Research and Application of Rail Vehicle Technology, 2nd Edition

Dear Colleagues,

Following the success of our previous Special Issue, titled ‘Research and Application of Rail Vehicle Technology’ (https://www.mdpi.com/journal/machines/special_issues/88G6161KYI), we are pleased to announce the next in the series, titled ‘Research and Application of Rail Vehicle Technology, 2nd Edition’.

With the acceleration of urbanization and the continuous growth of transportation demands, rail vehicle technology, as a crucial component of modern transportation, is facing unprecedented development opportunities. To further promote the research and application of rail vehicle technology, we are hosting the second edition of this Special Issue. It will present research findings and practical experiences from experts, scholars, and industry professionals both domestically and internationally to jointly explore the development trends and frontiers of rail vehicle technology.

This Special Issue seeks original research papers focusing on advances in rail vehicle technology. We welcome papers that offer new research directions and insights. We hope that this Special Issue will be useful and informative to both researchers and practitioners, and deliver promising new ideas and directions for future research.

Research topics that are of interest for this Special Issue include, but are not limited to, the following:

1. Rail vehicle technology: vehicle design, material application, dynamic performance, and operational safety.
2. Intelligent rail vehicle technology: research and application of intelligent rail vehicles such as autonomous driving, intelligent control, fault diagnosis and prediction, and information platforms.
3. Energy-saving and environmental protection technology for rail vehicles: research and application of green materials, energy-saving technologies, and emission control.
4. Rail vehicle systems and equipment: research and application of key components such as new braking systems, traction systems, communication systems, and safety systems.
5. Machine learning for railway vehicles: interpretable and robust machine learning for railway vehicles, encompassing system reliability analysis, diagnosis, prognosis, and health management.

Prof. Dr. Jingsong Zhou
Dr. Kai Zhou
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines 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 2400 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.