Robust optimization design method for powertrain mounting systems based on six sigma quality control criteria

This paper presents a robust optimization design method based on Six Sigma quality control criteria to improve the design of a powertrain mounting system (PMS). The powertrain is modeled as a rigid body having six degrees of freedom (DOF) connected to a rigid base by four rubber mounts, and each mount is simplified as a three-dimensional spring-damper element in its local coordinate system (LCS). The calculation method based on energy decoupling is used to estimate the decoupling ratios of a PMS. The location and static stiffness of each mount and the orientations of the two anti-torsion mounts are selected as uncertain design variables, and the nominal values of these design variables are optimized to obtain a robust Six Sigma design for a PMS. The uncertain design variables are characterized by a perturbation or percent variation around their nominal values. The generalized reduced gradient (LSGRG2) optimization method is employed to solve the robust optimization problem, and a second-order Taylor series expansion is used to estimate the statistical properties of the performance constraints and objectives. The optimization results show that the robust design ensures good robustness or high reliability for the natural frequencies, decoupling ratios, and frequency separation constraints of a PMS.