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Original scientific paper

https://doi.org/10.17559/TV-20231123001145

Enhancing the Electrified Transportation System with the IOT Tools Placed Around a City

Naoufel Zitouni ; Laboratory of Applications of Energy Efficiency and Renewable Energies, UR-LAPER, Faculty of Sciences of Tunis, Tunis El Manar University, Tunisia
Aymen Flah ; A) Processes, Energy, Environment, and Electrical Systems (code: LR18ES34), National Engineering School of Gabès, University of Gabès, Tunisia, B) MEU Research Unit, Middle East University, Amman, Jordan C) College of Engineering, University of Business and Technology (UBT), Jeddah 21448, Saudi Arabia D) The private higher school of applied sciences and technlogie of gabes, university of Gabes, Tunisia. E) Applied Science Research Center, Applied Science Private University, Amman, 11931, Jordan; flahaymening@yahoo.fr (F.A.)
Habib Kraiem ; Department of Electrical Engineering, College of Engineering, Northern Border University, Arar, Saudi Arabia *
Claude Ziad El Bayeh ; Department of Electrical Engineering, Bayeh Institute, 55 Kfar Saleh-Hay El Arbe Street, Amchit, Mount Lebanon, Lebanon

* Corresponding author.


Full text: english pdf 630 Kb

page 1959-1967

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Abstract

Electric vehicles and smart city concepts based on IoT tools seem to be high-technology solutions that impact the transportation system, road safety, and road management sectors. In a big city where the number of vehicles is high, and the city roads are close and overlapped, road safety and vehicle management seem difficult. This is why one of the major solutions needs to use high-technology sensors based on IoT equipment and technology. In this context, this paper is exposed in order to use the benefit of the smart city, based on the IoT technology for enhancing the electric vehicle energy consumption mode, and this is by controlling the vehicle trajectory from two points in a road. The principle of the proposed work is based on the neural network concept, which uses a large database of information for making learning in order to find the optimum trajectory from various similar cars that have used the same trajectory for moving from position A to position B. The simulation was made on Matlab Simulink platform and the results were then exposed and discussed.

Keywords

buildings; neural network; optimization; power management; storage system efficiency; transportation sector, vehicle to sensors

Hrčak ID:

321918

URI

https://hrcak.srce.hr/321918

Publication date:

31.10.2024.

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