Optimisations of draft gear designs for heavy haul trains

This thesis developed a parallel multiobjective optimisation methodology to enable fast optimisations of draft gear designs for heavy haul trains. Improvements were achieved in the development of deterministic white-box draft gear models to enable direct use of the results in product design. Draft gear model parameters such as spring stiffness, wedge angles, and preloads were used as optimisation variables. Two optimisation algorithms were used: Genetic Algorithm and Particle Swarm Optimisation. All draft gear designs in the optimisations were constrained by impact tests to ensure the optimised designs also comply with current draft gear acceptance standards. Draft gear performance was assessed using whole-trip Longitudinal Train Dynamics (LTD) simulations and coupler fatigue damage calculations. Each simulation covered about 640 km of track and had about 10 hours of operational time. Three optimisation objectives were considered: minimal fatigue damage for wagon connection systems of loaded trains, minimal in-train (coupler) forces for loaded trains, and minimal longitudinal wagon accelerations for empty trains.