Dynamic characteristics and sensitivity analysis of a nonlinear vehicle suspension system with stochastic uncertainties

The suspension system is an important part of a vehicle and directly affects the vehicle's comfort and stability during driving. There are various nonlinearities and uncertainties in the vehicle suspension system, and even small changes can have a significant impact on the suspension performance. This paper provides an in-depth study of quarter- and half-vehicle suspensions modeled with nonlinear springs and dampers, considering the stochastic uncertainty of various parameters. A mathematical model of a nonlinear vehicle suspension was developed to more accurately simulate the increased stiffness of suspension springs with travel and the energy consumption of dampers. The sparse grid-based polynomial chaos expansion is employed to construct the metamodels of the system response in both the frequency and time domains. This approach effectively captures the stochastic characteristics of the system response, reducing computational cost while improving accuracy. Based on polynomial metamodels, various performance indicators of the nonlinear suspension were analyzed, including statistical moments, probability distributions, and parameter sensitivities. The results are then compared and discussed, revealing that uncertainties in the nonlinear spring, sprung mass, and tire stiffness significantly impact the frequency response, time response, ride comfort, and safety. These findings contribute to a deeper understanding of the dynamic characteristics and behaviors of nonlinear vehicle suspensions under complex parameter uncertainties and provide a reference for enhancing suspension performance.