• DocumentCode
    3564694
  • Title

    Decentralized Assignment for Intelligent Electric Vehicles to Recharge Stations

  • Author

    Adacher, Ludovica ; Pascucci, Federica ; Oliva, Gabriele

  • Author_Institution
    Dipt. di Ing., Univ. degli Studi Roma Tre, Rome, Italy
  • fYear
    2014
  • Firstpage
    357
  • Lastpage
    362
  • Abstract
    In this paper the problem of assigning electric cars to charging stations in a distributed manner is addressed, resorting to Lagrangian-based distributed algorithms. Within such algorithms, the routing process is the result of a cooperation among several decision makers, having each one a local knowledge of the system. The decision makers are in charge to decide the type of information to be exchanged. Our focus is to investigate the performance of different algorithms based on different knowledge degrees of the system. The implementation issues and the effectiveness of the algorithms are analysed via simulation. The trade-off between knowledge degree and system performance is currently under study.
  • Keywords
    decision making; distributed algorithms; electric vehicles; vehicle routing; Lagrangian-based distributed algorithms; charging stations; decentralized assignment; electric cars; intelligent electric vehicles; knowledge degree; recharge stations; routing process; system performance; Algorithm design and analysis; Batteries; Charging stations; Distributed algorithms; Electric vehicles; Routing; Decentralized Control; Decomposition methods; Electric Vehicles; Routing algorithms; Scheduling algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on
  • Print_ISBN
    978-1-4799-4923-6
  • Type

    conf

  • DOI
    10.1109/UKSim.2014.63
  • Filename
    7046092