An efficient analysis and optimization method for the powertrain mounting system with hybrid random and interval uncertainties

Abstract

In the traditional uncertainty-based analyses and optimizations of the automotive powertrain mounting system (PMS), uncertain parameters are usually treated as either random variables or interval variables. In this article, an efficient analysis and optimization method is proposed for PMS designs with hybrid random and interval uncertainties. An efficient analysis method, named the hybrid perturbation–finite difference method (HPFDM), is first derived to calculate the uncertain responses of the natural frequencies (NFs) and the decoupling ratios (DRs) of the PMS. Then, an optimization model of the PMS with hybrid uncertainties is established based on the HPFDM, where the uncertain responses of the relevant NFs and DRs are taken to create optimization constraints and optimization objectives. With the aid of the HPFDM, the nested optimization model can be solved efficiently. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed method.

KEYWORDS:

• Powertrain mounting system
• hybrid uncertainties
• random variable
• interval variable
• analysis and optimization

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 51975217, 51605167]; Science and Technology Program of Guangzhou [grant number 201804010092]; Fundamental Research Funds for the Central Universities, SCUT [grant number 2019MS058].