A methodology for design optimization of powertrain mounting systems involving hybrid interval-random uncertainties.

Automotive powertrain mounting systems (PMSs) may exhibit hybrid interval-random (HIR) uncertainties in engineering practice. In HIR case, the uncertain parameters of PMSs are characterized as the random variables with interval distributions. A comprehensive methodology is proposed for the design optimization of the PMSs involving HIR uncertainties in this study. The hybrid interval-random perturbation central difference method (HIRP-CDM) is firstly derived to calculate the uncertain responses of PMSs, in which HIR uncertainties are addressed by twice perturbation analyses and twice central difference analyses. Meanwhile, the hybrid interval-random Monte Carlo method is presented as a reference method. Then, reliability assessment models are constructed to evaluate the probability intervals of system inherent characteristics satisfying design requirements. Next, a design optimization model is formulated to explore the optimal design of PMSs. The expectation intervals and variance intervals of system inherent characteristics are taken to create optimization objective, and the minimal probabilities of system inherent characteristics meeting requirements are utilized to establish reliability constraints. Both robustness and reliability are considered in the optimization, and the optimization can be simplified with the aid of HIRP-CDM. The effectiveness of the proposed methodology is finally demonstrated by the numerical example. [ABSTRACT FROM AUTHOR]