• DocumentCode
    710320
  • Title

    Decision on prognosis approaches of Hybrid Electric Vehicles´ electrical machines

  • Author

    Ginzarly, Riham ; Hoblos, Ghaleb ; Moubayed, Nazih

  • Author_Institution
    IRSEEM, ESIGELEC, Rouen, France
  • fYear
    2015
  • fDate
    April 29 2015-May 1 2015
  • Firstpage
    175
  • Lastpage
    180
  • Abstract
    Hybrid Electric Vehicles (HEV) are becoming widely spread due to the predicted lack of fuel in addition to the pollution caused by the conventional vehicles. To overcome pollution and since it is expected that the lack of fuel will more increase, it is assessed that the production and use of HEVs will increase in the coming years. The main concern of HEVs is their reliability and availability; hence, assuring the health and proper operation of HEVs is a mission. Due to the importance of electrical machines health state in HEVs, this paper will present a survey on the available prognostic techniques that may be applied to assure an optimal and convenient operation of electrical machines in hybrid electric vehicle.
  • Keywords
    electric machines; hybrid electric vehicles; pollution; HEV; electrical machines; hybrid electric vehicles; prognosis approaches; prognostic techniques; Adaptation models; Data models; Hidden Markov models; Hybrid electric vehicles; Mathematical model; Neural networks; Prognostics and health management; Prognosis; electrical machine; hybrid electric vehicle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), 2015 Third International Conference on
  • Conference_Location
    Beirut
  • Print_ISBN
    978-1-4799-5679-1
  • Type

    conf

  • DOI
    10.1109/TAEECE.2015.7113622
  • Filename
    7113622