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Spectral Optimization of High-Speed Train Suspension Systems
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In this paper, an optimal suspension system for high-speed passenger trains is proposed based on a spectral analysis in frequency domain. In the optimization procedure, the ride quality and the fatigue life of the suspension system are simultaneously taken into consideration as objective functions. Spectral densities for the coil spring shear stress and the vertical acceleration are obtained using a spectral approach. A multi-variable optimization is carried out using genetic algorithms. Four design parameters including the damping properties of the secondary and primary suspension, and the wire diameter of their coil springs are obtained. A comprehensive parametric study is carried out on the effects of travelling speed, level of irregularity and eccentricity of the wagon body on the performance of the optimized system. The influences of any positive and negative deviations with respect to the optimal design parameters on the dynamic responses are also studied.
Keywords
Spectral density; Suspension system; High-speed train; Optimization; Genetic algorithm; Monte-Carlo simulation
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