Optimizing Electric Vehicle Charging with Charging Data Analytics

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Optimizing Electric Vehicle Charging with Charging Data Analytics

Khanam, Tayyibah / Kaushik, Ivanshu / Alam, Mohammad Saad / Deb, Sanchari / Rafat, Yasser

Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the summation of time taken to reach the charging stations and the waiting times for available chargers. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city to assist the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application.

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Document information

Title :

Optimizing Electric Vehicle Charging with Charging Data Analytics

Additional title:

Lect. Notes Electrical Eng.

Contributors:

Pillai, Reji Kumar (editor) / Singh, B. P. (editor) / Murugesan, N. (editor) / Khanam, Tayyibah (author) / Kaushik, Ivanshu (author) / Alam, Mohammad Saad (author) / Deb, Sanchari (author) / Rafat, Yasser (author)

Published in:

ISUW 2021 ; Chapter : 44 ; 405-413

Lecture Notes in Electrical Engineering ; 843

Publication date :

2022-05-28

Size :

9 pages

ISBN :

978-981-16-8727-3 , 978-981-16-8726-6

ISSN :

1876-1119 , 1876-1100

DOI :