Robust Optimal Design under Uncertainty for the Power-Plant Isolating System of the Truck

The power-plant of the truck is one of main vibration and noise sources which often result in drives' uncomfortable, steering wheel and rear view mirror vibration and so on, because the diesel engine of the higher vibration and noise operation is used. The rubber mounting system had been used to isolating the power-plant vibration in truck. But, the conventional design optimization may not always satisfy the designed targets duo to the significant uncertainties in the rubber mounting system. In the paper, the method of robust design methods is used to minimize the quality effect of uncertainties on the power-plant isolating system. The 6-DOF dynamical model of the power-plant isolating of the truck is established for calculating the performance and robustness. The objectives of the robust optimal design are to optimize the mean performances and minimize the variability of the vibration transmission from the power-plant to the frame, the spatial motion of the power-plant and uncouple of the model kinetic energy of the power-plant isolating system. The analysis techniques of the uncertainties and the worst-case estimating for the objective functions and constrains are discussed based on Monte-Carlo simulation method, the Taguchi approaches, interval algorithm and complex affine algorithm analysis for the power-plant isolating system. A preference aggregation method converts the multi-objective problem to a single objective problem, which is then solved using Genetic Algorithm. The robust optimal approach for the rubber mounting stiffness and location uncertainty of the power-plant isolating system for a truck is demonstrated. The results of the numerical simulations and the experiments in proving ground show a significant improvement in isolating performances and robustness for the power-plant isolating system compared with the reference vehicle.