Abstract
The elastic vibrations of the carbody tend to have influence on riding comfort in recent railway vehicles. For studying methods to reduce these vibrations, numerical analysis models are required. The authors proposed a simple analytical model that can express several three-dimensional elastic vibration modes of a carbody. Along with the modelling technique, determining the parameters used in the analysis models (called “model parameters” in this work) is also important. This study proposes a method to determine model parameters using particle swarm optimization (PSO), which is one of the optimization techniques, together with measured data. In this method, the frequency response functions (FRFs) at the several points on the vehicle were used to evaluate fitness between calculated and measured results, and the parameters that minimize the difference between them are decided. In order to verify the validity of the proposed method, excitation tests using Shinkansen type test vehicle were performed. As the results, good agreements between measured and calculated results were observed and the validity of the proposed method was confirmed.
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