A Charging Station Recommendation System for Electric Vehicles using Big Data Analysis

As Electric vehicles (EVs ) become popular, the authors expect EV charging stations especially on highways will be over-crowded because charging an EV takes a long time and continuous mileage of an EV is short. In order to balance the load of EV charging stations, the authors have proposed EV charging station recommendation systems which recommends appropriate EV charging stations to EV drivers. This system analyzes big data such as time series data of traffic and weather stored over a long period of time, and extracts useful rules to predict the average velocity, electricity efficiency of EVs on each road link and so on. Thus , the system can be adapted to the latest environment. This paper proposes big data analysis techniques applied to the EV charging station recommendation system, and shows numerical experimental results where the number of waiting EVs at EV charging stations decreased.

  • Availability:
  • Supplemental Notes:
    • Abstract used with permission of ITS Japan. Paper No. 3307.
  • Corporate Authors:

    ITS Japan

    Tokyo,   Japan 
  • Authors:
    • Kano, Makoto
    • Kawano, Shin-ichiro
    • Une, Yasuomi
    • Suzuki, Hiroyuki
    • Yamamoto, Junichi
    • Shimada, Tsuyoshi
  • Conference:
  • Publication Date: 2013


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 10p
  • Monograph Title: 20th ITS World Congress, Tokyo 2013. Proceedings

Subject/Index Terms

Filing Info

  • Accession Number: 01535395
  • Record Type: Publication
  • ISBN: 9784990493981
  • Files: TRIS
  • Created Date: Aug 21 2014 5:01PM