• DocumentCode
    3671679
  • Title

    Traffic light assistant system for optimized energy consumption in an electric vehicle

  • Author

    Emre Kural;Stephen Jones;Alejandro Ferreira Parrilla;Anders Grauers

  • Author_Institution
    AVL Powertrain Engineering, AVL GmbH, Graz, Austria
  • fYear
    2014
  • Firstpage
    604
  • Lastpage
    611
  • Abstract
    Increasingly intelligent vehicle driving systems are rapidly being developed, and will in the future become a necessity for sustainable, convenient and safe mobility in our ever more urbanized world. This paper presents an innovative approach for the control of a fully electric vehicle approaching a road segment with Multiple Traffic Lights (TL). By utilizing Vehicle to Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, the energy consumption for the maneuver completion can be reduced. The problem is approached from a Model Predictive Control (MPC) framework. The performance of the system is evaluated using a complex simulation toolchain representing the vehicle, powertrain, driver, and road including the traffic conditions. The results have shown an overall energy consumption reduction of 29 % for an idealized case and 17 % for a real road simulated scenario as compared to `normal´ human driver behavior.
  • Keywords
    "Acceleration","Mechanical power transmission","Electric vehicles","Mathematical model","Optimization","Predictive models"
  • Publisher
    ieee
  • Conference_Titel
    Connected Vehicles and Expo (ICCVE), 2014 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICCVE.2014.7297619
  • Filename
    7297619