• DocumentCode
    2855168
  • Title

    Fourier and laplace transform used in pretreatment for neural network battery modeling

  • Author

    Hu, Jialei ; Liu, Changhong ; Li, Xuguang

  • Author_Institution
    Department of Electrical Engineering, Shanghai Jiao Tong University, China
  • Volume
    1
  • fYear
    2012
  • fDate
    2-5 June 2012
  • Firstpage
    172
  • Lastpage
    176
  • Abstract
    To solve the large storage capacity in neural network battery modeling, an input pretreatment, based on Fourier or Laplace transform, is proposed. As simulation shows, the improved battery model gets a better precision and consumes a smaller storage capacity. This method can also be used in SOC estimation if farther experiments are conducted.
  • Keywords
    Batteries; Biological neural networks; Estimation; Laplace equations; Mathematical model; Neurons; System-on-a-chip; Fourier; Laplace; battery model; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Motion Control Conference (IPEMC), 2012 7th International
  • Conference_Location
    Harbin, China
  • Print_ISBN
    978-1-4577-2085-7
  • Type

    conf

  • DOI
    10.1109/IPEMC.2012.6258892
  • Filename
    6258892
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2855168