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Electric Vehicle Usage Pattern Analysis Using Nonnegative Matrix Factorization in Renewable EV-Smart Charging Grid Environment
被引:2
|作者:
Balasubramaniam, Anandkumar
[1
]
Balasubramaniam, Thirunavukarasu
[2
]
Paul, Anand
[1
]
Seo, HyunCheol
[3
]
机构:
[1] Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu, South Korea
[2] Queensland Univ Technol, Sch Comp Sci & Ctr Data Sci, Brisbane, Qld, Australia
[3] Kyungpook Natl Univ, Sch Architectural Environm & Energy Engn, Daegu, South Korea
基金:
新加坡国家研究基金会;
关键词:
INTELLIGENT TRANSPORTATION;
D O I:
10.1155/2022/9365214
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
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 oflong waiting hours in traffic signals. This study deals with these problems by proposing an architecture that includes EV usage pattern analysis using non-negative 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.
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页数:9
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