| Title |
Framework for optimizing the charging time of electric vehicles in public supply station deployed in smart cities |
| ID_Doc |
40963 |
| Authors |
El-Fedany, I; Kiouach, D; Alaoui, R |
| Title |
Framework for optimizing the charging time of electric vehicles in public supply station deployed in smart cities |
| Year |
2018 |
| Published |
|
| DOI |
|
| Abstract |
The goal of a smart city is to ameliorate the quality of inhabitant's life, reduce pollution, and reduce CO2 emissions, by involving companies, organizations, research institutes, and residents. Electric vehicles, zero emissions of CO2 and acoustics, are certainly fundamental for developing a smart city. This is why administrations and public services direct their choices to electric vehicles. They are ideal for the creation of an eco-sustainable urban environment. However, the capacity of their batteries are limited and the waiting time for users to have their vehicles loaded in public charging stations is greater than the vehicles that use the fuel. Therefore, to meet the challenge of optimizing loading processes in terms of minimizing waiting times, smart cities need a new application that allows charging stations to dynamically interact with vehicles. This article presents a framework for driving and exploring data that is used to identify the status of each charging station according to its location, service number, type of power used, and rate of service. Thus the proposed framework implement an algorithm of the queue, based on the concept of the first comes is the first to be served in order to process the requests of electric vehicles drivers and directed their towards the electric vehicles public supply station who has the minimum waiting. |
| Author Keywords |
Electric vehicle; smart city; queue; waiting time; electric vehicle public supply station; framework |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000462053800095 |
| WoS Category |
Computer Science, Information Systems; Computer Science, Theory & Methods; Engineering, Electrical & Electronic |
| Research Area |
Computer Science; Engineering |
| PDF |
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