• DocumentCode
    3110717
  • Title

    A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management

  • Author

    Musardo, Cristian ; Rizzoni, Giorgio ; Staccia, Benedetto

  • Author_Institution
    Center for Automotive Research at the Ohio State University. Research Department at Renault, France (phone: +33 176857995, fax: +33 176857716 e-mail: cristian.musardo@renault.com).
  • fYear
    2005
  • fDate
    12-15 Dec. 2005
  • Firstpage
    1816
  • Lastpage
    1823
  • Abstract
    Hybrid Electric Vehicles (HEV) improvements in fuel economy and emissions strongly depend on the energy management strategy. In this paper a new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented. This real-time energy management for HEV is obtained adding to the ECMS framework an on-the-fly algorithm for the estimation of the equivalence factor according to the driving conditions. The main idea is to periodically refresh the control parameter according to the current road load, so that the battery State of Charge (SOC) is maintained within the boundaries and the fuel consumption is minimized. The results obtained with A-ECMS show that the fuel economy that can be achieved is only slightly sub-optimal and the operations are charge-sustaining.
  • Keywords
    Automotive; Hybrid Electric Vehicle; Optimal Control; Real-time Control; Supervisory Control; Adaptive algorithm; Energy management; Hybrid electric vehicles; Automotive; Hybrid Electric Vehicle; Optimal Control; Real-time Control; Supervisory Control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. 44th IEEE Conference on
  • Print_ISBN
    0-7803-9567-0
  • Type

    conf

  • DOI
    10.1109/CDC.2005.1582424
  • Filename
    1582424