Modular, Platoon-Based, Vehicle-to-Vehicle Electric Charging Problem
This study introduces an innovative dynamic charging solution, defined as a platoon-based vehicle-to-vehicle charging (P-V2V-C) technology. A fleet of electricity suppliers (ESs) can be deployed to transfer power to other electric vehicles, defined as electricity requests (ERs), while moving in platoon to avoid the detour and delay at a CS. The authors mathematically formulate a mixed integer linear programming (MILP) model for the P-V2V-C problem, along with two fundamental and benchmark operation scenarios with minor simplifications, the electric vehicle routing problem (E-VRP) and electric vehicle platooning problem (E-VPP). The objective is to minimize the total energy consumption and travel time for ERs, including the charging time at CS, platoon formation delay, and wait time for the P-V2V-C service. To solve large-scale P-V2V-C problems for practical scenarios and compare against the E-VRP and E-VPP, the authors propose a set of customized genetic algorithms (GAs) for all three problems to search and identify the routing and charging scheduling of electric vehicles over the evolution of multiple generations. Numerical experiments are tested on the Sioux Falls network for the performance evaluation of the authors' proposed MILP model and GA. In comparison with the E-VRP scenario, the results show that the P-V2V-C technology can save up to 5.86% in energy consumption, 3.78% in travel time and 4.36% in total cost, while the E-VPP does not exhibit much performance improvement overall.
- Record URL:
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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:
- Fu, Zhexi
- Chow, Joseph Y J
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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; Tables;
- Pagination: 21p
Subject/Index Terms
- TRT Terms: Electric vehicle charging; Energy consumption; Genetic algorithms; Mixed integer programming; Traffic platooning; Vehicle to vehicle communications
- Geographic Terms: Sioux Falls (South Dakota)
- Subject Areas: Energy; Highways; Operations and Traffic Management; Vehicles and Equipment;
Filing Info
- Accession Number: 01907075
- Record Type: Publication
- Report/Paper Numbers: TRBAM-24-01959
- Files: TRIS, TRB
- Created Date: Feb 6 2024 1:18PM