• DocumentCode
    630986
  • Title

    A near-optimal power management strategy for rapid component sizing of power split hybrid vehicles with multiple operating modes

  • Author

    Xiaowu Zhang ; Huei Peng ; Jing Sun

  • Author_Institution
    Dept. of Mech. Eng., Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    5972
  • Lastpage
    5977
  • Abstract
    In the design of hybrid vehicles, it is important to identify proper component sizes. When the search space of the design problem is large, exhaustive power management strategy such as dynamic programming (DP) is too time-consuming to be feasible. Instead, a near-optimal method that is orders of magnitude faster than DP is needed. One such near-optimal method is developed and presented in this paper. This method is applied to design an input-split hybrid vehicle utilizing a single planetary gear (PG). There are 6 possible input split configurations, and each configuration has up to 4 modes [1]. Based on the analysis of the efficiency of powertrain components of the four modes, and the “Power-weighted Efficiency” (PE) concept, we show that the computation time for each sizing problem can be reduced by a factor of 10,000 compared with the dynamic-programming based approach.
  • Keywords
    dynamic programming; energy management systems; gears; hybrid electric vehicles; power transmission (mechanical); DP; PE; PG; dynamic programming; multiple operating mode; near-optimal method; near-optimal power management strategy; power split hybrid vehicle; power-weighted efficiency concept; powertrain component; rapid component sizing identification; single planetary gear; Batteries; Engines; Fuels; Gears; Hybrid power systems; Sun; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6580775
  • Filename
    6580775