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Research on Intelligent Operation and Maintenance and Key Technology of New Energy Vehicles

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

Deadline for manuscript submissions: 18 February 2025 | Viewed by 602

Special Issue Editors


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Guest Editor
School of Mechanical Engineering, Guangxi University, Nanning, China
Interests: new energy vehicle; intelligent operation and maintenance; fault diagnosis

E-Mail Website
Guest Editor
School of Mechanical Engineering, Guangxi University, Nanning, China
Interests: new energy vehicle; intelligent operation and maintenance; fault diagnosis
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China
Interests: rotating machinery monitoring and diagnosis

Special Issue Information

Dear Colleagues

With increasing global attention being paid to environmental sustainability, the new energy vehicle industry plays a crucial role in solving the problems of traditional vehicle emissions and resource depletion. New energy vehicles use unconventional vehicle fuels as power sources, which mainly include hybrid vehicles, pure electric vehicles, fuel cell vehicles, and other new energy sources (such as supercapacitors, flywheels, and other efficient energy storage devices) vehicles. For new energy vehicles, research is of great significance to the national economy and people's travel safety. It is urgent to carry out intelligent operation and maintenance work and key technology research for new energy vehicles. The intelligent operation and maintenance of new energy vehicles aims to use data mining, machine learning, big data, and other methods to analyse and process vehicle real-time status data and vehicle record data so as to improve the operation efficiency, reliability, and environmental friendliness of new energy vehicles. This Special Issue aims to introduce and disseminate the latest research related to the intelligent operation and maintenance of new energy vehicles. The topics of interest include, but are not limited to:

  • Electric vehicles;
  • Low-carbon rail transit vehicles;
  • Electrical engineering;
  • Energy-saving optimization control;
  • Monitoring and control systems;
  • Batteries, fuel cells, reliability analysis;
  • Electrical engineering;
  • Diagnostics and prognostics of new energy vehicles;
  • Power electronics.

Dr. Zhenzhen Jin
Prof. Dr. Deqiang He
Prof. Dr. Dechen Yao
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

  • intelligent operation and maintenance
  • fault diagnosis
  • new energy vehicle
  • intelligent transportation system
  • prediction, detection, and optimization
  • emerging technologies
  • internet of vehicles
  • health status monitoring
  • intelligent perception

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Published Papers (1 paper)

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Research

22 pages, 8807 KiB  
Article
Performance and Efficiency Evaluation of a Secondary Loop Integrated Thermal Management System with a Multi-Port Valve for Electric Vehicles
by Jaehyun Bae, Jinwon Yun and Jaeyoung Han
Energies 2024, 17(22), 5729; https://doi.org/10.3390/en17225729 - 15 Nov 2024
Viewed by 391
Abstract
Recently, battery electric vehicles (BEVs) have faced various technical challenges, such as reduced driving range due to ambient temperature, slow charging speeds, fire risks, and environmental regulations. This numerical study proposes an integrated thermal management system (ITMS) utilizing R290 refrigerant and a 14-way [...] Read more.
Recently, battery electric vehicles (BEVs) have faced various technical challenges, such as reduced driving range due to ambient temperature, slow charging speeds, fire risks, and environmental regulations. This numerical study proposes an integrated thermal management system (ITMS) utilizing R290 refrigerant and a 14-way valve to address these issues, proactively meeting future environmental regulations, simplifying the system, and improving efficiency. The performance evaluation was conducted under high-load operating conditions, including driving and fast charging in various environmental conditions of 35 °C and −10 °C. As a result, the driving efficiency was 4.82 km/kWh in high-temperature conditions (35 °C) and 4.69 km/kWh in low-temperature conditions (−10 °C), which demonstrated higher efficiency than the Octovalve-ITMS applied to the Tesla Model Y. Furthermore, in fast charging tests, the high voltage battery was charged from a 10% to a 90% state of charge in 26 min at 35 °C and in 31 min at −10 °C, outperforming the Octovalve-ITMS-equipped Tesla Model Y’s fast charging time of 27 min under moderate ambient conditions. This result highlights the superior fast-charging performance of the 14-way valve-based ITMS, even under high cooling load conditions. Full article
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