• DocumentCode
    153989
  • Title

    Dynamic power demand prediction for battery-supercapacitor hybrid energy storage system of electric vehicle with terrain information

  • Author

    Qiao Zhang ; Weiwen Deng ; Jian Wu ; Feng Ju ; Jingshan Li

  • Author_Institution
    State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
  • fYear
    2014
  • fDate
    8-8 Oct. 2014
  • Firstpage
    82
  • Lastpage
    87
  • Abstract
    Accurate and reliable prediction on power demand is critically important for effective power or energy management for hybrid energy storage systems with battery- super-capacitor for electric vehicles. Terrain information is one of the most common factors on power demand prediction from both driving and regenerative braking. This paper first establishes system dynamic models with battery, super-capacitor and electric motor. Based on these models, the dynamic response and characteristics of battery and super-capacitor are analyzed. Then the system time constant is formulated and studied in order to predict the dynamic power demand for battery-super-capacitor hybrid energy storage system of electric vehicle. Simulation has been conducted to verify that the proposed method in predicting dynamic power demand of electric vehicle is valid.
  • Keywords
    battery powered vehicles; supercapacitors; battery-supercapacitor hybrid energy storage system; dynamic power demand prediction; electric vehicle; terrain information; Batteries; Power demand; Power system dynamics; Roads; Time factors; Vehicle dynamics; battery; hybrid energy storage system; power demand prediction; supercapacitor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Energy Systems (IWIES), 2014 IEEE International Workshop on
  • Conference_Location
    San Diego, CA
  • Type

    conf

  • DOI
    10.1109/IWIES.2014.6957051
  • Filename
    6957051