Litcius/Paper detail

Dynamics and control simulation of railway virtual coupling

Qing Wu, Xiaohua Ge, Qing‐Long Han, Bo Wang, Honghua Wu, Colin Cole, Maksym Spiryagin

2022Vehicle System Dynamics40 citationsDOIOpen Access PDF

Abstract

This paper developed a parallel computing architecture for high-fidelity virtual coupling simulations. Multi-body train dynamics models considered various nonlinear components including wheel-rail contact, suspensions, and inter-vehicle connections. A virtual coupling controller was developed which can be implemented under various train-to-train communication topologies. The controller also allows existing trains to leave the platoon and new trains to merge into the platoon without re-designing the controller. The parallel computing architecture is also scalable and not limited by: the number of vehicles in each train; the number of trains in each train platoon and the topology of train-to-train communications. A case study by simulating a three-train (18 vehicles in total) platoon on a real-world track section was conducted. The results show that, by using 19 computer cores, parallel computing speed is nearly twice as fast as real-time. Parallel computing is about 17 times faster than serial computing. The results also show that the maximum spacing errors of the follower trains were about 0.22 m. Dynamics results such as wheel-rail contact forces, suspension forces, carbody vibrations and inter-vehicle forces were obtained; these results can be used to conduct system assessments in terms of passenger ride comfort, mechanical wear, etc.

Topics & Concepts

PlatoonTrainVehicle dynamicsGear trainEngineeringScalabilityVibrationController (irrigation)SimulationComputer scienceControl engineeringAutomotive engineeringControl (management)BiologyArtificial intelligenceAgronomyDatabaseQuantum mechanicsCartographySpiral bevel gearPhysicsGeographyRailway Engineering and DynamicsRailway Systems and Energy EfficiencyCivil and Geotechnical Engineering Research