Joint Delay and Cost Optimization of In-Route Charging for On-Demand Electric Vehicles
Autor: | Mustafa Ammous, Sameh Sorour, Syrine Belakaria, Ahmed Abdel-Rahim |
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Rok vydání: | 2020 |
Předmět: |
education.field_of_study
Mathematical optimization Control and Optimization business.product_category Queue management system Computer science Population Weighting Artificial Intelligence Server Automotive Engineering Convex optimization Electric vehicle Routing (electronic design automation) education business Average cost |
Zdroj: | IEEE Transactions on Intelligent Vehicles. 5:149-164 |
ISSN: | 2379-8904 2379-8858 |
DOI: | 10.1109/tiv.2019.2955374 |
Popis: | On-Demand electric vehicle (EV) systems are expected to play a significantly increasing role in near future urban transportation systems, to cope with the massive increases in urban population and reduce global carbon emissions. One inconvenience in MoD-EV systems is the need of some customers to perform in-routing charging, which may cause delays in the trip time. Moreover, the customer choice of which station to charge at is an operational issue for the MoD-EV service operator due to the different pricing for the charging at different stations. Given a connected system, we propose a routing scheme that aims to reduce these inconveniences for both customers and the operator. By modeling the routing problem between multiple MoD-EV stations as a multi-server queuing system, we formulate the joint problem of minimizing the average trip time for all customers and the average cost of charging as a dual-objective convex optimization problem. Single and multiple servers per charging stations are considered. Optimal routing decisions are derived analytically for any arbitrary weighting of the two problem objectives and simulation results show the significant merits of our proposed solution as compared to shortest time and random routing decisions. They also illustrate the trade-offs between the two objectives. |
Databáze: | OpenAIRE |
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