A Hybrid Electric Vehicle Energy Supply System via Direct and Asynchronous V2V Charging Modes

Cui, Jixing, Liu, Shuohan, Cao, Yue, Zhang, Xu ORCID: https://orcid.org/0000-0001-6557-6607, Zhou, Huan and Ren, Xuefeng (2022) A Hybrid Electric Vehicle Energy Supply System via Direct and Asynchronous V2V Charging Modes. In: 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics . The Institute of Electrical and Electronics Engineers (IEEE), CZE, pp. 2056-2061. ISBN 9781665452588

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In recent years, great attention has been paid on Electric Vehicles (EVs) in terms of environmental pollution. Here, EVs can greatly reduce the environmental pollution, compared with traditional Internal Combustion Vehicles (ICVs). However, since EVs cannot be replenished fast like ICVs, the rigid deployment of charging infrastructure and its limited charging capability, leads to service congestion particularly due to a large number of EVs being parked with charging demand. Compared to CSs with rigid extension in location and charging facilitates, the Vehicle-to-Vehicle (V2V) charging service provides a spatial and temporal advance in flexibility, with potential to supplement with G2V charging mode, which can supplement or even replace the G2V Charging Mode. In this paper, we propose a hybrid V2V charging scheme, consisting of direct and asynchronous V2V charging modes, to achieve a great charging flexibility and alleviate the burden for grid load. Here, we estimate the Minimum Waiting Time (MWT) under each mode, as guidance to switch between modes and optimize charging service under each mode. Results show that our proposed hybrid V2V charging scheme outperforms literature works, in terms of average waiting time and number of full charged EVs.

Item Type: Book Section
Additional Information: Funding Information: VII. ACKNOWLEDGEMENT The research is supported in part by the Suzhou Municipal Key Industrial Technology Innovation Program (SYG202123), and Wuhan AI Innovation Program (2022010702040056). Publisher Copyright: © 2022 IEEE.
Uncontrolled Keywords: electrical and electronic engineering,control and systems engineering,human-computer interaction,sdg 12 - responsible consumption and production ,/dk/atira/pure/subjectarea/asjc/2200/2208
Faculty \ School: Faculty of Science > School of Computing Sciences
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Depositing User: LivePure Connector
Date Deposited: 01 Feb 2024 03:18
Last Modified: 01 Feb 2024 03:18
URI: https://ueaeprints.uea.ac.uk/id/eprint/94341
DOI: 10.1109/SMC53654.2022.9945337

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