Prediction and Mitigation of Falling-Friction Wheel Squeal Noise Amplitude Under Combined Lateral and Longitudinal Creepage

• Continuous creep curve model under combined longitudinal and lateral creep. • Closed-form approximation of critical creep under combined creepage effects. • Analytical prediction of squeal amplitude under combined creepage. • Squeal amplitude decreases with increases in longitudinal creepage. • The analytical prediction is 12,000 times faster than the numerical model. Railway wheel squeal amplitude and sound pressure level under combined longitudinal and lateral creepage due to the falling friction mechanism were investigated in this study. An energy based closed-form solution for predicting wheel squeal amplitude was utilized using a modified heuristic creep curve, which was extended to include longitudinal creepage. The modified heuristic creep curve is simulated and validated using CONTACT software and experimental measurements. Analytical predictions and numerical models were verified and showed good agreement experimental results. For the reduced scale test rig at the University of Queensland, the results showed that an increase in longitudinal creepage would initially reduce squeal noise by 3 dB for longitudinal creepage lower than 0.005 and eliminate squeal when longitudinal creepage becomes higher than 0.005. An increase in longitudinal creepage causes the lower and upper bounds of angles of attack which causes squeal to converge, thereby reducing the range where squeal can occur. The model was further verified with field measurements of freight trains on an Australian main line with a curve radius of 300 m. Predicted trends of squeal sound pressure level were found to behave similarly with experimental results, increasing monotonically with an increase in the angle of attack and decreasing similarly with an increase in longitudinal creepage. Investigation of time-varying longitudinal creepage effects on squeal amplitude was carried out to investigate the feasibility of traction-based strategies and also confirmed the predicted effects. This insight may be used for squeal control through traction-based strategies. The proposed analytical method offers a computational speed-up of nearly 12,000 times compared to the numerical simulations.