• DocumentCode
    3777854
  • Title

    Battery SOC estimation based on multivariate adaptive regression splines

  • Author

    Xing Jin; Bing-Yan Li; Ya-Jun Zhang

  • Author_Institution
    School of Electrical and Electronic Engineering, Chang Chun University of Technology, 130012, China
  • fYear
    2015
  • Firstpage
    111
  • Lastpage
    114
  • Abstract
    The voltage, current and temperature are used as input variables in this paper. The SOC estimation of the lithium iron phosphate battery is achieved by the method of multivariate adaptive regression splines (MARS). The data obtained by the test is standardized, which can be then used in the train of the SOC estimation mathematical model. After that the model is verified. The simulation results show that the proposed method can improve the accuracy of SOC estimation.
  • Keywords
    "Batteries","Mars","State of charge","Estimation","Splines (mathematics)","Discharges (electric)","Adaptation models"
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2015 12th International Computer Conference on
  • Type

    conf

  • DOI
    10.1109/ICCWAMTIP.2015.7493957
  • Filename
    7493957
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3777854