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Energies
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Advancements in Electric Vehicle (EV) Charging for a Sustainable Future
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Advancements in Electric Vehicle (EV) Charging for a Sustainable Future

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (13 December 2024) | Viewed by 6658

Special Issue Editor

Dr. Zahra Hajabdollahi

E-Mail Website
Guest Editor
James Watt School of Engineering, University of Glasgow, Glasgow, UK
Interests: power and energy systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are excited to announce a special issue of our journal, dedicated to "Advancements in Electric Vehicle (EV) Charging for a Sustainable Future." As EVs revolutionize transportation, this special issue aims to showcase cutting-edge research, innovations, and insights into EV charging infrastructure and technology. We invite researchers, experts, and practitioners to contribute their work in advancing sustainable and efficient charging solutions, with a focus on reducing environmental impact and supporting the global transition towards cleaner mobility. Join us in shaping the future of EV charging systems and their pivotal role in a more sustainable world.

Even though the Special Issue is open to all contributions related to EV Charging, potential focus areas are summarized as the following:

  • Renewable Energy Integration
  • Fast Charging
  • Smart EV Charging
  • Wireless Charging EVs
  • Environmental Impact Assessment of EVs
  • Battery Management System

Dr. Zahra Hajabdollahi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • EV charging
  • environmental impact
  • energy efficiency
  • grid integration
  • charging infrastructure

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Published Papers (3 papers)

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Research

19 pages, 4115 KiB  
Article
Techno-Economic Design Analysis of Electric Vehicle Charging Stations Powered by Photovoltaic Technology on the Highways of Saudi Arabia
by Yassir Alhazmi
Energies 2025, 18(2), 315; https://doi.org/10.3390/en18020315 - 13 Jan 2025
Cited by 1 | Viewed by 1836
Abstract
The globalization of electric vehicle development and production is a significant goal. The availability of charging stations helps to encourage the global transition to electric vehicles, which may lead to a decrease in traditional fuel consumption. Nevertheless, the rise in the number of [...] Read more.
The globalization of electric vehicle development and production is a significant goal. The availability of charging stations helps to encourage the global transition to electric vehicles, which may lead to a decrease in traditional fuel consumption. Nevertheless, the rise in the number of electric vehicles is accompanied by sustainability issues, such as managing the grid’s electrical demand, building more charging stations, and providing electricity from renewable resources in an efficient and sustainable manner, especially in Saudi Arabia. This work focused on three challenges regarding the installation of fast charging stations (FCSs) for electric vehicles (EVs) on highways. The first challenge is choosing optimal locations on highways to address the range of anxiety of EV drivers. The second challenge is to fuel these FCSs using renewable resources, such as photovoltaic (PV) panels, to make FCSs sustainable. The last challenge is to design FCSs by considering both highway driving behavior and the available renewable energy resources in order to cover charging demand. All of these challenges should be considered while planning the EV charging infrastructure of Saudi highways from both technical and economic perspectives. Thus, using the HOMER® Grid software (version 1.10.1 June 2023), locations on Saudi Arabian highways were selected based on the renewable resources of several roads that support a large number of vehicles traveling on them. These roads were the Makkah to Riyadh, Makkah to Abha, Riyadh to Dammam, Riyadh to NEOM, and Jeddah to NEOM roads. Electric vehicle charging stations with a capacity of 200 kW, 300 kW, and 500 kW were designed on these roads based on their natural renewable resources, which is PV energy. These roads are the most important roads in the Kingdom and witness heavy traffic. An economic study of these stations was carried out in addition to considering their efficiency. This study revealed that the 500 kW station is ideal for charging electric vehicles, with an annual energy production of 3,212,000 kWh. The 300 kW station had better efficiency but higher capital expenses. The 200 kW station could charge 6100 vehicles annually. The three stations on the Makkah to Riyadh, Makkah to Abha, and Riyadh to Dammam roads can charge 65,758 vehicles annually. The total cost of the project was USD 2,786,621, with the 300 kW plant having the highest initial investment, which can be potentially justified due to its higher power output. This study provides a comprehensive overview of the project costs and the potential returns of using solar power plants for charging electric vehicles. Full article
(This article belongs to the Special Issue Advancements in Electric Vehicle (EV) Charging for a Sustainable Future)
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25 pages, 5341 KiB  
Article
Artificial Intelligence Optimization for User Prediction and Efficient Energy Distribution in Electric Vehicle Smart Charging Systems
by Siow Jat Shern, Md Tanjil Sarker, Mohammed Hussein Saleh Mohammed Haram, Gobbi Ramasamy, Siva Priya Thiagarajah and Fahmid Al Farid
Energies 2024, 17(22), 5772; https://doi.org/10.3390/en17225772 - 19 Nov 2024
Cited by 5 | Viewed by 2529
Abstract
This paper presents an advanced AI-based optimization framework for Electric Vehicle (EV) smart charging systems, focusing on efficient energy distribution to meet dynamic user demand. The study leverages machine learning models such as Random Forest, Support Vector Regression (SVR), Gradient Boosting Regressor, XGBoost, [...] Read more.
This paper presents an advanced AI-based optimization framework for Electric Vehicle (EV) smart charging systems, focusing on efficient energy distribution to meet dynamic user demand. The study leverages machine learning models such as Random Forest, Support Vector Regression (SVR), Gradient Boosting Regressor, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) to forecast user demand and optimize energy allocation. Among the models, XGBoost demonstrated superior predictive performance, achieving the lowest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), making it the most effective for real-time user demand prediction in smart charging scenarios. The framework introduces proportional and priority-based allocation strategies to distribute available energy effectively, with a focus on minimizing energy shortfalls and balancing supply with user demand. Results from the XGBoost model reduced prediction error by 15% compared to other models, significantly improving the station’s ability to meet user demand efficiently. The proposed AI framework enhances charging station operations, supports grid stability, and promotes sustainability in the context of increasing EV adoption. Full article
(This article belongs to the Special Issue Advancements in Electric Vehicle (EV) Charging for a Sustainable Future)
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17 pages, 42940 KiB  
Article
Enhancing Electric Vehicle Charger Performance with Synchronous Boost and Model Predictive Control for Vehicle-to-Grid Integration
by Youness Hakam, Ahmed Gaga, Mohamed Tabaa and Benachir El hadadi
Energies 2024, 17(7), 1787; https://doi.org/10.3390/en17071787 - 8 Apr 2024
Cited by 7 | Viewed by 1634
Abstract
This paper investigates optimizing the power exchange between electric vehicles (EVs) and the grid, with a specific focus on the DC-DC converters utilized in vehicle-to-grid (V2G) systems. It specifically explores using model predictive control (MPC) in synchronous boost converters to enhance efficiency and [...] Read more.
This paper investigates optimizing the power exchange between electric vehicles (EVs) and the grid, with a specific focus on the DC-DC converters utilized in vehicle-to-grid (V2G) systems. It specifically explores using model predictive control (MPC) in synchronous boost converters to enhance efficiency and performance. Through experiments and simulations, this paper shows that replacing diodes with SIC MOSFETs in boost converters significantly improves efficiency, particularly in synchronous mode, by minimizing the deadtime of SIC MOSFETs during switching. Additionally, this study evaluates MPC’s effectiveness in controlling boost converters, highlighting its advantages over traditional control methods. Real-world validations further validate the robustness and applicability of MPC in V2G systems. This study utilizes TMS320F28379D, one of Texas Instruments’ leading digital signal processors, enabling the implementation of MPC with a high PWM frequency of up to 200 MHz. This processor features dual 32-bit CPUs and a 16-bit ADC, allowing for high-resolution readings from sensors. Leveraging digital signal processing technologies and advanced electronic circuits, this study advances the development of high-performance boost converters, achieving power outputs of up to 48 watts and output voltages of 24 volts. Electronic circuits (PCB boards) have been devised, implemented, and evaluated to showcase their significance in advancing efficient V2G integration. Full article
(This article belongs to the Special Issue Advancements in Electric Vehicle (EV) Charging for a Sustainable Future)
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