Data Drive—Charging Behavior of Electric Vehicle Users with Variable Roles

Weihua Wu; Jieyun Wei; Eun Young Nam; Yifan Zhang; Dongphil Chun

doi:10.3390/su16114842

Data Drive—Charging Behavior of Electric Vehicle Users with Variable Roles

Weihua Wu, Jieyun Wei, Eun Young Nam, Yifan Zhang, Dongphil Chun

Department of Global Trade

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

The global proliferation of electric vehicles (EVs) has brought forth new challenges in electric vehicle (EV) charging infrastructure. This paper utilizes operational data from the 5G real-time system of EV and traffic platforms (5gRTS-ET) in China, encompassing 12,597,109 cases and 32,259 EVs. By employing frequency density analysis, a dynamic charging behavior model is devised to address the limitations of static models in accommodating the diverse roles of EV users. Analysis reveals distinct charging behavior preferences among three urban EV operation modes, paving the way for an adaptive model for integrating charging points into networked operations on the platform.

Original language	English
Article number	4842
Journal	Sustainability (Switzerland)
Volume	16
Issue number	11
DOIs	https://doi.org/10.3390/su16114842
State	Published - Jun 2024

Keywords

5G
charging behavior
charging point
EV

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/su16114842

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title = "Data Drive—Charging Behavior of Electric Vehicle Users with Variable Roles",

abstract = "The global proliferation of electric vehicles (EVs) has brought forth new challenges in electric vehicle (EV) charging infrastructure. This paper utilizes operational data from the 5G real-time system of EV and traffic platforms (5gRTS-ET) in China, encompassing 12,597,109 cases and 32,259 EVs. By employing frequency density analysis, a dynamic charging behavior model is devised to address the limitations of static models in accommodating the diverse roles of EV users. Analysis reveals distinct charging behavior preferences among three urban EV operation modes, paving the way for an adaptive model for integrating charging points into networked operations on the platform.",

keywords = "5G, charging behavior, charging point, EV",

author = "Weihua Wu and Jieyun Wei and Nam, {Eun Young} and Yifan Zhang and Dongphil Chun",

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AU - Zhang, Yifan

AU - Chun, Dongphil

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AB - The global proliferation of electric vehicles (EVs) has brought forth new challenges in electric vehicle (EV) charging infrastructure. This paper utilizes operational data from the 5G real-time system of EV and traffic platforms (5gRTS-ET) in China, encompassing 12,597,109 cases and 32,259 EVs. By employing frequency density analysis, a dynamic charging behavior model is devised to address the limitations of static models in accommodating the diverse roles of EV users. Analysis reveals distinct charging behavior preferences among three urban EV operation modes, paving the way for an adaptive model for integrating charging points into networked operations on the platform.

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KW - charging point

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Data Drive—Charging Behavior of Electric Vehicle Users with Variable Roles

Abstract

Keywords

UN SDGs

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