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    Map-based linear estimation of drive cycle for hybrid electric vehicles

    Access Status
    Fulltext not available
    Authors
    Nejad, Arash Zargham
    Deilami, Sara
    Masoum, Mohammad Sherkat
    Haghdadi, N.
    Date
    2015
    Type
    Conference Paper
    
    Metadata
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    Citation
    Nejad, A. and Deilami, S. and Masoum, M.S. and Haghdadi, N. 2015. Map-based linear estimation of drive cycle for hybrid electric vehicles. In 2015 Australasian Universities Power Engineering Conference: Challenges for Future Grids (AUPEC 2015), 27-30 Sept. 2015: IEEE.
    Source Title
    2015 Australasian Universities Power Engineering Conference: Challenges for Future Grids, AUPEC 2015
    DOI
    10.1109/AUPEC.2015.7324873
    ISBN
    9781479987252
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/49904
    Collection
    • Curtin Research Publications
    Abstract

    Applications of hybrid electric vehicles (HEVs) and plug-in electric vehicles (PEVs) in modern power grids are increasing due to the growing concerns about environmental issues and unpredictable fuel prices. However, detailed information on drivers' behaviors which is required for vehicle control and management is not widely available. This paper presents a map-based linear estimation approach to estimate the drive cycles of hybrid electric vehicles (HEVs). It is shown that knowing geological data of the vehicle, a linear estimation of drive cycle is possible. Detailed simulations are presented to investigate the accuracy of the linear estimation compared with the real drive cycles. Simulation results are presented and analyzed for the linear estimations of two typical drive cycles including the highway fuel economy test (HWFET) cycle and the New York City cycle (NYCC).

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