Prediction and control of wheel squeal

Xiaogang Liu; Siqi Ye; Junbo Wu

doi:10.1117/12.2679748

16 June 2023 Prediction and control of wheel squeal

Xiaogang Liu, Siqi Ye, Junbo Wu

Proceedings Volume 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023); 127021M (2023) https://doi.org/10.1117/12.2679748
Event: International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 2023, Changsha, China

Abstract

When a vehicle is negotiating a curve of track, a kind of wheel squeal tends to be generated. In order to predict and mitigate wheel squeal, a model of wheel squeal based on modal coupling and negative damping theory is developed. The sensitivity of angle of attack, rolling velocity, negative slope coefficient and wheel damping is analysed based on this model, and the results correlate well with experimental measurements, indicating that this model is effective. Furthermore, these parameters of wheel-rail system are optimised based on this model using genetic algorithm. When these optimised parameters are applied, the result shows that the wheel vibration amplitude decreases evidently, and the sound pressure level is reduced by 16 dB, indicating that the optimisation using genetic algorithm based on this model is effective.

Citation Download Citation

Xiaogang Liu, Siqi Ye, and Junbo Wu "Prediction and control of wheel squeal", Proc. SPIE 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 127021M (16 June 2023); https://doi.org/10.1117/12.2679748

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