open access publication

Article, 2024

Advancing Electric Vehicle Infrastructure: A Review and Exploration of Battery-Assisted DC Fast Charging Stations

Energies, ISSN 1996-1073, Volume 17, 13, Page 3117, 10.3390/en17133117

Contributors

Aksoz, Ahmet 0000-0002-2563-1218 (Corresponding author) [1] Asal, Burçak 0009-0003-3729-8170 [2] Biçer, Emre 0000-0002-9871-4102 [3] [4] Oyucu, Saadin 0000-0003-3880-3039 [5] Gençtürk, Merve [3] [4] Golestan, Saeed 0000-0002-8568-1612 (Corresponding author) [6]

Affiliations

  1. [1] Sivas Cumhuriyet University
    2. [NORA names: Turkey; Asia, Middle East; OECD];
  2. [2] Hacettepe University
    3. [NORA names: Turkey; Asia, Middle East; OECD];
  3. [3] Battery Research Laboratory, Faculty of Engineering and Natural Sciences, Sivas University of Science and Technology, 58010 Sivas, Türkiye;, emre.bicer@sivas.edu.tr, (E.B.);, merve.gencturk@sivas.edu.tr, (M.G.)
  4. [4] Sivas University of Science and Technology
    5. [NORA names: Turkey; Asia, Middle East; OECD];
  5. [5] Adıyaman University
    6. [NORA names: Turkey; Asia, Middle East; OECD];

Abstract

Concerns over fossil fuel depletion, fluctuating fuel prices, and CO2 emissions have accelerated the development of electric vehicle (EV) technologies. This article reviews advancements in EV fast charging technology and explores the development of battery-assisted DC fast charging stations to address the limitations of traditional chargers. Our proposed approach integrates battery storage, allowing chargers to operate independently of the electric grid by storing electrical energy during off-peak hours and releasing it during peak times. This reduces dependence on grid power and enhances grid stability. Moreover, the transformer-less, modular design of the proposed solution offers greater flexibility, scalability, and reduced installation costs. Additionally, the use of smart energy management systems, incorporating artificial intelligence and machine learning techniques to dynamically adjust charging rates, will be discussed to optimize efficiency and cost-effectiveness.

Keywords

CO2, CO2 emissions, DC fast charging station, advances, artificial intelligence, battery, battery storage, charger, charging rate, charging stations, concerns, cost, cost-effective, dependence, depletion, design, development, development of electric vehicles, efficiency, electric vehicle infrastructure, electric vehicles, electrical energy, electrical grid, electricity, emission, energy, energy management system, enhance grid stability, exploration, fast charging stations, fast charging technology, flexibility, fluctuating fuel prices, fossil fuel depletion, fuel depletion, fuel prices, grid, grid power, grid stability, hours, infrastructure, installation cost, intelligence, learning techniques, limitations, machine, machine learning techniques, management system, modular design, off-peak hours, optimal efficiency, peak, peak time, power, price, rate, reduce dependence, reduced installation costs, review, review advances, scalability, smart energy management system, solution, stability, stations, storage, system, technique, technology, time, traditional charger, transformer-less, vehicle, vehicle infrastructure

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