• DocumentCode
    592292
  • Title

    Adaptive detection of terminal voltage collapses for Li-ion batteries

  • Author

    Mukhopadhyay, Saibal ; Fumin Zhang

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    4799
  • Lastpage
    4804
  • Abstract
    We introduce a novel approach for detecting and predicting terminal voltage collapses in Li-ion batteries without having complete knowledge of a battery model. We present a simplified dynamic model for a Li-ion battery that is forced to track the output voltage curve of a physical Li-ion battery by using universal adaptive stabilization (UAS). We prove that when the physical Li-ion battery becomes unstable, then the simplified dynamic model becomes unstable. Our results do not require a sophisticated model for a battery that faithfully captures all dynamics. Using our results, we present an algorithm for detecting impending voltage collapses for Liion batteries.
  • Keywords
    lithium; secondary cells; Li; UAS; adaptive detection; battery model; lithium-ion batteries; simplified dynamic model; terminal voltage collapses prediction; universal adaptive stabilization; Adaptation models; Batteries; Current measurement; Discharges (electric); System-on-a-chip; Threshold voltage; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-2065-8
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2012.6426223
  • Filename
    6426223