Browse Publications Technical Papers 2010-36-0251
2010-10-06

Stochastic Simulation Method for CAE Vehicle Dynamics Evaluation and Design Robustness Analysis 2010-36-0251

This work presents a statistical approach for simulation based on Monte Carlo method. As an exercise of the method a CAE vehicle dynamics model was specifically created to evaluate the likelihood to meet a given target driving a maneuver for given inputs variations. In the exercise, three different inputs were chosen as stochastic inputs (also called noise factors) and all relevant information about their statistics has been raised, based in components information. The chosen inputs are: front/rear dampers curves, front/rear ride heights and tire surface temperature.
A brief description of the Monte Carlo technique is presented. The choice of this method is due to the reduced number of simulations required to have a given accuracy in comparison with other approaches, especially for multivariable system.
As output variable for the exercise, the tire patch height was chosen and the resulting probability density function of it is presented. Two different setups were tested in order to evaluate the robustness level of each. A third test was also done having as a parameter the height of the center of gravity of the vehicle.
The method has proven to be a powerful design tool. One verified advantage of the method is its outcome, not normally obtained from conventional deterministic CAE simulations: the likelihood of achieving a specific target and the design robustness to inputs variation.

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