• DocumentCode
    3236948
  • Title

    A Rule-Based Energy Management Strategy for a New BSG Hybrid Electric Vehicle

  • Author

    Liu Shaohua ; Du Changqing ; Yan Fuwu ; Wang Jun ; Li Zheng ; Luo Yuan

  • Author_Institution
    Sch. of Automotive Eng., Wuhan Univ. of Technol., Wuhan, China
  • fYear
    2012
  • fDate
    6-8 Nov. 2012
  • Firstpage
    209
  • Lastpage
    212
  • Abstract
    This paper focuses on the analysis of energy management for hybrid electric vehicle of BSG type. A well designed control strategy is a significant factor for obtaining lower fuel consumption, less emission as well as satisfying drivability. To ensure engine operating in the optimal fuel consumption region and coordinate the power split between electrical and mechanical energy sources, an adaptive power splitting algorithm is presented and discussed here on the basis of a new BSG hybrid electric vehicle equipped with both a battery of higher capacity and a motor of higher peak power. Also a smart regenerative braking method is proposed to realize the maximum energy saving purpose. The proposed hybrid electric vehicle (HEV) algorithm simulation results are compared with those of a conventional vehicle with similar configuration as HEV. And the simulation results show that the overall dynamic performance, fuel consumption and emission are all greatly improved.
  • Keywords
    belts; energy conservation; energy management systems; energy resources; hybrid electric vehicles; power dividers; regenerative braking; HEV; adaptive power splitting algorithm; belt driven starter generator; drivability; electrical energy source; fuel consumption; maximum energy saving purpose; mechanical energy source; new BSG hybrid electric vehicle; optimal fuel consumption; power split coordination; rule-based energy management strategy; smart regenerative braking method; well designed control strategy; Batteries; Engines; Fuels; Hybrid electric vehicles; System-on-a-chip; Torque; BSG; HEV; control strategy; simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2012 Third Global Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4673-3072-5
  • Type

    conf

  • DOI
    10.1109/GCIS.2012.63
  • Filename
    6449518