The Usage of Big Data in Electric Vehicle Charging: A Comprehensive Review

Liu Wu, Min Liu, Ke Gong (), Liudan Jiao, Xiaosen Huo, Yu Zhang and Hao Wang
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Liu Wu: Department of Engineering, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
Min Liu: Department of Engineering, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
Ke Gong: Department of Engineering, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
Liudan Jiao: Department of Engineering, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
Xiaosen Huo: Department of Engineering, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
Yu Zhang: Department of Engineering, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China
Hao Wang: Department of Engineering, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China

Energies, 2025, vol. 18, issue 19, 1-25

Abstract: With major effects on power grids and people’s lifestyles, the quick uptake of electric vehicles (EVs) poses serious problems for the robustness of charging infrastructure. By enabling spatiotemporally optimal charging strategies that optimize grid operations, big data technologies provide game-changing solutions. In order to solve the following issues, this paper summarizes state-of-the-art applications of EV charging big data, which are derived from vehicles, charging stations, and power grids: (1) optimized control of grid operation; (2) charging infrastructure layout; (3) battery development; and (4) safety of charging equipment. Future research opportunities include: (1) deep integration of intelligent transportation and smart grids; (2) renewable energy and intelligent energy management optimization; (3) synergizing smart homes with EVs; and (4) AI for energy demand forecasting and automated management. This study establishes big data as a pivotal tool for low-carbon EV transition, providing actionable frameworks for researchers and policymakers to harmonize electrified transport with energy sustainability goals.

Keywords: electric vehicle charging; big data; charging infrastructures; power grid; carbon emission (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: 2025
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