• DocumentCode
    3737601
  • Title

    Battery characterization and state-of-charge prediction for different journey conditions with the help of the "journey mapping" concept

  • Author

    Kavya Prabha Divakarla;Shamsuddeen Nalakath;Martin Drennan;Ryan Ahmed;Ali Emadi;Saiedeh Razavi

  • Author_Institution
    Electrical and Computer Engineering, Department McMaster University, Hamilton, Canada
  • fYear
    2015
  • Firstpage
    3683
  • Lastpage
    3688
  • Abstract
    Electric vehicle battery modeling and state-of-charge prediction has gained a lot of importance with the growing range anxiety among electric vehicle users. The future of battery implementation in electric vehicles might be in their customized design according to specific journey conditions. As such, this paper highlights the application of a novel concept - Journey Mapping for a Ford Focus Electric 2012´s battery characterization and SOC prediction with the help of Genetic Algorithm and the Recursive Least Squares techniques respectively. The Journey Mapping concept, which re-defines driving cycles in order to better capture the journey of a vehicle by including various external conditions such as weather, terrain, traffic, driver behavior, road, aerodynamic and vehicle proved to be a a more accurate testing bed for electric vehicle battery modeling.
  • Keywords
    "Batteries","Vehicles","Integrated circuit modeling","Autoregressive processes","Computational modeling","Roads","Data models"
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, IECON 2015 - 41st Annual Conference of the IEEE
  • Type

    conf

  • DOI
    10.1109/IECON.2015.7392674
  • Filename
    7392674