• DocumentCode
    1644767
  • Title

    Multirate strong tracking extended Kalman filter and its implementation on lithium iron phosphate (LiFePO4) battery system

  • Author

    Jia, J. ; Lin, P. ; Chin, C.S. ; Toh, W.D. ; Gao, Z. ; Lyu, H. ; Cham, Y.T. ; Mesbahi, E.

  • Author_Institution
    Sch. of Eng., Temasek Polytech., Singapore, Singapore
  • fYear
    2015
  • Firstpage
    640
  • Lastpage
    645
  • Abstract
    Lithium Iron phosphate (LiFePO4) battery has obtained extensive attention of researchers for its high energy density, little contamination and ready availability. In this paper, different numbers of RC branches in the equivalent Thevenin circuit model are explored by comparing accuracy of curve fitting with in-house experimental data. Besides, battery system with 6 cells of second order equivalent circuit is modeled using Matlab/Simscape. A multirate strong tracking extended filter (MRSTEKF) is proposed by introducing the multirate control strategy and lifting technology into strong tracking extended Kalman filter (STEKF) to improve tracking stability and estimation precision of state of charge (SOC). Root mean square error (RMSE) is exploited to evaluate the performance of the algorithms of extended Kalman filter (EKF), STEKF and MRSTEKF. Simulation results demonstrate that the proposed MRSTEKF is faster than EKF and STEKF by 55.34% and 49.51%, and is more precise by 52.66% and 33.88%.
  • Keywords
    Kalman filters; curve fitting; equivalent circuits; mean square error methods; nonlinear filters; secondary cells; tracking filters; MRSTEKF; RMSE; SOC estimation; curve fitting; energy density; equivalent Thevenin circuit model; lifting technology; lithium iron phosphate battery system; multirate control strategy; multirate strong tracking extended Kalman filter; root mean square error; state of charge estimation; tracking stability improvement; Batteries; Equivalent circuits; Estimation; Integrated circuit modeling; Kalman filters; Mathematical model; System-on-chip; Battery modeling; Extended Kalman filter (EKF); Lifting technology; Matlab/Simscape; Multirate digital control system; Strong tracking filter (STF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Drive Systems (PEDS), 2015 IEEE 11th International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/PEDS.2015.7203572
  • Filename
    7203572