• DocumentCode
    1794543
  • Title

    Fuel Cells Remaining Useful Lifetime Forecasting Using Echo State Network

  • Author

    Morando, S. ; Jemei, S. ; Gouriveau, R. ; Zerhouni, N. ; Hissel, D.

  • Author_Institution
    FC-Lab., Techn´Hom, Belfort, France
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The Hydrogen energy vector is one of the possible solutions to overcome future energy crisis announced by the International Energy Agency. However, various bottleneck, whether technological or societal, slow the industrial interest for this technology and therefore the mass production of fuel cells. Among these locks that may be mentioned one relating to the still limited useful lifetime of the fuel cells. To improve this lifetime, one of the existing approaches is to use the discipline of PHM (for Prognostics and Health Management). This discipline aims to improve the efficiency of control and maintenance operations on the system by using diagnostic or prognostics algorithms. This article covers the prognostics aspect of PHM applied to a PEMFC using an algorithm based on a tool from the reservoir computing discipline to predict the Remaining Useful Lifetime.
  • Keywords
    maintenance engineering; power engineering computing; proton exchange membrane fuel cells; remaining life assessment; PEMFC; control operations; diagnostic algorithms; echo state network; fuel cells remaining useful lifetime forecasting; maintenance operations; prognostics algorithms; prognostics and health management; reservoir computing; Forecasting; Fuel cells; Maintenance engineering; Mathematical model; Neurons; Prognostics and health management; Reservoirs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicle Power and Propulsion Conference (VPPC), 2014 IEEE
  • Conference_Location
    Coimbra
  • Type

    conf

  • DOI
    10.1109/VPPC.2014.7007074
  • Filename
    7007074