• DocumentCode
    1734321
  • Title

    Study on genetic- fuzzy control strategy for PHEV drive system

  • Author

    Ma Xianghua ; Ye Yinzhong

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Shanghai Inst. of Technol., Shanghai, China
  • fYear
    2013
  • Firstpage
    7575
  • Lastpage
    7579
  • Abstract
    To improve the fuel economy for driving system of parallel hybrid electric vehicles, in the paper the genetic algorithm is used to optimize the designed fuzzy controller. It has two input variables, which are the torque difference ΔT and the SOC of battery with one output variable the torque coefficient. The fuzzy control strategy before and after optimization is validated in the CYC CHINA cycle via ADVISOR2002. The simulation results show that the optimized fuzzy controller can further improve fuel economy and reduce the fluctuations of the final value of SOC.
  • Keywords
    control system synthesis; electric drives; fuel economy; fuzzy control; genetic algorithms; hybrid electric vehicles; secondary cells; ADVISOR2002; CYC CHINA cycle; PHEV drive system; battery SOC; driving system; fuel economy improvement; fuzzy controller design; genetic algorithm; genetic-fuzzy control strategy; input variables; optimization; parallel hybrid electric vehicles; torque difference; ADVISOR; Fuzzy logic control; PHEV; genetic algorithm; optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2013 32nd Chinese
  • Conference_Location
    Xi´an
  • Type

    conf

  • Filename
    6640772