• DocumentCode
    679410
  • Title

    Do you feel lucky? Why current range estimation methods are holding back EV adoption

  • Author

    Heath, Stuart ; Sant, Paul ; Allen, Ben

  • Author_Institution
    Inst. for Res. into Applicable Comput., Univ. of Bedfordshire, Luton, UK
  • fYear
    2013
  • fDate
    6-7 Nov. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    One challenge facing the adoption of electric vehicles (EVs) is the reduction of the impact of running out of fuel. An EV, with its limited charging point infrastructure and long charge times, is not seen as being as reliable as a conventional car in this respect. To make EVs more acceptable, forward-looking predictive methods of calculating range need to be developed which also take into account opportunities to conserve or harvest energy, as well as environmental factors such as terrain and weather conditions. Using a well-established EV range simulator, this paper describes scenarios showing the limitations of relying on such an approach and the potential detrimental results to both the driver and vehicle´s ability to start and complete a journey. It provides an overview of the research being undertaken by the authors to address these problems, including a description of `Electrikitty´, a road legal pure EV that will be used to gather data to verify the development of novel range estimation algorithms.
  • Keywords
    automobiles; battery powered vehicles; energy conservation; energy harvesting; environmental factors; estimation theory; prediction theory; EV range simulator; Electrikitty description; car; electric vehicle; energy conservation; energy harvesting; environmental factor; forward-looking predictive method; limited charging point infrastructure; range estimation method; terrain condition; weather condition; range anxiety EV battery Peukert supercapacitor;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Hybrid and Electric Vehicles Conference 2013 (HEVC 2013), IET
  • Conference_Location
    London
  • Electronic_ISBN
    978-1-84919-776-2
  • Type

    conf

  • DOI
    10.1049/cp.2013.1893
  • Filename
    6728813