• DocumentCode
    264453
  • Title

    Proton Exchange Membrane Fuel Cells (PEMFC) impedance estimation using regression analysis

  • Author

    Vianna, Wlamir Olivares Loesch ; Paixao de Medeiros, Ivo ; Santos Aflalo, Bernardo ; Ramos Rodrigues, Leonardo ; Pinheiro Malere, Joao Pedro

  • Author_Institution
    EMBRAER S.A., São José dos Campos, Brazil
  • fYear
    2014
  • fDate
    22-25 June 2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper describes the application of the PHM concept to assess the State of Health (SoH) of a Proton Exchange Membrane Fuel Cell (PEMFC) as part of the IEEE PHM 2014 Data Challenge. Two regression approaches are used as health monitoring algorithms to estimate the impedance of the PEMFC. One was a linear regression and the other was a higher order polynomial regression combined with other function found on the literature. The linear regression presented the best results compared to the other method.
  • Keywords
    IEEE standards; condition monitoring; electric impedance measurement; polynomials; proton exchange membrane fuel cells; regression analysis; IEEE PHM 2014 data challenge; PEMFC impedance estimation; PHM concept; SoH; health monitoring algorithm; higher order polynomial regression; linear regression analysis; prognostics and health management; proton exchange membrane fuel cell impedance estimation; state of health; Estimation; Fuel cells; Impedance; Linear regression; Monitoring; Polynomials; Prognostics and health management; Fuel Cells; Health Monitoring; Prognostics; Regression Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Prognostics and Health Management (PHM), 2014 IEEE Conference on
  • Conference_Location
    Cheney, WA
  • Type

    conf

  • DOI
    10.1109/ICPHM.2014.7036404
  • Filename
    7036404