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Advancements in New Energy Vehicle Technology

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

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 13216

Special Issue Editors


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Guest Editor
School of Engineering, University of Warwick, Coventry CV4 7AL, UK
Interests: electric vehicles; wind farms; microgrid
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Computer Science and Engineering, SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad 201204, Uttar Pradesh, India
Interests: VANET; energy; artificial intelligence

Special Issue Information

Dear Colleagues,

Rising concerns over global warming, the energy crisis, and environmental pollution have initiated the decarbonization movement. As per the International Energy Agency (IEA), the transportation sector is still responsible for 24% of direct CO2 emissions due to fossil fuel combustion. Given the urgent need for the transportation sector's decarbonization, the concept of electrification was initiated and led to the development of New Energy Vehicles (NEV). NEVs include plug-in electric vehicles eligible for public subsidies and include battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), and fuel cell electric vehicles (FCEV). Artificial Intelligence (AI) has become the tremendous technology that plays an important role in different fields of operations. Machine Learning (ML) and Deep Learning (DL) algorithms make predicting energy, transportation, and communication easier in environmental aspects. This Special Issue will focus on recent developments in the paradigm of NEV and AI techniques. Topics of interest for publication include, but are not limited to:

  • Design of NEVs;
  • Charging infrastructure for NEVs;
  • Global status of NEVs;
  • Policies to promote NEVs;
  • Control of NEVs;
  • Vehicle Grid Integration;
  • Application of artificial intelligence for NEVs;
  • Battery technology for NEVs;
  • Connected and autonomous NEVs;
  • Monitoring of NEVs;
  • NEVs as flexible resources;
  • Business models for NEVs;
  • AI in the realm of NEVs;
  • Advantages and techniques using machine learning and deep learning;
  • Intelligent energy vehicle systems;
  • Connected automated driving using energy vehicle technology;
  • Autonomous vehicles in VANET, Internet of Vehicles (IOV), Intelligent transportation systems (ITS) using energy vehicle technology.

Dr. Sanchari Deb
Prof. Dr. D.Ganesh Gopal
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. 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

  • NEVs
  • charging
  • vehicle grid integration
  • artificial intelligence
  • VANET
  • battery

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Published Papers (2 papers)

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Review

29 pages, 7015 KiB  
Review
A Review of Sensor Applications in Electric Vehicle Thermal Management Systems
by Anyu Cheng, Yi Xin, Hang Wu, Lixin Yang and Banghuai Deng
Energies 2023, 16(13), 5139; https://doi.org/10.3390/en16135139 - 3 Jul 2023
Cited by 3 | Viewed by 5357
Abstract
With the rapid development of the automotive industry, the application of sensors is of great importance in maintaining the reliability of electric vehicles and ensuring the safe operation of electric vehicles. Faced with the increasing data of thermal management system condition monitoring, sensor [...] Read more.
With the rapid development of the automotive industry, the application of sensors is of great importance in maintaining the reliability of electric vehicles and ensuring the safe operation of electric vehicles. Faced with the increasing data of thermal management system condition monitoring, sensor detection is widely used in the monitoring of electric vehicle thermal management system. In recent years, a large number of related studies and contributions to the literature have been published. Although a number of reviews have summarized this, these reviews lack an overview of the issues and methods raised in these studies. This paper reviews recent sensor applications for electric vehicle thermal management systems. Currently, battery internal sensors, battery external sensors and related multi-sensor fusion, traditional motor sensors, positionless motor sensors, and component-level sensors of air conditioning systems are the main application sensors in the field of thermal management systems. This article introduces the basic principles of each type of sensor, reviews the relevant applications of various thermal management modules, and summarizes the usage characteristics of each type of sensor. The main problems faced by the existing research on the application of thermal management system-based sensors, such as the detection accuracy of traditional sensors and the detection stability of advanced sensors, are summarized, and the solutions proposed by the existing research are also summarized. Finally, some future research directions, trends, and hotspots are outlined. It is hoped that this review can help readers to understand the problems and existing solutions for thermal-management-system-based sensor applications, and to conduct related research more effectively. Full article
(This article belongs to the Special Issue Advancements in New Energy Vehicle Technology)
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21 pages, 1514 KiB  
Review
Electric Vehicles Charging Infrastructure Demand and Deployment: Challenges and Solutions
by Praveen Prakash Singh, Fushuan Wen, Ivo Palu, Sulabh Sachan and Sanchari Deb
Energies 2023, 16(1), 7; https://doi.org/10.3390/en16010007 - 20 Dec 2022
Cited by 22 | Viewed by 6846
Abstract
Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum [...] Read more.
Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum among researchers all over the world. Different planning and scheduling models have been proposed in the literature. Each model is unique and has both advantages and disadvantages. Moreover, the performance of the models also varies and is location specific. A model suitable for a developing country may not be appropriate for a developed country and vice versa. This paper provides a classification and overview of charging station placement and charging activity scheduling as well as the global scenario of charging infrastructure planning. Further, this work provides the challenges and solutions to the EV charging infrastructure demand and deployment. The recommendations and future scope of EV charging infrastructure are also highlighted in this paper. Full article
(This article belongs to the Special Issue Advancements in New Energy Vehicle Technology)
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