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WEVJ
Special Issues
Sustainable EV Rapid Charging, Challenges, and Development
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Sustainable EV Rapid Charging, Challenges, and Development

A special issue of World Electric Vehicle Journal (ISSN 2032-6653).

Deadline for manuscript submissions: 28 February 2025 | Viewed by 7225

Special Issue Editors

Prof. Dr. Salah Al-Majeed

E-Mail Website
Guest Editor
School of Science and Engineering, Al Akhawayn University in Ifrane, Ifrane, Morocco
Interests: systems engineering; EV connectivity; smart systems; industrial Internet of Things (IIoT)
Prof. Dr. Grzegorz Sierpiński

E-Mail Website
Guest Editor
Department Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Krasińskiego Str. 8, 40-019 Katowice, Poland
Interests: sustainable transport; electromobility; travel behavior; environmentally friendly transport solutions; traffic engineering; traffic flow measurement; analysis and prognosis; transport systems modeling; optimization of transport networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electric vehicles (EVs) offer substantially reduced greenhouse gas emissions over traditional vehicles that reduce air pollution, combat climate change, and provide health benefits to the general population. Despite these benefits, EV growth has remained slow within the global market. This is partially attributable to a range of challenges for prospective stakeholders, such as whether EV Rapid Charging Points can store adequate energy levels or longer commutes caused by end-to-end charging systems.

The challenges in developing sustainable solutions have increased dramatically because of Net-Zero and clean energy fast-approaching targets, as well as the political situation. On the other hand, technology, standardisation, manufacturers, and consumers have moved to a higher level, in which there is an urgent need for relatively sustainable end-to-end system approaches.

This Special Issue, therefore, invites all original and reviewed articles covering the challenging aspects of the development of EV charging systems, including but not limited to sustainable EV rapid charging (points, network, and distributions) and sustainable EV rapid storage systems.

Prof. Dr. Salah Al-Majeed
Prof. Dr. Grzegorz Sierpiński
Guest Editors

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. World Electric Vehicle Journal is an international peer-reviewed open access monthly 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 1400 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

  • electromobility
  • charging stations
  • electric vehicles
  • power grid

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Published Papers (5 papers)

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Research

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21 pages, 6730 KiB  
Article
Are Greek Drivers Willing to Embrace V2G Technology? A Survey Research
by Emmanouil Kostopoulos, Dimitrios Krikis and Georgios Spyropoulos
World Electr. Veh. J. 2024, 15(10), 434; https://doi.org/10.3390/wevj15100434 - 26 Sep 2024
Viewed by 582
Abstract
According to the European Commission, electric vehicles (EVs) remain parked for 95% of their life, which makes them inefficient. In addition, EV sales are forecasted to rise over the following years, which will create additional electricity demand, especially during peak hours. This challenge [...] Read more.
According to the European Commission, electric vehicles (EVs) remain parked for 95% of their life, which makes them inefficient. In addition, EV sales are forecasted to rise over the following years, which will create additional electricity demand, especially during peak hours. This challenge coincides with the growing trend of homeowners installing renewable energy sources (RES) in their homes. Therefore, a potential solution to managing the increase in electricity costs and peak demand is the use of EVs as a flexible storage system by utilizing vehicle-to-grid (V2G) technology. The successful market penetration of V2G technology hinges significantly on the willingness of current and future EV drivers to participate. Hence, in the broader context of the promotion and transition to electromobility and related technologies (V2G), the main purpose of this paper was to shed light on the hitherto unknown attitudes of Greek drivers towards V2G technology. The adopted methodology involved a survey questionnaire with statements serving as indicators on a 5-point Likert scale. The results show that Greek drivers highly appreciate the positive environmental impact of EVs but are primarily driven by the potential economic incentives they might receive from engaging with V2G technology. In addition, they appear to be skeptical about both V2G technology and electromobility, mainly due to the increased upfront cost of EVs but also due to the immature V2G market. Full article
(This article belongs to the Special Issue Sustainable EV Rapid Charging, Challenges, and Development)
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23 pages, 3425 KiB  
Article
Depot Charging Schedule Optimization for Medium- and Heavy-Duty Battery-Electric Trucks
by Shuhan Song, Yin Qiu, Robyn Leigh Coates, Cristina Maria Dobbelaere and Paige Seles
World Electr. Veh. J. 2024, 15(8), 379; https://doi.org/10.3390/wevj15080379 - 21 Aug 2024
Viewed by 1246
Abstract
Charge management, which lowers charging costs for fleets and prevents straining the electrical grid, is critical to the successful deployment of medium- and heavy-duty battery-electric trucks (MHD BETs). This study introduces an energy demand and cost management framework that optimizes depot charging for [...] Read more.
Charge management, which lowers charging costs for fleets and prevents straining the electrical grid, is critical to the successful deployment of medium- and heavy-duty battery-electric trucks (MHD BETs). This study introduces an energy demand and cost management framework that optimizes depot charging for MHD BETs by combining an energy consumption machine learning model and a linear program optimization model. The framework considers key factors impacting real-world MHD BET operations, including vehicle and charger configurations, duty cycles, use cases, geographic and climate conditions, operation schedules, and utilities’ time-of-use (TOU) rates and demand charges. The framework was applied to a hypothetical fleet of 100 MHD BETs in California under three different utilities for 365 days, with results compared to unmanaged charging. The optimized charging solution avoided more than 90% of on-peak charging, reduced fleet charging peak load by 64–75%, and lowered fleet energy variable costs by 54–64%. This study concluded that the proposed charge management framework significantly reduces energy costs and peak loads for MHD BET fleets while making recommendations for fleet electrification infrastructure planning and the design of utility TOU rates and demand charges. Full article
(This article belongs to the Special Issue Sustainable EV Rapid Charging, Challenges, and Development)
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21 pages, 4916 KiB  
Article
Optimal Allocation of Fast Charging Stations on Real Power Transmission Network with Penetration of Renewable Energy Plant
by Sami M. Alshareef and Ahmed Fathy
World Electr. Veh. J. 2024, 15(4), 172; https://doi.org/10.3390/wevj15040172 - 20 Apr 2024
Cited by 2 | Viewed by 1792
Abstract
Because of their stochastic nature, the high penetration of electric vehicles (EVs) places demands on the power system that may strain network reliability. Along with increasing network voltage deviations, this can also lower the quality of the power provided. By placing EV fast [...] Read more.
Because of their stochastic nature, the high penetration of electric vehicles (EVs) places demands on the power system that may strain network reliability. Along with increasing network voltage deviations, this can also lower the quality of the power provided. By placing EV fast charging stations (FCSs) in strategic grid locations, this issue can be resolved. Thus, this work suggests a new methodology incorporating an effective and straightforward Red-Tailed Hawk Algorithm (RTH) to identify the optimal locations and capacities for FCSs in a real Aljouf Transmission Network located in northern Saudi Arabia. Using a fitness function, this work’s objective is to minimize voltage violations over a 24 h period. The merits of the suggested RTH are its high convergence rate and ability to eschew local solutions. The results obtained via the suggested RTH are contrasted with those of other approaches such as the use of a Kepler optimization algorithm (KOA), gold rush optimizer (GRO), grey wolf optimizer (GWO), and spider wasp optimizer (SWO). Annual substation demand, solar irradiance, and photovoltaic (PV) temperature datasets are utilized in this study to describe the demand as well as the generation profiles in the proposed real network. A principal component analysis (PCA) is employed to reduce the complexity of each dataset and to prepare them for the k-means algorithm. Then, k-means clustering is used to partition each dataset into k distinct clusters evaluated using internal and external validity indices. The values of these indices are weighted to select the best number of clusters. Moreover, a Monte Carlo simulation (MCS) is applied to probabilistically determine the daily profile of each data set. According to the obtained results, the proposed RTH outperformed the others, achieving the lowest fitness value of 0.134346 pu, while the GRO came in second place with a voltage deviation of 0.135646 pu. Conversely, the KOA was the worst method, achieving a fitness value of 0.148358 pu. The outcomes attained validate the suggested approach’s competency in integrating FCSs into a real transmission grid by selecting their best locations and sizes. Full article
(This article belongs to the Special Issue Sustainable EV Rapid Charging, Challenges, and Development)
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16 pages, 4434 KiB  
Article
Dynamic Programming of Electric Vehicle Reservation Charging and Battery Preheating Strategies Considering Time-of-Use Electricity Price
by Bo Zhu, Chengwu Bao, Mingyao Yao and Zhengchun Qi
World Electr. Veh. J. 2024, 15(3), 90; https://doi.org/10.3390/wevj15030090 - 1 Mar 2024
Cited by 1 | Viewed by 1588
Abstract
Electric vehicles can effectively make use of the time-of-use electricity price to reduce the charging cost. Additionally, using grid power to preheat the battery before departure is particularly important for improving the vehicle mileage and reducing the use cost. In this paper, a [...] Read more.
Electric vehicles can effectively make use of the time-of-use electricity price to reduce the charging cost. Additionally, using grid power to preheat the battery before departure is particularly important for improving the vehicle mileage and reducing the use cost. In this paper, a dynamic programming algorithm is used to optimize the battery AC (Alternating Current) charging–preheating strategy to minimize the total cost of battery charging and preheating, with the charging current and battery preheating power consumption as the control variables. The cost difference between the optimized control strategy and the conventional preheating strategy was analyzed under different ambient temperatures (−20~0 °C) and different target travel times (7:00~12:00). The simulation results show that the optimized control strategy makes the state of charge (SOC) and temperature of the battery reach the set value at the user’s target departure time, and the total cost of the grid is the lowest. Compared with the conventional preheating strategy, the optimized control strategy can utilize the power grid energy in the valley price area and reduce the opening time of the positive temperature coefficient (PTC) heater in the flat and the peak price zones. Furthermore, the cost utilization rate can reach 18.41~73.96%, and the cost-saving effect is significant. Full article
(This article belongs to the Special Issue Sustainable EV Rapid Charging, Challenges, and Development)
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Review

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44 pages, 973 KiB  
Review
A Review on State-of-Charge Estimation Methods, Energy Storage Technologies and State-of-the-Art Simulators: Recent Developments and Challenges
by Tawanda Kunatsa, Herman C. Myburgh and Allan De Freitas
World Electr. Veh. J. 2024, 15(9), 381; https://doi.org/10.3390/wevj15090381 - 23 Aug 2024
Viewed by 930
Abstract
Exact state-of-charge estimation is necessary for every application related to energy storage systems to protect the battery from deep discharging and overcharging. This leads to an improvement in discharge efficiency and extends the battery lifecycle. Batteries are a main source of energy and [...] Read more.
Exact state-of-charge estimation is necessary for every application related to energy storage systems to protect the battery from deep discharging and overcharging. This leads to an improvement in discharge efficiency and extends the battery lifecycle. Batteries are a main source of energy and are usually monitored by management systems to achieve optimal use and protection. Coming up with effective methods for battery management systems that can adequately estimate the state-of-charge of batteries has become a great challenge that has been studied in the literature for some time. Hence, this paper analyses the different energy storage technologies, highlighting their merits and demerits. The various estimation methods for state-of-charge are discussed, and their merits and demerits are compared, while possible applications are pointed out. Furthermore, factors affecting the battery state-of-charge and approaches to managing the same are discussed and analysed. The different modelling tools used to carry out simulations for energy storage experiments are analysed and discussed. Additionally, a quantitative comparison of different technical and economic modelling simulators for energy storage applications is presented. Previous research works have been found to lack accuracy under varying conditions and ageing effects; as such, integrating hybrid approaches for enhanced accuracy in state-of-charge estimations is advised. With regards to energy storage technologies, exploring alternative materials for improved energy density, safety and sustainability exists as a huge research gap. The development of effective battery management systems for optimisation and control is yet to be fully exploited. When it comes to state-of-the-art simulators, integrating multiscale models for comprehensive understanding is of utmost importance. Enhancing adaptability across diverse battery chemistries and rigorous validation with real-world data is essential. To sum up the paper, future research directions and a conclusion are given. Full article
(This article belongs to the Special Issue Sustainable EV Rapid Charging, Challenges, and Development)
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