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Article
IoV-based Deployment and Scheduling of Charging Infrastructure in Intelligent Transportation Systems
IEEE Sensors Journal
  • Waleed Ejaz, Thompson Rivers University
  • Muhammad Naeem, COMSATS University Islamabad
  • Shree Krishna Sharma, University of Luxembourg
  • Asad Masood Khattak, Zayed University
  • Muhammad Rashid Ramzan, COMSATS University Islamabad
  • Amjad Ali, COMSATS Institute of Information Technology
  • Alagan Anpalagan, Ryerson University
Document Type
Article
Publication Date
7-2-2020
Abstract

Internet of vehicles (IoV) is an emerging paradigm to exchange and analyze information collected from sensors using wireless technologies between vehicles and people, vehicles and infrastructure, and vehicles-to-vehicles. With the recent increase in the number of electric vehicles (EVs), the seamless integration of IoV in EVs and charging infrastructure can offer environmentally sustainable and budget-friendly transportation. In this paper, we propose an IoV-based framework that consists of deployment and scheduling of a mobile charging infrastructure. For the deployment, we formulate an optimization problem to minimize the total cost of mobile charging infrastructure placement while considering constraints on the number of EVs that can be charged simultaneously. The formulated problem is mixed-integer programming and solved by using the branch and bound algorithm. We then propose an IoV-based scheduling scheme for EVs charging to minimize travel distance and charging costs while satisfying the constraints of charging time requirement of EVs and resources of a charging station. We consider passive road sensors and traffic sensors in the proposed IoV-based scheduling scheme to enable EV users for finding a charging station that can fulfill their requirements, as well as to enable service providers to know about the demand in the area. Simulation results illustrate the significant impact of the optimal deployment of charging infrastructure and scheduling optimization on the efficiency of EVs charging.

Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Scopus ID

85110730662

Creative Commons License
Creative Commons Attribution-NonCommercial-Share Alike 4.0 International
Indexed in Scopus
Yes
Open Access
Yes
Open Access Type
Green: A manuscript of this publication is openly available in a repository
Citation Information
Waleed Ejaz, Muhammad Naeem, Shree Krishna Sharma, Asad Masood Khattak, et al.. "IoV-based Deployment and Scheduling of Charging Infrastructure in Intelligent Transportation Systems" IEEE Sensors Journal Vol. 21 Iss. 14 (2020) ISSN: <p><a href="https://v2.sherpa.ac.uk/id/publication/issn/1530-437X" target="_blank">1530-437X</a></p>
Available at: http://works.bepress.com/asad-khattak/99/