• DocumentCode
    1939425
  • Title

    Applying Management Methodology to Electric Vehicles with Multiple Energy Storage Systems

  • Author

    Rosario, Leon ; Luk, Patrick Chi Kwong

  • Author_Institution
    Cranfield Univ., Shrivenham
  • Volume
    7
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    4223
  • Lastpage
    4230
  • Abstract
    Research in power and energy management of multiple energy systems within electric vehicle (EV) architectures has been undertaken exclusively with scientific methodologies, with varying focuses and degree of success. However, the narrowing vision of scientific quest means other bodies of knowledge like management and economics are being largely ignored in this intriguing multi-discipline of power and energy management. Whilst current research endeavours embracing intelligent control strategies seem to offer some promising results, remarkably no effort is made to exploit well-known management concepts into this field of power management. This paper reports our work as the first to revisit the fundamentals of management concepts, with a view to formulating a novel modular power management framework that is readily implementable to a multi-sourced electric vehicle. Practical results are included to support the validity of the framework.
  • Keywords
    cells (electric); electric vehicles; energy management systems; intelligent control; electric vehicles; energy management; intelligent control; multiple energy storage systems; multiple energy systems; multisourced electric vehicle; power management; Batteries; Conference management; Cybernetics; Electric vehicles; Energy management; Energy storage; Intelligent control; Machine learning; Power system management; Technology management; Batteries; Dual-sourced ultracapacitors; Electric vehicles; Power and energy management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370888
  • Filename
    4370888