Riding Comfort Analysis for Coupled Vehicle-track Systems With Uncertain Parameters

Riding comfort is an important index of the vehicle dynamic performance, of which the accurate and efficient prediction is of great importance for improving the vehicle design and reducing the costs. In this paper, the dynamic analysis with uncertain factors was studied. The uncertain parameters were described by random variables and the random excitations were described by random processes, respectively. Based on the pseudo-excitation method combined with the improved perturbation method, a deterministic approach was established for the analysis of double random vibration problems. In the numerical example, nine random variable parameters were considered and the riding comfort indexes at different positions under track irregularities were investigated. Results show that this method agrees well with those by using Monte Carlo method, and ignoring parameter uncertainty will lead to higher comfort evaluation.