• DocumentCode
    29690
  • Title

    A Generalized Powertrain Design Optimization Methodology to Reduce Fuel Economy Variability in Hybrid Electric Vehicles

  • Author

    Roy, Hillol Kumar ; McGordon, Andrew ; Jennings, Paul A.

  • Author_Institution
    WMG, Univ. of Warwick, Coventry, UK
  • Volume
    63
  • Issue
    3
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    1055
  • Lastpage
    1070
  • Abstract
    Hybrid electric vehicles (HEVs) are considered to be one of the energy-efficient technologies for near-term sustainability of the transportation sector. Over the years, research has focused on improving fuel economy (FE) for a given drive cycle, but FE variability over a realistic range of real-world driving patterns has been generally overlooked, and this can lead to FE benefits not being fully realized in real-world usage. No systematic methodology exists to reduce FE variability by design optimization of powertrain components. This study proposes a methodology of powertrain component optimization to reduce the FE variability due to variations in driving patterns. In the proposed methodology, powertrain components are optimum over a range of driving patterns of different traffic conditions and driving styles simultaneously. The proposed methodology demonstrates the potential to reduce FE variability by up to 34% over six driving patterns of different traffic conditions and driving styles.
  • Keywords
    finite element analysis; fuel economy; hybrid electric vehicles; power transmission (mechanical); road traffic; transportation; FE benefits; FE variability; HEV; design optimization; energy-efficient technologies; fuel economy variability; generalized powertrain design optimization methodology; hybrid electric vehicles; near-term sustainability; powertrain component optimization; powertrain components; traffic conditions; transportation sector; variability; Batteries; Engines; Iron; Mechanical power transmission; Optimization; System-on-chip; Vehicles; Batteries; design methodology; genetic algorithms (GAs); internal combustion (IC) engines; motors;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2013.2283749
  • Filename
    6613533