You are currently viewing a new version of our website. To view the old version click .

Research and Application of Rail Vehicle Technology

This special issue belongs to the section “Vehicle Engineering“.

Special Issue Information

Dear Colleagues,

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 Special Issue entitled "Research and Application of Rail Vehicle Technology". This Special Issue 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. We also hope to deliver readers promising new ideas and directions for future research.

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

  1. Rail vehicle technology: including vehicle design, material application, dynamic performance and operational safety.
  2. Intelligent rail vehicle technology: including 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
Dr. Yuejian Chen
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-blind 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.

Keywords

  • rail vehicle technology
  • rail vehicle system dynamics
  • vehicle vibration and noise
  • fault diagnosis
  • new braking systems
  • traction systems
  • machine learning

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Published Papers

Get Alerted

Add your email address to receive forthcoming issues of this journal.

XFacebookLinkedIn
Machines - ISSN 2075-1702