• DocumentCode
    2253904
  • Title

    Cycle life prediction for lithium-ion battery based on GM(1, N) grey model

  • Author

    Tong, Wang ; Naxin, Cui ; Yunlong, Shang ; Chenghui, Zhang

  • Author_Institution
    School of Control Science and Engineering, Shandong University, Jinan 250061, P.R. China
  • fYear
    2015
  • fDate
    28-30 July 2015
  • Firstpage
    4010
  • Lastpage
    4014
  • Abstract
    The accurate prediction of battery life has an important effect on the safe and reliable operation of electric vehicles. The decline of capacity and the increase of resistance indicate the decay of battery life. This paper considers comprehensively the change trends of battery capacity and battery internal resistance, and proposes a battery life prediction model based on GM(1, N) grey theory. The validity of the proposed prediction model is verified by experiments and simulation. The maximum prediction error of the model is less than 30 mAh, and the mean relative error is less than 0.071. GM(1, N) model has the higher prediction accuracy and good robustness than the traditional GM(1,1) model that only considers battery internal resistance. By accurate cycle life prediction, the attenuation trends of battery capacity are acquired, and the accidents caused by invalid batteries are effectively avoided.
  • Keywords
    Accuracy; Analytical models; Batteries; Data models; Mathematical model; Predictive models; Resistance; Battery capacity; Battery internal resistance; GM(1; N) grey model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2015 34th Chinese
  • Conference_Location
    Hangzhou, China
  • Type

    conf

  • DOI
    10.1109/ChiCC.2015.7260258
  • Filename
    7260258