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

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 41481

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Special Issue Editors

Dr. Grzegorz Sierpiński

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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

Dr. Roberta Di Pace

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Guest Editor

Department of Civil Engineering, University of Salerno, via Giovanni Paolo II, 132, 84084 Fisciano (SA), Italy
Interests: cooperative intelligent transportation systems; traffic management and control; within-day traffic flow modelling; models and algorithms for travel demand assignment; smart/sustainable mobility; discrete choice models and alternative paradigms for travel behavior analysis and modelling; sharing mobility; transportation environmental impacts
Special Issues, Collections and Topics in MDPI journals

Dr. Angelo Coppola

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Guest Editor

Department of Civil, Architectural and Environmental Engineering, University of Naples “Federico II”, via Claudio 21, 80125 Naples, Italy
Interests: cooperative intelligent transportation systems; connected and automated vehicles; smart/sustainable mobility; electric vehicles; eco-driving control architectures; transportation environmental impacts

Special Issue Information

Dear Colleagues,

This Special Issue of WEVJ deals with problems faced with charging electric vehicles and the infrastructure for this purpose.

The development of electromobility is important, inter alia, due to the need to limit the negative impact of transport on the environment. This development depends on a number of factors, including the cost of electric vehicles, travel concerns regarding range, difficulties in planning a trip with charging en route, etc., with the increase in the number of electric vehicles on the roads being strongly dependent on the infrastructure in a given area, determining the possibility of making longer trips. The problem is very complex as it concerns both the location of the charging stations as well as the number of available plugs and charging power. Therefore, the aspects discussed here concern not only the needs of travelers and the determination of preferences in terms of travel frequency or their destinations, but also the possibilities resulting from the energy infrastructure. Multi-criteria analyses may also take into account the environmental aspect.

We invite scientists and engineers to submit articles related to the development and modeling problem of the electric car charging infrastructure.

Topics covered in the Special Issue include, but are not limited to, the following:

Charging station optimal sitting;
Environmental analysis related to charging processes;
Electromobility development;
Smart grid services;
Optimization of energy usage in transport networks;
Analysis of charging station accessibility.

Prof. Dr. Grzegorz Sierpiński
Prof. Dr. Roberta Di Pace
Dr. Angelo Coppola
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

charging station
electromobility
electric vehicles
transport infrastructure
smart grid
charging process

Published Papers (13 papers)

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Research

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13 pages, 5809 KiB

Open AccessArticle

Electric Vehicle Charging Data Analytics of Corporate Fleets

by Frederico Gonçalves, Liselene de Abreu Borges and Rodrigo Batista

World Electr. Veh. J. 2022, 13(12), 237; https://doi.org/10.3390/wevj13120237 - 7 Dec 2022

Cited by 1 | Viewed by 3511

Abstract

The advances in electric mobility, motivated by current sustainability issues, have led public and private organizations to invest in the electrification of their corporate fleets. To succeed in this transition, companies must mitigate the impacts of electrification on their fleet operation, in particular the ones on vehicle recharging. The increase in energy demand caused by electrification may require changes in the company electrical infrastructure, the installation of charging stations, and the proper planning of the recharging schedule, considering the particularities of each fleet and operation. In this context, data analytics is seen as an important tool to help companies to understand their charging fleet profile, supporting decision makers in making data-driven decisions regarding their charging infrastructure. This paper shows how data analytics could be applied to analyze the charging data of corporate electric fleets, adopting a business-oriented analysis method based on the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. The analyses were performed on data collected from three different companies, with each one of them operating fleets of vehicles of different categories, i.e., ultra-light, light, and heavy vehicles. The results illustrate how data analytics, based on interactive reports and dashboards, can shed light on business questions related to the operation of electric vehicle corporate fleets. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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13 pages, 3199 KiB

Open AccessArticle

A New Control Strategy for Energy Management of Bidirectional Chargers for Electric Vehicles to Minimize Peak Load in Low-Voltage Grids with PV Generation

by Parnian Fakhrooeian and Volker Pitz

World Electr. Veh. J. 2022, 13(11), 218; https://doi.org/10.3390/wevj13110218 - 19 Nov 2022

Cited by 3 | Viewed by 1529

Abstract

This paper introduces a new bidirectional vehicle-to-grid (V2G) control strategy for energy management of V2G charging points equipped with photovoltaic systems (PVs), considering the interaction between V2G chargers, electric vehicle (EV) owners, and the network operator. The proposed method aims to minimize peak load, grid infeed power, feeder loading, and transformer loading by scheduling EVs charging and discharging. The simulation experiments take into account three EV battery capacities as well as two levels of EV penetration. In order to validate the effectiveness of the proposed approach, five scenarios are studied in a single feeder of a low-voltage (LV) distribution network in DIgSILENT PowerFactory, which comprises a combination of residential and commercial loads as well as PV systems. Simulation results demonstrate that the proposed V2G strategy improves the paper’s objectives by providing ancillary services to the grid. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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16 pages, 3464 KiB

Open AccessArticle

Analysis of Charging Load Acceptance Capacity of Electric Vehicles in the Residential Distribution Network

by Yuan-Peng Hua, Shi-Qian Wang, Ding Han, Hong-Kun Bai, Yuan-Yuan Wang and Qiu-Yan Li

World Electr. Veh. J. 2022, 13(11), 214; https://doi.org/10.3390/wevj13110214 - 17 Nov 2022

Cited by 1 | Viewed by 1540

Abstract

After large-scale electric vehicles (EVs) are connected to the residential distribution network, community charging has become one of the main bottlenecks at present, especially in old residential areas. Therefore, the current residential distribution network’s ability to accept charging load and when and how the distribution network needs to be transformed have become meaningful research points. Based on the characteristics of the EVs’ charging load of residential areas on a typical day and the size of the target annual charging load, this paper analyzes the acceptance capacity of the charging load of the distribution network on typical weekdays and weekends. By taking the charging load characteristics, the charging time of EVs, the voltage of each node of the distribution network, the line capacity, the transformation capacity of the distribution station as constraints, and the maximum capacity of the residential distribution network to accept the charging load as the objective function, the charging load capacity of the residential distribution network is analyzed. The particle swarm optimization algorithm is employed to solve the optimized mathematical model. The simulation uses an actual residential distribution network as an analysis example, and the partition optimization results prove the correctness and feasibility of this proposed method. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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16 pages, 2233 KiB

Open AccessEditor’s ChoiceArticle

Regional Electric Vehicle Fast Charging Network Design Using Common Public Data

by Nathaniel S. Pearre, Lukas G. Swan, Erin Burbidge, Sarah Balloch, Logan Horrocks, Brendan Piper and Julia Anctil

World Electr. Veh. J. 2022, 13(11), 212; https://doi.org/10.3390/wevj13110212 - 10 Nov 2022

Cited by 3 | Viewed by 2456

Abstract

Electric vehicles rely on public fast charging when traveling outside a single charge range. Networks of fast charging hubs are a preferred solution, but should be deployed according to a design that avoids both redundant infrastructure representing overinvestment, and “charging deserts” which limit travel by EVs and thus inhibit EV adoption. We present a two-stage design strategy for a network of charging hubs relying on common public data including maps of roadways and electrical systems, and ubiquitous and readily accessible daily traffic volume data. First, the network design is based on the electrical distribution system, roadways, and a target inter-hub driving distance. Second, the number of fast chargers necessary at each hub to support expected vehicle kilometers is determined such that queuing to charge is infrequent. A case study to prepare Nova Scotia, Canada for the 2030 electric fleet of 15% of vehicles results in a network design with an average hub catchment area of 1230 km² and 354 electric vehicles per fast charger, and ensures that they are equitably distributed and can enable travel by EV throughout the jurisdiction. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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15 pages, 2582 KiB

Open AccessArticle

Observational Evaluation of the Maximum Practical Utilization of Electric Vehicle DCFC Infrastructure

by Nathaniel S. Pearre and Lukas G. Swan

World Electr. Veh. J. 2022, 13(10), 190; https://doi.org/10.3390/wevj13100190 - 16 Oct 2022

Cited by 1 | Viewed by 1984

Abstract

Central to the design of a direct current fast charging (DCFC) network is the question of how much energy a DCFC of a given power can supply to vehicles without users being forced to queue to charge. We define ‘utilization factor’ as the ratio of the energy delivered by a DCFC in a multi-day period to the maximum amount of energy it could deliver in period. Three and a half years of data from 12 DCFCs are examined, characterizing each charging event by both the utilization factor and the time lag since the termination of the previous charging event. Short lags between events are inferred to indicate queuing. To keep the fraction of would-be users who have to queue below 10%, the overall utilization of the DCFC must likewise be limited to 10% (or 7–17% in exceptionally heterogeneous or exceptionally homogeneous traffic patterns, respectively). E.g., a 100 kW DCFC should not be expected to deliver more than 240 kWh per day (100 kW × 24 h × 10%). Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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13 pages, 2439 KiB

Open AccessArticle

Method of Location and Capacity Determination of Intelligent Charging Pile Based on Recurrent Neural Network

by Shangbin Su

World Electr. Veh. J. 2022, 13(10), 186; https://doi.org/10.3390/wevj13100186 - 3 Oct 2022

Cited by 3 | Viewed by 1737

Abstract

With the popularity of new energy vehicles, a large number of cities began to focus on the installation of electric vehicle charging piles. However, the existing intelligent charging piles have faced problems such as short supply, unreasonable distribution areas, and insufficient power supply. In response to these problems, this research proposes a recurrent neural network algorithm with an integrated firefly algorithm. Based on these two algorithms, a charging pile location and capacity model was established, and users’ travel habits were analyzed according to the model. In the simulation experiment, the PR curve analysis of the algorithm was carried out first. The analysis results showed that the AP value of the recurrent neural network algorithm combined with the firefly algorithm was increased from 0.9324 to 0.9972. In addition, it had higher accuracy and stability than before, which also verified the feasibility of the algorithm. Finally, through the model, the user’s travel habits were analyzed in detail. From the perspective of total demand, the charging demand of commercial centers was the highest, with a peak of about 537 kw, followed by 501 kw in office areas and then about 379 kw in parks. The kw charging demand in other areas was below 200 kw. The above results show that the recursive neural network can effectively determine the location and capacity of the charging pile, which is of great value to the development of transportation and new energy. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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27 pages, 14285 KiB

Open AccessArticle

Simulation-Based Evaluation of Charging Infrastructure Concepts: The Park and Ride Case

by Markus Fischer, Cornelius Hardt, Jörg Elias and Klaus Bogenberger

World Electr. Veh. J. 2022, 13(8), 151; https://doi.org/10.3390/wevj13080151 - 10 Aug 2022

Cited by 3 | Viewed by 2298

Abstract

In this study, a framework regarding park and ride facilities is presented and demonstrated to evaluate different approaches of charging concepts. The innovation in this study is that the framework can be used to evaluate arbitrary conductive charging concepts on a detailed level and on the basis of real usage data. Thus, the results can be broken down to the level of individual charging events and charging points. Among other factors, the study considers the expected growth in electric vehicles, the construction and operating costs for the investigated charging infrastructure, and the impact of heterogeneous electric vehicle fleets with different vehicle-specific charging powers. Since both technological and economic perspectives are considered in the framework, the study is relevant for all decision makers involved in the development and operation of charging infrastructure. The results in the investigated case of park and ride facilities show a high potential for cost-efficient low-power charging concepts. Thus, significantly higher energy volumes could be transmitted and better economic results could be achieved by the investigated low-power approaches. Especially for heterogeneous electric vehicle fleets, the number of available charging points appears to be more important than the charging power of the individual charging points in this case. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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20 pages, 4672 KiB

Open AccessEditor’s ChoiceArticle

Smart Tool Development for Customized Charging Services to EV Users

by Alberto Zambrano Galbis, Moisés Antón García, Ana Isabel Martínez García, Stylianos Karatzas, Athanasios Chassiakos, Vasiliki Lazari and Olympia Ageli

World Electr. Veh. J. 2022, 13(8), 145; https://doi.org/10.3390/wevj13080145 - 3 Aug 2022

Cited by 3 | Viewed by 2131

Abstract

E-mobility is a key element in the future energy systems. The capabilities of EVs are many and vary since they can provide valuable system flexibility services, including management of congestion in transmission grids. According to the literature, leaving the charging process uncontrolled could hinder some of the present challenges in the power system. The development of a suitable charging management system is required to address different stakeholders’ needs in the electro-mobility value chain. This paper focuses on the design of such a system, the TwinEV module, that offers high-value services to electric vehicles (EV) users. This module is based on a Smart Charging Tool (SCT), aiming to deliver a more user-central and cooperative approach to the EV charging processes. The methodology of the SCT tool, as well as the supportive optimization algorithm, are explained thoroughly. The architecture and the web applications of TwinEV module are analyzed. Finally, the deployment and testing results are presented. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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33 pages, 7999 KiB

Open AccessArticle

Electric Vehicle Simulations Based on Kansas-Centric Conditions

by Tyler Simpson, George Bousfield, Austin Wohleb and Christopher Depcik

World Electr. Veh. J. 2022, 13(8), 132; https://doi.org/10.3390/wevj13080132 - 26 Jul 2022

Viewed by 2622

Abstract

Range anxiety is a significant contributor to consumer reticence when purchasing electric vehicles (EVs). To alleviate this concern, new commercial EVs readily achieve over 200 miles of range, as found by the United States Environmental Protection Agency (EPA). However, this range, measured under idealized conditions, is often not encountered in real-world conditions. As a result, this effort describes the simplest model that incorporates all key factors that affect the range of an EV. Calibration of the model to EPA tests found an average deviation of 0.45 and 0.57 miles for highway and city ranges, respectively, among seven commercial EVs. Subsequent predictions found significant losses based on the impact of road grade, wind, and vehicle speed over a Kansas interstate highway. For cabin conditioning, up to 57.8% and 37.5% losses in range were found when simulating vehicles at 20 °F and 95 °F, respectively. Simulated aging of the vehicle battery pack showed range losses up to 53.1% at 100,000 miles. Model extensions to rain and snow illustrated corresponding losses based on the level of precipitation on the road. All model outcomes were translated into an Excel spreadsheet that can be used to predict the range of a generic EV over Kansas-centric roads. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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27 pages, 6115 KiB

Open AccessEditor’s ChoiceArticle

Optimizing Public Charging: An Integrated Approach Based on GIS and Multi-Criteria Decision Analysis

by Ali Khalife, Tu-Anh Fay and Dietmar Göhlich

World Electr. Veh. J. 2022, 13(8), 131; https://doi.org/10.3390/wevj13080131 - 25 Jul 2022

Cited by 5 | Viewed by 3352

Abstract

The rise in electric vehicle uptake has reshaped the German mobility landscape at unprecedented speed and scale. While public charging is pivotal to growing the electric vehicle market, municipalities can play a crucial role in accelerating the energy transition in transport. This research aims to assist municipalities in planning their strategic rollouts of public charging infrastructure in size and location. In the first step, charging demand is estimated based on four development scenarios in 2030 of EV adoption and public charging. In a second step, a geospatial analysis was performed on the study area. Supply and demand criteria were considered to reflect the attractiveness of each location on a grid map. While the supply criteria represent constraints related to infrastructure availability, the demand criteria are categorized into three dimensions: residential, commercial, and leisure. The prioritization of demand criteria was derived from the municipality’s input using the analytical hierarchy process method to reflect its strategy. After obtaining the suitability index map, a cluster analysis was performed using a k-means clustering algorithm to ensure adequate geographical coverage of the charging network. Finally, the proposed charging stations in each scenario were allocated to the top-scoring locations, establishing a municipal public charging network. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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14 pages, 955 KiB

Open AccessArticle

Layout Evaluation of New Energy Vehicle Charging Stations: A Perspective Using the Complex Network Robustness Theory

by Peipei Zhang, Juan Chen, Lilan Tu and Longteng Yin

World Electr. Veh. J. 2022, 13(7), 127; https://doi.org/10.3390/wevj13070127 - 12 Jul 2022

Cited by 4 | Viewed by 2070

Abstract

At present, the new energy vehicle industry is developing rapidly, but the relative lag in the development of its supporting infrastructure, especially charging stations, has become a bottleneck that restricts the development of the electric vehicle industry. In this paper, we propose a model for constructing a network of new energy vehicle charging facilities based on complex network theory and analyze the operation and the rationality of the layout of the new energy vehicle (NEV) charging stations in Wuhan and Hangzhou, respectively. The results show that the current layout of new energy vehicle charging stations in the city is relatively reasonable, but the allocation of charging pile resources is unreasonable. Our results of the virtual charging station network constructed by adding new charging station nodes show that the change in network structure helps to enhance the performance of the charging station system. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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18 pages, 20513 KiB

Open AccessEditor’s ChoiceArticle

Electric Vehicle Public Charging Infrastructure Planning Using Real-World Charging Data

by Benedict J. Mortimer, Christopher Hecht, Rafael Goldbeck, Dirk Uwe Sauer and Rik W. De Doncker

World Electr. Veh. J. 2022, 13(6), 94; https://doi.org/10.3390/wevj13060094 - 24 May 2022

Cited by 16 | Viewed by 5908

Abstract

The current increase of electric vehicles in Germany requires an adequately developed charging infrastructure. Large numbers of public and semi-public charging stations are necessary to ensure sufficient coverage. To make the installation worthwhile for the mostly private operators as well as public ones, a sufficient utilization is decisive. An essential factor for the degree of utilization is the placement of a charging station. Therefore, the initial site selection plays a critical role in the planning process. This paper proposes a charging station placement procedure based on real-world data on charging station utilization and places of common interest. In the first step, we correlate utilization rates of existing charging infrastructure with places of common interest such as restaurants, shops, bars and sports facilities. This allows us to estimate the untapped potential of unexploited areas across Germany in a second step. In the last step, we employ the resulting geographical extrapolation to derive two optimized expansion strategies based on the attractiveness of locations for electric vehicle charging. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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Review

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15 pages, 1197 KiB

Open AccessEditor’s ChoiceReview

Charging Electric Vehicles Today and in the Future

by Jennifer Leijon and Cecilia Boström

World Electr. Veh. J. 2022, 13(8), 139; https://doi.org/10.3390/wevj13080139 - 29 Jul 2022

Cited by 27 | Viewed by 8211

Abstract

It is expected that more vehicles will be electrified in the coming years. This will require reliable access to charging infrastructure in society, and the charging will include data exchange between different actors. The aim of this review article is to provide an overview of recent scientific literature on different charging strategies, including for example battery swapping, conductive- and inductive charging, and what data that may be needed for charging of different types of electric vehicles. The methodology of the paper includes investigating recent scientific literature and reports in the field, with articles from 2019 to 2022. The contribution of this paper is to provide a broad overview of different charging strategies for different types of electric vehicles, that could be useful today or in the coming years. The literature review shows that data utilized for charging or discharging includes for example information on the battery, temperature, electricity cost, and location. It is concluded that the preferred charging strategy for an electric vehicle may depend on the type of electric vehicle and when, where, and how the vehicle is used. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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