• DocumentCode
    2844135
  • Title

    Engine power smoothing energy management strategy for a series hybrid electric vehicle

  • Author

    Di Cairano, Stefano ; Liang, W. ; Kolmanovsky, I.V. ; Kuang, M.L. ; Phillips, A.M.

  • fYear
    2011
  • fDate
    June 29 2011-July 1 2011
  • Firstpage
    2101
  • Lastpage
    2106
  • Abstract
    Hybrid electric vehicles exploit energy production and energy storage systems to achieve improved fuel economy with respect to conventional powertrains. In order to maximize such improvements, advanced control strategies are needed for deciding the amount of energy to be produced and stored. In this paper we propose an approach for energy management of a series hybrid electric vehicle (SHEV). This approach focuses on maximizing the pointwise powertrain efficiency, rather than the overall fuel consumption. For a given power request the steady state engine operating point is chosen to maximize the efficiency. A control algorithm regulates the transitions between different operating points, by using the battery to smoothen the engine transients. Due to the constrained nature of the transient smoothing problem, we implement the control algorithm by model predictive control. Experimental testing on the UDDS cycle shows improved fuel economy with respect to two baseline strategies.
  • Keywords
    battery powered vehicles; energy management systems; energy storage; engines; hybrid electric vehicles; power transmission (mechanical); predictive control; UDDS cycle; control algorithm; energy production; energy storage systems; engine power smoothing energy management strategy; engine transients; fuel consumption; fuel economy; model predictive control; pointwise powertrain efficiency; series hybrid electric vehicle; steady state engine operating point; transient smoothing problem; Batteries; Engines; Fuels; Generators; Hybrid electric vehicles; System-on-a-chip; Transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2011
  • Conference_Location
    San Francisco, CA
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4577-0080-4
  • Type

    conf

  • DOI
    10.1109/ACC.2011.5990627
  • Filename
    5990627