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

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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)

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.

Suggested Citation

  • Liu Wu & Min Liu & Ke Gong & Liudan Jiao & Xiaosen Huo & Yu Zhang & Hao Wang, 2025. "The Usage of Big Data in Electric Vehicle Charging: A Comprehensive Review," Energies, MDPI, vol. 18(19), pages 1-25, September.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:19:p:5066-:d:1756591
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