Electric Vehicle Usage Pattern Analysis Using Nonnegative Matrix Factorization in Renewable EV-Smart Charging Grid Environment

Anandkumar Balasubramaniam, Thirunavukarasu Balasubramaniam, Anand Paul, HyunCheol Seo and Ravi Samikannu

Mathematical Problems in Engineering, 2022, vol. 2022, 1-9

Abstract: The global utilization of electric vehicles (EVs) is exponentially increasing due to the increased availability of cost-efficient EVs and infrastructure managements for the EVs. In spite of the increasing usage of EVs, the problem of EV usage patterns’ analysis and implementing sustainable infrastructure for the EV transportation is still under development. In addition to this, there is a challenging problem of long waiting hours in traffic signals. This study deals with these problems by proposing an architecture that includes EV usage pattern analysis using nonnegative matrix factorization (NMF) technique and renewable solar-powered wireless smart charging grid to effectively utilize or mitigate the long traffic signal waiting hours. The insights from the EV usage patterns are analyzed and presented showing the importance of usage pattern analysis alongside to the presented architecture of renewable solar-powered wireless EV-smart charging grid. These implementations improvise the usage of the EVs and enhancing the transportation experience, which in turn leads to the development of sustainable smart transportation.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/9365214.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/9365214.xml (application/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9365214

DOI: 10.1155/2022/9365214

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().