• DocumentCode
    136678
  • Title

    Parameter design and optimization of electric vehicle

  • Author

    Qidong Yin ; Zhongbin Wu ; Xiaoming Rui

  • Author_Institution
    North China Electr. Power Univ., Baoding, China
  • fYear
    2014
  • fDate
    Aug. 31 2014-Sept. 3 2014
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Improving the efficiency of powertrain system is a critical issue for electric vehicle´s technologies. Suitable parameters of this system are beneficial to enhancing the fuel economy and extending the mileage since battery on electric vehicle has a limit of capacity. In this paper, we establish models of vehicle system and components in MATLAB/Simulink to study parameter design for electric vehicle. We apply genetic algorithm in optimizing parameters of the prototype. Control strategy is also discussed to obtain the optimal performance of electric vehicle. We use simulations to test our proposed design. The electric vehicle can meet the requirement of power and fuel economy characteristic. Improvement is obtained through optimizing the parameters of transmission. These results show an agreement between the theory and our design.
  • Keywords
    electric vehicles; fuel economy; genetic algorithms; power transmission (mechanical); MATLAB; Simulink; electric vehicle; fuel economy; genetic algorithm; parameter design; parameter optimization; powertrain system; Atmospheric modeling; Batteries; Biological system modeling; Electric vehicles; Integrated circuit modeling; Torque; electric vehicle; optimum algorithm; parameter design; powertrain system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-4240-4
  • Type

    conf

  • DOI
    10.1109/ITEC-AP.2014.6940949
  • Filename
    6940949