• DocumentCode
    1944303
  • Title

    Maximizing lithium ion vehicle battery life through optimized partial charging

  • Author

    Hoke, Anderson ; Brissette, A. ; Maksimovic, Dragan ; Kelly, Denis ; Pratt, A. ; Boundy, David

  • Author_Institution
    Electr., Comput., & Energy Eng., Univ. of Colorado, Boulder, CO, USA
  • fYear
    2013
  • fDate
    24-27 Feb. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The limited lifetime, high cost, and large size of current lithium ion batteries are some of the primary obstacles to wider adoption of electric vehicles and plug-in hybrid electric vehicles. Simulations presented in this paper predict that Li-ion battery life can be extended through intelligent charging, especially when predictions of next-day energy needs are used to charge the battery only as needed. As-needed charging minimizes battery degradation by minimizing time spent at high state-of-charge. Preliminary results presented here indicate that the battery of a vehicle used for daily commuting and short errands could see its useable life extended by up to 150 % over unoptimized charging.
  • Keywords
    battery powered vehicles; hybrid electric vehicles; lithium; secondary cells; Li; battery degradation; electric vehicles; high state-of-charge; lithium ion vehicle battery life maximization; optimized partial charging; plug-in hybrid electric vehicles; Batteries; Degradation; Mathematical model; Resistance; Sun; System-on-chip; Vehicles; Batteries Electric vehicles; Machine learning algorithms; Numerical simulation; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies (ISGT), 2013 IEEE PES
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4673-4894-2
  • Electronic_ISBN
    978-1-4673-4895-9
  • Type

    conf

  • DOI
    10.1109/ISGT.2013.6497818
  • Filename
    6497818