Spatial Query-Combined Tour Scheduler for Electric Vehicles

Abstract:

This paper designs a spatial data-centric tour and charging scheduler for electric vehicles, which need energy-efficient route planning, especially when visiting multiple destinations, due to their short driving range. Basically, the hybrid orienteering problem solver finds a feasible tour schedule for mandatory user-selected tour spots and optimal system-recommended charging spots, aiming at reducing the waiting time and meeting the given constraint. To recommend essential candidates, our system manages the information on tour spots and charging facilities in the spatial database, adjusting the bounding box size according to the pre-analysis result. The pre-analysis module can implement a sophisticated recommendation logic based on the preprocessed data customized mainly from geographic analysis. In addition, by continuously updating the current status of each charger, the recommender can catch the installation of new charging facilities and exclude the failed or overbooked chargers.

• Periodical: Applied Mechanics and Materials (Volume 686)
• Pages: 612-615
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.686.612
• Online since: October 2014
• Authors: Jung Hoon Lee*, Soo Young Kim
• Keywords: Charger Recommendation, Electric Vehicle (EV), Smart Grid (SG), Spatial Data Analysis, Tour Schedule

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