• DocumentCode
    2006759
  • Title

    Optimal fuel control of series-parallel input split hybrid electric vehicle using genetic algorithm based control strategy

  • Author

    Panday, Aishwarya ; Bansal, Hari Om

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Birla Inst. of Technol. & Sci., Pilani, India
  • fYear
    2015
  • fDate
    27-28 March 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The present transportation system heavily relies on of internal combustion engine (ICE) based vehicles. These vehicles emit toxic gases, which results in environmental pollution and create massive health problem. For energy security and greener tomorrow, the concept of hybrid vehicle came into existence. Hybrid vehicles consist of alternative energy storages like fuel-cell, super capacitor, battery or hybrid storage. The presence of two power sources, i.e., engine and battery, makes it necessary to intelligently split the power between them to minimize the fuel consumption. An intelligent controller should be used to split the on road power demand for optimum fuel economy. This article applies a genetic algorithm based controller to toggle between engine and battery. The optimization is based on the selection of vital parameters such as state of charge in the battery, engine on time and power demand. The authenticity and feasibility of proposed controller are verified extensively through numerous simulation results.
  • Keywords
    air pollution; energy security; fuel economy; genetic algorithms; hybrid electric vehicles; intelligent control; internal combustion engines; minimisation; optimal control; road vehicles; ICE; battery power source; energy security; engine power source; environmental pollution; fuel consumption minimization; genetic algorithm based control strategy; intelligent controller; internal combustion engine; massive health problem; optimum fuel economy; road power demand; series-parallel input split hybrid electric vehicle optimal fuel control; toxic gas emission; Batteries; Engines; Fuel economy; Genetic algorithms; Sociology; Statistics; Vehicles; fuel efficiency; genetic algorithm; hybrid electric vehicle; planetary gear; power optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy Economics and Environment (ICEEE), 2015 International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4673-7491-0
  • Type

    conf

  • DOI
    10.1109/EnergyEconomics.2015.7235069
  • Filename
    7235069