ENHANCED REAL TIME CHARGING STATION RECOMMENDATION SYSTEM FOR LOAD BASE ELECTRIC-VEHICLE TAXIS
Abstract
Electric Vehicles(EV) have less air pollution and are more environment friendly, and due to their contribution to carbon dioxide reduction, EVs are becoming increasingly popular nowadays. In the real time charging system, the waiting time can be a non-negligible portion to the total work hours, the decision will naturally affect the revenue of individual EV taxis. The current practice of a taxi driver is to choose a station heuristically without a global knowledge. However the heuristical choice can be a wrong one that leads to more waiting time. The proposed system provides a real-time charging station recommendation system for EV taxis via large-scale GPS data mining. By combining each EV taxi’s historical recharging events and real-time GPS trajectories, the current operational state of each taxi is predicted with Load balancing. Based on this information, for an EV taxi requesting a recommendation, recommend a charging station that leads to the minimal total time before its recharging starts.
Author
Kanmani.L,
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