Dynamic reliability evaluation of vehicle–track coupled systems considering the randomness of suspension and wheel–rail parameters

The ride quality and running safety of high-speed trains are directly influenced by uncertainties of some key parameters, such as the damping and stiffness coefficients of suspension systems, wheel–rail coefficient of friction and wheel–rail profiles. Dynamic reliability problems of vehicle–track coupled systems under the influence of the above random parameters are studied in this article. An efficient numerical method is presented by combining a prediction-based iterative solution technique with subset simulation method. The solution efficiency of deterministic responses is improved by means of efficient prediction of wheel–rail forces, and the number of deterministic solutions required is reduced by expressing a small failure probability as a product of large conditional probabilities. The accuracy and the efficiency of the present method are verified by comparing with the direct Monte Carlo simulation. The failure probability distribution curves of the lateral ride index on straight track and the derailment coefficient during curve negotiation are obtained and the reliability sensitivity analyses are also carried out. The main conclusions are given as follows: the reliability of the system is higher when the randomness of the parameters with greater sensitivity is not considered; the increase of the damping of anti-yaw damper or the wheel–rail coefficient of friction will improve the ride quality on straight track, but will lower the running safety when negotiating a curved track.