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Dynamic-Area-Based Shortest-Path Algorithm for Intelligent Charging Guidance of Electric Vehicles

Author

Listed:
  • Junpeng Cai

    (Mathematics and Computer Science College of Fuzhou University, Fuzhou University, Fuzhou 350000, China)

  • Dewang Chen

    (Mathematics and Computer Science College of Fuzhou University, Fuzhou University, Fuzhou 350000, China)

  • Shixiong Jiang

    (Mathematics and Computer Science College of Fuzhou University, Fuzhou University, Fuzhou 350000, China)

  • Weijing Pan

    (Mathematics and Computer Science College of Fuzhou University, Fuzhou University, Fuzhou 350000, China)

Abstract

With the increasing popularization and competition of electric vehicles (EVs), EV users often have anxiety on their trip to find better charging stations with less travel distance. An intelligent charging guidance strategy and two algorithms were proposed to alleviate this problem. First, based on the next destination of EV users’ trip, the strategy established a dynamic-area model to match charging stations with users’ travel demand intelligently. In the dynamic area, the Dijkstra algorithm is used to find the charging station with the shortest trip. Then, the area extension algorithm and the charging station attribution algorithm were developed to improve the robustness of the dynamic area. The two algorithms can automatically adjust the area size according to the number of charging stations in the dynamic area to reduce the number of nodes traversed by the Dijkstra algorithm. Finally, simulation examples were used to verify the effectiveness of the proposed model and algorithms. The results showed that the proposed intelligent charging guidance strategy can meet the travel demand of users. It is a promising technique in smart cities to find better travel trips with less travel distance and less computed time.

Suggested Citation

  • Junpeng Cai & Dewang Chen & Shixiong Jiang & Weijing Pan, 2020. "Dynamic-Area-Based Shortest-Path Algorithm for Intelligent Charging Guidance of Electric Vehicles," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7343-:d:410227
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    References listed on IDEAS

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