• DocumentCode
    817326
  • Title

    Prognostics in Battery Health Management

  • Author

    Goebel, Kai ; Saha, Bhaskar ; Saxena, Abhinav ; Celaya, Jose R. ; Christophersen, Jon P.

  • Volume
    11
  • Issue
    4
  • fYear
    2008
  • fDate
    8/1/2008 12:00:00 AM
  • Firstpage
    33
  • Lastpage
    40
  • Abstract
    In this article, we examine prognostics and health management (PHM) issues using battery health management of Gen 2 cells, an 18650-size lithium-ion cell, as a test case. We will show where advanced regression, classification, and state estimation algorithms have an important role in the solution of the problem and in the data collection scheme for battery health management that we used for this case study.
  • Keywords
    battery management systems; condition monitoring; maintenance engineering; pattern classification; regression analysis; secondary cells; state estimation; 18650-size lithium-ion cell; Gen 2 cells; battery health management; classification; prognostics and health management; regression; state estimation algorithms; Battery charge measurement; Battery management systems; Battery powered vehicles; Circuit testing; Hybrid electric vehicles; Instruments; Laboratories; Life testing; NASA; Temperature;
  • fLanguage
    English
  • Journal_Title
    Instrumentation & Measurement Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1094-6969
  • Type

    jour

  • DOI
    10.1109/MIM.2008.4579269
  • Filename
    4579269
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=817326