Scheduling and Routing of Mobile Charging Stations With Stochastic Travel Times to Service Heterogeneous Spatiotemporal Electric Vehicle Charging Requests With Time Windows

Qureshi, Ubaid; Ghosh, Arnob; Panigrahi, Bijaya Ketan

doi:10.1109/tia.2022.3182323

Cited by 31 publications

(1 citation statement)

References 25 publications

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“…In the actual scene, the charging vehicle with limited battery capacity consumes a lot of energy due to moving [7]. In order to reduce the energy consumption of the mobile charging vehicle and ensure that it can return to the service station smoothly to supplement its own energy, the scheduling problem of the mobile charging vehicle has been widely studied [8].…”

Section: Related Workmentioning

confidence: 99%

Research on mobile charging vehicle path planning considering road restrictions

ZHENG

Wang

et al. 2023

International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023)

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In order to alleviate the "power shortage panic" phenomenon caused by the lack of flexibility in the use of fixed charging stations, the introduction of mobile charging vehicles can effectively alleviate the charging problem of electric vehicles and improve the user experience. First, we divide the road network in specific areas, and then forecast the resident traffic volume (OD) data, so as to determine the initial location and distribution of mobile charging vehicles. From the global optimization of the charging time of the mobile charging vehicle at each charging position, ensure that each energy critical sensor is fully charged. At the same time, a mobile charging vehicle path planning algorithm considering the road state is proposed to determine the charging loop of the mobile charging vehicle and the charging time of the corresponding location, so as to minimize the total charging scheduling time on the loop. Finally, the performance of the proposed algorithm is evaluated through simulation experiments. Experimental results show that the proposed algorithm has low energy consumption, strong robustness and excellent performance.

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Section: Related Workmentioning

confidence: 99%