JOURNAL ARTICLE

Braking in Railway Vehicles: A Review.

  • Published In: International Journal of Vehicle Structures & Systems (IJVSS), 2025, v. 17, n. 2. P. 273 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Bhardawaj, Sono; Sharma, Rakesh Chandmal; Raturi, Anuj; Satyanarayana, V. S. V.; Pavankumar, R.; Bahl, Shashi 3 of 3

Abstract

The safe and efficient operation of rail vehicles is completely dependent on the braking systems. This review paper provides a comprehensive overview of the various braking systems utilized in railway vehicles, encompassing both traditional and modern technologies. Beginning with an examination of the fundamental principles underlying braking systems, the paper explores the evolution of braking systems from manual to pneumatic, hydraulic, electro-pneumatic and electro-dynamic systems. Each braking system's design, operation, advantages and limitations are discussed in detail, along with their applications in different types of railway vehicles such as freight wagons, passenger trains and locomotives. Special emphasis is placed on recent advancements in braking technology, including regenerative braking, disc brakes, vacuum brakes and electronic control systems. Furthermore, the paper addresses challenges and future directions in railway braking system development, focusing on enhancing safety, reliability and energy efficiency. Overall, this review offers valuable insights for researchers, engineers and practitioners in the field of railway transportation. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Vehicle Structures & Systems (IJVSS). 2025/03, Vol. 17, Issue 2, p273
  • Document Type:Literature Review
  • Subject Area:History
  • Publication Date:2025
  • ISSN:0975-3060
  • DOI:10.4273/ijvss.17.2.15
  • Accession Number:187398079
  • Copyright Statement:Copyright of International Journal of Vehicle Structures & Systems (IJVSS) is the property of Carbon Magics Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.