• DocumentCode
    181937
  • Title

    On-road PHEV power management with hierarchical strategies in vehicular networks

  • Author

    Bingnan Jiang ; Yunsi Fei

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA
  • fYear
    2014
  • fDate
    8-11 June 2014
  • Firstpage
    1077
  • Lastpage
    1084
  • Abstract
    In plug-in hybrid electric vehicles (PHEVs), the power management system coordinates powertrain operations to achieve high energy efficiency. Conventional PHEV power management systems work in either an online or offline mode. Most online systems are based on some pre-set power balancing strategies without utilizing the driving cycle or route information. Offline management strategies solved from historical driving cycles are not optimal for real specific driving routes. With the rapid development of vehicular networks and proliferation of smartphones, real-time traffic information can be collected by smartphones from a vehicular network so as to facilitate online PHEV power management. This paper proposes an on-road PHEV power management cyber-physical system (CPS) with 2-level hierarchical optimizations to minimize the fuel consumption of a trip. The high-level online stochastic optimization generates a battery energy budget for each road at runtime according to the traffic prediction and trip information. The low-level powertrain policies are solved offline from historical driving cycles. During driving, the high-level battery energy budgets and low-level policies are combined to get the optimal power decisions according to current driving states. Simulation results show that the proposed method significantly outperforms other three methods in fuel savings.
  • Keywords
    hybrid electric vehicles; optimal control; optimisation; power control; road traffic control; road vehicles; CPS; battery energy budget generation; cyber-physical system; fuel consumption minimization; hierarchical optimizations; hybrid electric vehicles; on-road PHEV power management system; online stochastic optimization; optimal power decisions; powertrain policies; road traffic prediction; vehicular networks; Batteries; Fuels; Ice; Mechanical power transmission; Optimization; Roads; Torque;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium Proceedings, 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/IVS.2014.6856597
  • Filename
    6856597