A traffic-aware electric vehicle charging management system for smart cities. Barbecho Bautista, P., Lemus Cárdenas, L., Urquiza Aguiar, L., & Aguilar Igartua, M. Vehicular Communications, 20:100188, December, 2019.
Paper doi abstract bibtex The expected increase in the number of electric vehicles (EVs) in the coming years will contribute to reducing CO2 pollution in our cities. Currently, EVs' users may suffer from distress due to long charging service times and overloaded charging stations (CSs). Critical traffic conditions (e.g., traffic jams) affect EVs' trip time (TT) towards CSs and thus influence the total trip duration. With this concern, Intelligent transport systems (ITS) and more specifically connected vehicle technologies, can leverage an efficient real-time EV charging service by jointly considering CSs status and traffic conditions in the city. In this work, we propose a scheme to manage EVs' charging planning, focusing on the selection of a CS for the energy-requiring EV. The proposed scheme considers anticipated charging slots reservations performed through a vehicular ad hoc network (VANET), which has been regarded as a cost-efficient communication framework. In specific, we consider two aspects: 1) the EV's total trip time towards its destination considering an intermediate charging at each candidate CS, and 2) the communication delay of the VANET routing protocol. First, in order to estimate the EV's total trip time, our CS selection scheme takes into account the average road speed, traffic lights, and route distance, along the path of the EV. The optimal CS that produces the minimum total charging service time (including the TT) is suggested to that energy-requiring EV. Then, we introduce two communication modes based on geographical routing protocols for VANETs to attain an anticipated charging slot reservation. Simulation results show that with our charging scheme EVs' charging service time is reduced and more EVs are successfully charged.
@article{barbecho_bautista_traffic-aware_2019,
title = {A traffic-aware electric vehicle charging management system for smart cities},
volume = {20},
issn = {2214-2096},
url = {http://www.sciencedirect.com/science/article/pii/S2214209619302359},
doi = {10.1016/j.vehcom.2019.100188},
abstract = {The expected increase in the number of electric vehicles (EVs) in the coming years will contribute to reducing CO2 pollution in our cities. Currently, EVs' users may suffer from distress due to long charging service times and overloaded charging stations (CSs). Critical traffic conditions (e.g., traffic jams) affect EVs' trip time (TT) towards CSs and thus influence the total trip duration. With this concern, Intelligent transport systems (ITS) and more specifically connected vehicle technologies, can leverage an efficient real-time EV charging service by jointly considering CSs status and traffic conditions in the city. In this work, we propose a scheme to manage EVs' charging planning, focusing on the selection of a CS for the energy-requiring EV. The proposed scheme considers anticipated charging slots reservations performed through a vehicular ad hoc network (VANET), which has been regarded as a cost-efficient communication framework. In specific, we consider two aspects: 1) the EV's total trip time towards its destination considering an intermediate charging at each candidate CS, and 2) the communication delay of the VANET routing protocol. First, in order to estimate the EV's total trip time, our CS selection scheme takes into account the average road speed, traffic lights, and route distance, along the path of the EV. The optimal CS that produces the minimum total charging service time (including the TT) is suggested to that energy-requiring EV. Then, we introduce two communication modes based on geographical routing protocols for VANETs to attain an anticipated charging slot reservation. Simulation results show that with our charging scheme EVs' charging service time is reduced and more EVs are successfully charged.},
language = {en},
urldate = {2021-01-26},
journal = {Vehicular Communications},
author = {Barbecho Bautista, Pablo and Lemus Cárdenas, Leticia and Urquiza Aguiar, Luis and Aguilar Igartua, Mónica},
month = dec,
year = {2019},
keywords = {Applications, Electric vehicles (EVs), Intelligent transportation systems, Smart charging service, VANET, Vehicle-to-vehicle},
pages = {100188},
}
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