• DocumentCode
    2655076
  • Title

    Short term power demand forecasting in light- and heavy-duty electric vehicles through linear prediction method

  • Author

    Sangdehi, Mahdi Mousavi ; Iyer, K. Lakshmi Varaha ; Mukherjee, Kaushik ; Kar, Narayan C.

  • Author_Institution
    Centre for Hybrid Automotive Res. & Green Energy, Univ. of Windsor, Windsor, ON, Canada
  • fYear
    2012
  • fDate
    18-20 June 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper a novel method based on linear prediction technique is proposed for short term power demand forecasting in light and heavy-duty electric vehicles for improvement in the overall efficiency of the vehicle. The paper also utilizes filtering of unnecessary information which would have been a major bottleneck in improving the method´s accuracy. The predicted demand function is fed to a wavelet function, which apportions the share between the battery and the ultracapacitor of the considered energy management system. The proposed method is validated with empirical power demand data obtained from on road tests of both light and heavy-duty electric vehicles through numerical investigations.
  • Keywords
    battery powered vehicles; demand forecasting; energy management systems; filtering theory; load forecasting; prediction theory; supercapacitors; battery; demand function prediction; energy management system; heavy-duty electric vehicle; information filtering; light-duty electric vehicle; linear prediction method; short term power demand forecasting; ultracapacitor; wavelet function; Correlation; Energy management; Filtering; Power demand; Power measurement; Predictive models; Vehicles; Energy management system; heavy duty electric vehicles; light duty electric vehicles; linear prediction; predictive control scheme; wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transportation Electrification Conference and Expo (ITEC), 2012 IEEE
  • Conference_Location
    Dearborn, MI
  • Print_ISBN
    978-1-4673-1407-7
  • Electronic_ISBN
    978-1-4673-1406-0
  • Type

    conf

  • DOI
    10.1109/ITEC.2012.6243480
  • Filename
    6243480