Uncertainty Analysis Of Vehicle Suspension Systems Based On Polynomial Chaos Methods

Suspension is an important part of the modern automotive, and it has a great impact for ride comfort, handling and stability, passing ability, the life of the car and so on.Now the vast majority of cars still used the traditional passive suspension system because of the cost control. The resilient element (rigidity value) and damping element (damping value) of the passive suspension are usually fixed to the road conditions and driving conditions, and it’s determined. But, actually, the uncertainty factor is an objective existence in the suspension system. If there are too many uncertainties influencing factors, significant errors of the results of the preliminary design must be caused, and the results of that are loss of time and cost. So, this paper studies the problem of uncertainty exists in the of automotive suspension system.But, the difference is that in this paper the problem of the uncertainty of the vehicle suspension system is solved by Generalized Polynomial Chaos methods instead of Monte Carlo method. In order to demonstrate the polynomial chaos methods can be used in the field of vehicle dynamics, based on an A-class car as the prototype, the author established the vehicle model and uncertainty of the model has been studied using polynomial chaos methods during the simulation by using the multi-body dynamic analysis software ADAMS.By comparing with Monte Carlo simulation method using MATLAB, the results show that polynomial chaos methods are more efficient than Monte Carlo method and are a relatively powerful approach for the simulation of multi-body dynamic system with uncertainties.