Modeling and Analysis of Electric Vehicle User Behavior Based on Full Data Chain Driven

Ruisheng Wang, Qiang Xing, Zhong Chen, Ziqi Zhang and Bo Liu
Additional contact information
Ruisheng Wang: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Qiang Xing: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Zhong Chen: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Ziqi Zhang: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Bo Liu: School of Electrical Engineering, Southeast University, Nanjing 210096, China

Sustainability, 2022, vol. 14, issue 14, 1-19

Abstract: The rapid development of electric vehicles (EVs) has posed challenges to power grids and transportation networks. Accurately capturing the usage patterns of EV users is a prerequisite for EVs’ interaction with electrified transportation networks. Thus, this paper proposes a full data chain (FDC) driven model to mine EVs’ comprehensive characteristics. By collecting the data of 150 private electric vehicles (PREVs), 100 commercial electric vehicles (CEVs), and 50 official electric vehicles (OEVs) in Chongqing, China, the driving characteristics are firstly mined by the adoption of origin-destination (OD) distribution and driving portrait. Moreover, the charging characteristics are extracted based on the state recognition for data chains. Then, vehicle usage characteristics of different types of users are comprehensively described based on the density-based spatial clustering of applications with noise (DBSCAN). Finally, the results of EV user characteristics are analyzed, and the effectiveness of the proposed model is verified by regional charging load analysis and urban road traffic flow comparison. The findings provide a data source and user behavior model for the planning, operation, and control of power grids and transportation networks.

Keywords: electric vehicle; full data chain mining; driving characteristics; charging characteristics; vehicle usage characteristics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/14/8600/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/14/8600/ (text/html)

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:gam:jsusta:v:14:y:2022:i:14:p:8600-:d:862352

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().