Cooperative-driving control for mixed fleets at wireless charging sections for lane changing behaviour
Bin Li,
Xujun Dong and
Jianghui Wen
Energy, 2022, vol. 243, issue C
Abstract:
Recently, electric vehicles (EVs) have become an important traffic tool in connected and automated environments due to their own advantages. However, the optimal driving control strategies of EVs and charging modes of wireless charging lanes are complex since wireless charging technology is limited when EVs are moving and traffic conditions are random. This paper constructs a scenario in which wireless charging facilities are deployed in part of a single lane and proposes a cooperative control method of mixed fleets including EVs and fuel vehicles based on the four objectives of driving safety, traffic efficiency, passenger comfort and energy management. Combined with the particle swarm optimization algorithm, the average driving velocity, lane-changing frequency and location of vehicles under different deployment lengths of charging facilities and mixing ratios are compared to discuss the influence of deployment length on the control effect of energy consumption and traffic efficiency. The numerical results indicate that when the lane length is 1500 m, with the increasing proportion of EVs, the optimal deployment lengths are approximately 700 m, 550 m and 400 m in the case of low traffic density and approximately 550 m, 500 m and 450 m in the case of high traffic density.
Keywords: Cooperative control method of mixed fleet; Particle swarm optimization algorithm; Optimal deployment; Energy consumption (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:243:y:2022:i:c:s0360544221032254
DOI: 10.1016/j.energy.2021.122976
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