Research on the Operation Modes of Electric Vehicles in Association with a 5G Real-Time System of Electric Vehicle and Traffic

Weihua Wu, Yifan Zhang, Dongphil Chun, Yu Song, Lingli Qing, Ying Chen and Peng Li
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Weihua Wu: Graduate School of Management of Technology, Pukyong National University, Busan 48513, Korea
Yifan Zhang: School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China
Dongphil Chun: Graduate School of Management of Technology, Pukyong National University, Busan 48513, Korea
Yu Song: Graduate School of Management of Technology, Pukyong National University, Busan 48513, Korea
Lingli Qing: Graduate School of Management of Technology, Pukyong National University, Busan 48513, Korea
Ying Chen: Graduate School of Management of Technology, Pukyong National University, Busan 48513, Korea
Peng Li: Graduate School of Management of Technology, Pukyong National University, Busan 48513, Korea

Energies, 2022, vol. 15, issue 12, 1-17

Abstract: With the popularity of 5G technology and electric vehicles, many countries around the world have adopted 5G technology to build sustainable smart city systems, and intelligent transportation is an important part of smart cities. From the perspective of 5G technology innovation bringing changes to traditional industries, in this paper, we analyze the mechanism by which 5G technology drives the transformation and upgrading of the electric vehicle industry. Based on the changes brought by 5G technology to the three industries of agriculture, industry and services, we analyzed the transformation of business models brought about by 5G with respect to electric vehicle operation. Furthermore, we analyzed the data of a 5G real-time system of electric vehicle and traffic operating in Nanjing, China, for a month in 2021, with a total of 10,610 electric vehicles and 1,048,575 cases to model the modes of electric vehicle operation associated with the platform. Based on the frequency density method, we identified three typical operating modes of urban electric vehicles: private electric vehicle use instead of walking accounts for 24.8%, passenger vehicles (Uber/Didi and taxi) account for 64.4% and logistic distribution electric vehicles account for 10.8%. We developed a method to automatically identify the operating mode of electric vehicles using data from a 5G real-time electric vehicle traffic platform, which provide a reference for the operation of electric vehicles associated with the platform. This work also provides data that can be used to support the establishment of models for the commercial operation of charging points.

Keywords: 5G technology; EV operation mode; 5gRTS-ET (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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