• DocumentCode
    3164829
  • Title

    Statistic Driving Cycle Analysis and application for hybrid electric vehicle parametric design

  • Author

    Tan, Di ; Luo, Yutao ; Huang, Xiangdong

  • Author_Institution
    Sch. of Mech.&Auto Eng., South China Univ. of Technol., Guangzhou, China
  • fYear
    2011
  • fDate
    16-18 April 2011
  • Firstpage
    5259
  • Lastpage
    5263
  • Abstract
    An optimal parametric design is the precondition of an excellent performance of a HEV. A novel approach, Statistic Driving Cycles Analysis (SDCA), is put forward. The SDCA is based on the characteristic statistic of the existing driving cycles. In order to analyze the driving cycles commendably, a novel concept, Cycle Block, is put forward correspondingly. By choosing the characteristic parameters to represent the driving cycles, most of the typical driving cycles are statistically analyzed. As a consequence, taking a midsize HEV designing as an example, the optimal parameters are calculated. To evaluate the feasibility of the SDCA method, some simulations are carried out. A stochastic made up driving cycle is used to evaluate the adaptitude of the SDCA method. Further more, the contrastive simulations are carried out to test the advantage of the SDCA method.
  • Keywords
    hybrid electric vehicles; statistical analysis; HEV parametric design; SDCA method; hybrid electric vehicle parametric design; statistic driving cycle analysis; Acceleration; Electric motors; Engines; Fuels; Hybrid electric vehicles; Optimization; Cycle block; Driving cycle; Hybrid electric vehicle; Parametric matching; Statistic analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
  • Conference_Location
    XianNing
  • Print_ISBN
    978-1-61284-458-9
  • Type

    conf

  • DOI
    10.1109/CECNET.2011.5769094
  • Filename
    5769094