Online Electric Vehicle Charging Recommendation: Using Minimum Travel Time Model and Heuristic Search
With the widespread usage of electric vehicles (EVs), issues such as long charging periods and user range anxiety have also gradually emerged due to the randomness and disorderliness of EV charging behavior. Therefore, there is an imperative need to provide online charging recommendation services for EVs, guiding users to make rational arrangements for their charging operations. This paper analyzes the characteristics of EV charging behavior, comprehensively considers the traffic flow conditions and charging pile occupancy status, and constructs an EV charging recommendation model with the objective of minimizing the total travel time for all vehicles. Based on this, a Levy MFO-based charging recommendation algorithm (LMCRA) is proposed, which demonstrates prominent advantages in terms of fitness value, execution time, and average charging time compared to other methods, effectively improving the efficiency of EV charging recommendations.
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Supplemental Notes:
- This paper was sponsored by TRB committee AMS40 Standing Committee on Alternative Fuels and Technologies.
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Corporate Authors:
Transportation Research Board
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Authors:
- Chen, Rumeng
- An, Yisheng
- Mu, Chen
- Li, Ting
- Zhao, Xiangmo
- Gao, Yuxin
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Conference:
- Transportation Research Board 103rd Annual Meeting
- Location: Washington DC
- Date: 2024-1-7 to 2024-1-11
- Date: 2024
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References;
- Pagination: 24p
Subject/Index Terms
- TRT Terms: Computer online services; Electric vehicle charging; Heuristic methods; Information services; Travel time; Vehicle range
- Subject Areas: Data and Information Technology; Energy; Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01908112
- Record Type: Publication
- Report/Paper Numbers: TRBAM-24-01499
- Files: TRIS, TRB
- Created Date: Feb 14 2024 2:33PM