A Reliability Analysis Method for Powertrain Mounting Systems of Electric Vehicles

被引：0
|
作者：
Li W. [1 ]
Mao H. [3 ]
Lü H. [1 ,2 ]
机构：
[1] State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha
[2] Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing
[3] School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou
来源：
Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences | 2023年 / 50卷 / 04期
基金：
中国国家自然科学基金; 国家重点研发计划;
关键词：
correlation; electric vehicles; imprecise information; powertrain mounting system（PMS）; reliability;
D O I：
10.16339/j.cnki.hdxbzkb.2023154
中图分类号：
学科分类号：
摘要：
To handle the complex cases that the uncertain parameters of the Powertrain Mounting Systems （PMSs）of electric vehicles are of imprecise information and correlation，a reliability analysis method of electric vehicle PMS is proposed by considering the imprecise information and correlation of PMS parameters. Firstly，evidence variables were employed to describe the parametrical imprecise information，and the correlation between evidence variables was described by the correlation coefficient matrix. Then，based on the affine transformation and standardization techniques，the relevant evidence variables were transformed into standard irrelevant evidence variables. Finally，by calculating the inherent characteristic response of the PMS as well as the belief function and plausibility function that meets design requirements，the reliable probability intervals of PMS responses were evaluated. The reliability analysis results of the numerical example of an electric vehicle PMS show that the parametrical imprecise information and correlation can be effectively handled by the correlated evidence variables；the parametrical imprecise information has a great influence on the system reliability，especially on the reliability related to the natural frequency in Roll direction；the system reliability changes obviously as the parametrical correlation increases，and ignoring the parametrical correlation may lead to large errors of reliability analysis. © 2023 Hunan University. All rights reserved.
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页码：55 / 64
页数：9
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