• DocumentCode
    1315302
  • Title

    Battery state-of-charge estimation using polynomial enhanced prediction

  • Author

    Unterrieder, Christoph ; Lunglmayr, Michael ; Marsili, Stefano ; Huemer, Mario

  • Author_Institution
    Networked & Embedded Syst., Univ. of Klagenfurt, Klagenfurt, Austria
  • Volume
    48
  • Issue
    21
  • fYear
    2012
  • Firstpage
    1363
  • Lastpage
    1365
  • Abstract
    A novel polynomial-enhanced open-circuit voltage extrapolation method is presented. It is used to identify a battery´s state-of-charge based on the estimation of the corresponding relaxation voltage. The proposed method represents the relaxation process via a polynomial enhanced voltage model, calculated by least squares estimation. Compared to state-of-the-art models, the proposed approach reduces the period of time needed until the state-of-charge can be accurately determined. For the particular cell under test, an open-circuit voltage accuracy of ´1 can be reached within the first 11 minutes of the relaxation process. In addition, the reduced estimation time also leads to a lower power consumption of an integrated circuit-based battery identification solution.
  • Keywords
    extrapolation; least squares approximations; secondary cells; battery state-of-charge estimation; integrated circuit-based battery identification solution; least squares estimation; polynomial-enhanced open-circuit voltage extrapolation method; relaxation process; relaxation voltage; time 11 min;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el.2012.2773
  • Filename
    6329309