voltage sensing; Batteries; Battery charge measurement; Estimation; Integrated circuit modeling; Sensors; System-on-chip; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6579918
  • Filename
    6579918