• DocumentCode
    2897383
  • Title

    Smart battery adaptive algorithms-system gain calibration elimination by use of adaptive learn cycle in integrated VFC measurement circuit

  • Author

    Bonnett, W. Bruce

  • Author_Institution
    Adv. Analog Products, Texas Instrum. Inc., Dallas, TX, USA
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    311
  • Lastpage
    316
  • Abstract
    Factory calibration is eliminated for system level voltage to charge conversion gain for available charge estimation systems used in rechargeable battery applications, by taking advantage of normalized capacity learning methods. These methods allow the use of state of charge modeling techniques to predict remaining time for portable electronics applications such as talk time on cellular phones or remaining use time on computers, and eliminates the need for absolute units such as amp-hours. One such algorithm is discussed showing how this calibration can be eliminated. Time-of-use estimates are compared and analyzed against laboratory data
  • Keywords
    battery testers; electric current measurement; secondary cells; voltage-frequency convertors; adaptive learn cycle; cellular phone talk time; charge estimation systems; computers; current measurement; gain calibration elimination; integrated VFC measurement circuit; normalized capacity learning methods; portable electronics; rechargeable battery; remaining use time; smart battery adaptive algorithms; time-of-use estimates; Application software; Batteries; Calibration; Cellular phones; Data analysis; Learning systems; Portable computers; Predictive models; Production facilities; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications and Advances, 2001. The Sixteenth Annual Battery Conference on
  • Conference_Location
    Long Beach, CA
  • ISSN
    1089-8182
  • Print_ISBN
    0-7803-6545-3
  • Type

    conf

  • DOI
    10.1109/BCAA.2001.905145
  • Filename
    905145