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Special Issue "Application of Emerging Techniques for Electric Vehicles: The Drive towards Green Environment"

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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: 15 June 2023 | Viewed by 3810

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Special Issue Editors

Prof. Rajvikram Madurai Elavarasan

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Guest Editor

Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai 625015, Tamil Nadu, India
Interests: sustainable development goals; energy storage; thermal energy storage; demand-side management; techno-economic analysis of RE systems
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Eklas Hossain

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Guest Editor

Electrical and Computer Engineering, Boise State University, Boise, ID 83725, USA
Interests: energy systems; smart grids; machine learning; big data analytics; power electronics; advanced control system
Special Issues, Collections and Topics in MDPI journals

Dr. Kaliaperumal Rukmani Devabalaji

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Guest Editor

Department of Electrical Engineering, University of Cape Town, Cape Town 7700, South Africa
Interests: power system resilience; electric vehicles; virtual power plant; energy storage device

Special Issue Information

Dear Colleagues,

The air pollution and recent climate change are severe threats to our environment and society. The major causes of air pollution come from the transportation sector, and a clean and energy-efficient transportation and green environment must be developed to minimize air pollution. Emerging techniques such as artificial intelligence (AI), machine learning (ML), and deep learning (DL) can be implemented to achieve improvements in energy storage devices, which can help significantly toward reducing environmental issues. Research on safe and clean transportation is essential to improve the reliability of hybrid electric vehicles.

The objective of this Special Issue is to publish state-of-the-art research on current trends in the application of AI, ML, DL, and other optimization techniques to smart electric vehicles. We therefore invite papers on novel technical developments, reviews, case studies, and analytical as well as assessment papers from different disciplines, which can potentially contribute to the design of electric vehicles. This Special Issue will accept original research articles/reviews on novel and innovative approaches that address (but are not limited to) the following topics:

Energy infrastructure for electrical transportation, charging systems;
Power electronics for electric traction;
Energy management and control systems;
Charging infrastructure;
AI, ML, and DL for electric vehicles;
Optimization techniques for electric vehicles;
Next-generation energy storage technologies;
Hybrid electric vehicles;
Wireless technologies for charging stations;
Design of converters for electric vehicles.

Prof. Rajvikram Madurai Elavarasan
Prof. Dr. Eklas Hossain
Dr. Kaliaperumal Rukmani Devabalaji
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. Electronics 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 2000 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

Electric Vehicles
Artificial Intelligence
Energy storage Device
Power Electronics

Published Papers (2 papers)

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Research

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Open AccessArticle

Congestion-Aware Rideshare Dispatch for Shared Autonomous Electric Vehicle Fleets

Chenn-Jung Huang

Kai-Wen Hu

and

Cheng-Yang Hsieh

Electronics 2022, 11(16), 2591; https://doi.org/10.3390/electronics11162591 - 18 Aug 2022

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Abstract

The problem of traffic congestion caused by the fast-growing travel demands has been getting serious in urban areas. Meanwhile, the future of urban mobility has been foreseen as being electric, shared, and autonomous. Accordingly, the routing and charging strategies for fleets of shared autonomous electric vehicles (SAEVs) need to be carefully addressed to cope with the characteristics of the rideshare service operation of the SAEV fleets. In the literature, much work has been done to develop various traffic control strategies for alleviating the problem in urban traffic congestion. However, little research has proposed effective solutions that integrate the route of charging strategies for SAEV fleets with the urban traffic congestion problem. In this regard, this work presents an integrated framework that tackles the route and charging of SAEV fleets as well as the urban traffic congestion prevention issues. Notably, our contribution in this work not only proposes a joint solution for the problems of the urban traffic congestion control and rideshare dispatch of SAEV fleets, but also fills the gap of the routing and charging strategies for mixed privately owned EVs (PEV) and SAEV fleets in the literature. A general optimization framework is formulated, and effective heuristics are proposed to tackle the above-mentioned problems in this work. The feasibility and effectiveness of the proposed algorithms were evaluated through four different scenarios in the simulation. After applying the proposed algorithms, the traffic volumes of the oversaturated main arterial road were diverted to other less busy road sections, and the traveling times of EV passengers were decreased by 28% during peak periods. The simulation results reveal that the proposed algorithms not only provide a practical solution to prevent the problem in urban traffic congestion during rush hours, but also shorten the travel times of EV passengers effectively. Full article

(This article belongs to the Special Issue Application of Emerging Techniques for Electric Vehicles: The Drive towards Green Environment)

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Review

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Open AccessReview

Power Electronics Converter Technology Integrated Energy Storage Management in Electric Vehicles: Emerging Trends, Analytical Assessment and Future Research Opportunities

Molla Shahadat Hossain Lipu

Rajvikram Madurai Elavarasan

Abdullah Al Mamun

Muhammad Ammirrul A. M. Zainuri

and

Aini Hussain

Electronics 2022, 11(4), 562; https://doi.org/10.3390/electronics11040562 - 13 Feb 2022

Cited by 5 | Viewed by 2610

Abstract

Globally, the research on electric vehicles (EVs) has become increasingly popular due to their capacity to reduce carbon emissions and global warming impacts. The effectiveness of EVs depends on appropriate functionality and management of battery energy storage. Nevertheless, the battery energy storage in EVs provides an unregulated, unstable power supply and has significant voltage drops. To address these concerns, power electronics converter technology in EVs is necessary to achieve a stable and reliable power transmission. Although various EV converters provide significant contributions, they have limitations with regard to high components, high switching loss, high current stress, computational complexity, and slow dynamic response. Thus, this paper presents the emerging trends in analytical assessment of power electronics converter technology incorporated energy storage management in EVs. Hundreds (100) of the most significant and highly prominent articles on power converters for EVs are studied and investigated, employing the Scopus database under predetermined factors to explore the emerging trends. The results reveal that 57% of articles emphasize modeling, experimental work, and performance evaluation. In comparison, 13% of papers are based on problem formulation and simulation analysis, and 8% of articles are survey, case studies, and review-based. Besides, four countries, including China, India, the United States, and Canada, are dominant to publish the maximum articles, indicating 33, 17, 14, and 13, respectively. This review adopts the analytical assessment that outlines various power converters, energy storage, controller, optimization, energy efficiency, energy management, and energy transfer, emphasizing various schemes, key contributions, and research gaps. Besides, this paper discusses the drawbacks and issues of the various power converters and highlights future research opportunities to address the existing limitations. This analytical assessment could be useful to EV engineers and automobile companies towards the development of advanced energy storage management interfacing power electronics for sustainable EV applications. Full article

(This article belongs to the Special Issue Application of Emerging Techniques for Electric Vehicles: The Drive towards Green Environment)

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