Multi-parameter and Multi-objective Optimization of Mountain Rack Vehicle Suspension Based on Particle Swarm Optimization

doi:10.3901/JME.260126

Abstract

Abstract: The rack train is widely used in mountain rail transportation due to its strong climbing ability. The gear-rack meshing force is the main power source when the train runs on the ramp. Due to the installation error of the racks and the impact of the line, the gear-rack meshing force is becoming more intensified, which affects the wheel-rail force and aggravates the vibration of the car body. Therefore, the ride comfort and safety of the rack train running on the ramp are reduced. To optimize the ride comfort and safety of the rack train, firstly, based on the theory of vehicle-track coupled dynamics and gear transmission system dynamics, a rack vehicle-track coupling model considering the influence of wheel-rail contact and gear-rack meshing excitation is established, and the accuracy of the model is verified by the experimental validation. Secondly, the suspension parameter matrix is generated by the optimal Latin hypercube sampling and the sensitivity of suspension parameters is explored by the variance analysis. Finally, the Radial Basis Function Neural Network surrogate model and particle swarm optimization algorithm are used to optimize the suspension parameters of the rack train. The simulated results indicate that the interaction effects of the suspension parameters have a minimal sensitivity on the dynamics, making the optimization of dynamic indicators more direct and effective when adjusting individual parameters. Properly increasing the vertical primary damping of the rack vehicle and reducing the vertical primary stiffness can effectively improve the stability and safety of the vehicle. This optimization method effectively identifies the optimal configuration for the suspension system of the rack vehicle, significantly enhancing the safety and stability within a speed range of 10 to 35 km/h.

Key words: rack vehicle dynamic, suspension system, sensitivity analysis, surrogate model, multi-objective optimization

CLC Number:

U271

ZHANG Haitao, CHEN Zaigang, YANG Guojun, CHEN Zhihui, CHEN Xin, YANG Jizhong. Multi-parameter and Multi-objective Optimization of Mountain Rack Vehicle Suspension Based on Particle Swarm Optimization[J]. Journal of Mechanical Engineering, 2026, 62(4): 296-308.

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