IEEE Transactions on Intelligent Transportation Systems · 2017 · 127 citations · 38 references
EngineeringAutomotive EngineeringTransportation PlanningSchedulingTransportationTransportation EngineeringCharging InfrastructureDistributed SchedulingQueueing AnalysisQueueing SystemsQueueing TheoryVehicle SchedulingControl Of Electric Vehicle ChargingCooperative ControlDistributed Cooperative ControlElectric Vehicle Charging StationsElectric Vehicle SchedulingHighway EngineeringVehicle Queue ManagementWaiting Times
The growing number of electric vehicles on highways demands expanded charging infrastructure, yet limited station capacity leads to variable waiting times across locations. This study proposes a coordination strategy that uses only local traffic and station status information to prevent excessively long waiting times at highway charging stations. A distributed algorithm schedules EV flows to neighboring stations and a decision policy guides individual vehicles on whether to enter the next station, aiming for uniform resource utilization and queue length targets while respecting battery constraints. Simulation on the Florida Turnpike shows that the strategy reduces waiting times and improves charging efficiency.
The increasing number of electric vehicles (EVs) on highways calls for the installment of adequate charging infrastructure. Since charging infrastructure has limited capacity, EVs need to wait at a charging station to get charged, and their waiting times may differ significantly from one location to another. This paper aims at developing a strategy to coordinate the queues among the charging stations, with only local information about traffic flows and the status of EV charging stations along a bidirectional highway, so that excessively long waiting times can be avoided. Specifically, a distributed algorithm is presented to schedule EV flows into neighboring charging stations, so that EVs are all appropriately served along the highway and that all the charging resources are uniformly utilized. In addition, a distributed decision making policy is developed to influence the aggregate number of EVs entering any given service station, so that each EV makes an appropriate decision (i.e., whether or not it should enter the next charging station) by contributing positively to meeting the desired queue length at service stations and by considering its own battery constraint. Performance improvement of the proposed strategy is illustrated via one of the highways in the United States, namely the Florida Turnpike.
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