• DocumentCode
    2729728
  • Title

    Statistical analysis of PHEV fleet data

  • Author

    Gong, Qiuming ; Midlam-Mohler, Shawn ; Marano, Vincenzo ; Rizzoni, Giorgio ; Guezennec, Yann

  • Author_Institution
    Center for Automotive Res., Ohio State Univ., Columbus, OH, USA
  • fYear
    2010
  • fDate
    1-3 Sept. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The added load that a PHEV (Plug-in Hybrid Electric Vehicle) fleet imposes on the existing electrical grid is of great concern to the electric utility industry. In this paper, analysis was done for a PHEV fleet which consists of 6 PHEVs that were instrumented using data loggers for a period of approximately one year. Systematic analysis using a clustering approach was carried out for the real world velocity profiles. A driving pattern recognition algorithm was developed based on the clustering of the results and Markov-chain model was used for the stochastic velocity generation for different driving patterns. The work of this paper is a part of a larger project in which a mass simulation of a neighborhood of PHEVs will be conducted based on statistical representations of key factors such as vehicle usage patterns, vehicle characteristics, and market penetration of PHEVs.
  • Keywords
    Markov processes; electricity supply industry; hybrid electric vehicles; power grids; statistical analysis; Markov-chain model; PHEV; clustering approach; electric utility industry; electrical grid; fleet data; pattern recognition algorithm; statistical analysis; stochastic velocity generation; Acceleration; Markov processes; Measurement; Road transportation; System-on-a-chip; Vehicles; PHEV; fleet study; grid interaction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicle Power and Propulsion Conference (VPPC), 2010 IEEE
  • Conference_Location
    Lille
  • Print_ISBN
    978-1-4244-8220-7
  • Type

    conf

  • DOI
    10.1109/VPPC.2010.5729224
  • Filename
    5729224