Prediction-based charging of PHEVs from the smart grid with dynamic pricing
LCN '10 Proceedings of the 2010 IEEE 35th Conference on Local Computer Networks
Efficient charging station scheduling for an autonomous parking and charging system
Proceedings of the ninth ACM international workshop on Vehicular inter-networking, systems, and applications
Optimal deployment of charging stations for electric vehicular networks
Proceedings of the first workshop on Urban networking
Two-sided online markets for electric vehicle charging
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Energy efficient navigation management for hybrid electric vehicles on highways
Proceedings of the ACM/IEEE 4th International Conference on Cyber-Physical Systems
Intention-aware routing to minimise delays at electric vehicle charging stations
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Environment preservation has become a prominent issue around the world. As traditional internal combustion engine (ICE) vehicles have been major contributors of air pollution, electric vehicles (EVs) are gaining popularity. However, due to the limited electricity supply of battery pack, EVs need to be charged frequently and each charge takes long time. This may degrade travel efficiency and driver comfort. To address this issue, this paper aims to minimize charging waiting time through intelligently scheduling charging activities spatially and temporally. A theoretical study has been conducted to formulate the waiting time minimized charging scheduling problem and derive a performance upper bound (i.e., the theoretical lower bound of charging waiting time). Based on the insights discovered from the theoretical analysis, a practical distributed scheme has been proposed. Extensive simulation results verify that the proposed design can achieve a waiting time near the theoretical lower bound.