Paper Info
Title
A Wireless Charging Facilities Deployment Problem Considering Optimal Traffic Delay and Energy Consumption on Signalized Arterial
Abstract
With the looming promise of wireless recharging technology, electric vehicles (EVs) are going to be able to acquire energy while still in motion. This paper focuses on the optimal deployment of wireless recharging facilities on signalized arterials for EVs. To address this issue, a bi-objective model considering both traffic operation efficiency (i.e., traffic delay saving) and charging infrastructure utilization rate (i.e., electricity gain from charging) has been formulated. A modified cell transmission model (CTM) is used as a base to simulate traffic flow on an arterial with traffic signals. The cells in the CTM also serve as a potential installation site for wireless recharging facilities. The essential goal of this model is to maximize the recharging electricity for EVs traveling on arterials while maintaining low travel delay. Due to the complexity in solving the bi-objective model, heuristic approaches, such as genetic algorithm and particle swarm optimization, are employed. The numerical experiments based on real day-to-day traffic demand are executed. A Pareto set is obtained and a sensitivity analysis regarding recharging rate, investment, and minimum recharging region length is provided.
Year
DOI
Venue
2019
10.1109/TITS.2018.2885635
IEEE Transactions on Intelligent Transportation Systems
Keywords
Field
DocType
Inductive charging,Roads,Wireless communication,Optimization,Delays,Vehicle dynamics
Particle swarm optimization,Heuristic,Traffic flow,Wireless,Simulation,Electricity,Cell Transmission Model,Real-time computing,Engineering,Energy consumption,Genetic algorithm
Journal
Volume
Issue
ISSN
20
12
1524-9050
Citations 
PageRank 
References 
1
0.35
0
Authors
6
Name
Order
Citations
PageRank
Ming Li1222.52
Xinkai Wu271.89
Zhao Zhang310.35
Guizhen Yu44911.52
Yunpeng Wang519425.34
Wanjing Ma6236.51