摘要
工程实际中,汽车动力总成悬置系统不可避免地存在着一定的参数不确定性,且不确定参数间往往同时存在一定的相关性与独立性。本文中引入多维平行六面体模型处理系统参数相关性和独立性并存的情形,结合蒙特卡洛法提出了一种悬置系统固有特性的不确定性分析方法,并给出了方法的分析步骤。对某悬置系统的数值分析结果表明:该方法能有效处理系统不确定参数的相关性和独立性,与未考虑参数相关性的区间方法相比,该方法能获得更为合理的固有频率和解耦率区间范围;对于给定的研究模型,其左右悬置点的刚度相关性对系统固有特性的影响比较明显,在设计和研究过程中应给予重点关注。
In engineering practice,it is inevitable that parametric uncertainties exist in the powertrain mounting system(PMS)of a vehicle and there is simultaneously a certain correlation and independence between the uncertain parameters.In this paper,the multidimensional parallelepiped model(MPM)is introduced to deal with the case of the co-existence of the system parameter correlation and independence,and a method of uncertainty analysis of the inherent characteristic of the mounting system is proposed by combining the Monte Carlo method.The analysis procedure of the proposed method is presented as well.The numerical analysis results of a mounting system show that the proposed method can effectively deal with the correlation and independence of the uncertain parameters of the system.Compared with the interval methods without considering parameter correlation,the proposed method can obtain more reasonable interval responses of natural frequencies and decoupling rates.Furthermore,for the given investigated model,the stiffness correlation of the left and right mounting points has obvious influence on the system inherent characteristics,which should be paid a special attention in the process of design and research.
作者
吕辉
杨坤
尹辉
上官文斌
于德介
Lü Hui;Yang Kun;Yin Hui;Shangguan Wenbin;Yu Dejie(School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641;Hunan University, State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Changsha 410082)
出处
《汽车工程》
EI
CSCD
北大核心
2020年第4期498-504,共7页
Automotive Engineering
基金
国家自然科学基金(51975217,51605167)
广州市科技计划一般项目(201804010092)
中央高校基本科研业务费项目(2019MS058)资助。
关键词
动力总成悬置系统
多维平行六面体模型
固有频率
解耦率
不确定性分析
powertrain mounting system
multidimensional parallelepiped model
natural frequency
decoupling ratio
uncertainty analysis
