Chen, Changji (Beijing Jiaotong University), Wang, Hongwei (Beijing Jiaotong University), Wang, Xi (School of Automation and Intelligence, Beijing Jiaotong Universi), Yuan, Lei (Beijing Jiaotong University)

Sliding Mode Control for Departure-Optimized Virtual Coupling of Heavy Haul Trains

Scheduled for presentation during the Regular Session "S33a-Intelligent Control for Next-Generation Railway Systems" (FR-LM-T33), Friday, November 21, 2025, 10:30−10:50, Southport 3

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

Heavy haul transportation leverages long trains for cost efficiency but faces challenges due to high combination costs and reduced efficiency in bottleneck areas. To improve the efficiency of existing heavy haul railway operations and enhance marshalling station departure performance, this study introduces a novel virtual coupling approach. A multi-particle heavy haul trains (HHTs) model is developed to capture unknown parameters and external disturbances, and it is integrated with a safety tracking model and an efficient departure process for trains operating on multiple arrival-departure tracks. To address the stability of the virtual coupling HHTs formation under complex dynamical models, a nonsingular terminal sliding mode controller is designed to achieve finite-time convergence. Simulation results from a six-train formation scenario demonstrate that the proposed strategy achieves precise speed tracking and maintains tight spacing error control, while the maximum coupler forces remain below the safety threshold, thereby confirming both the efficacy and safety of the virtual coupling formation.