Journal of Chaohu University ›› 2023, Vol. 25 ›› Issue (6): 117-122.doi: 10.12152/j.issn.1672-2868.2023.06.015

Previous Articles     Next Articles

Static Stiffness Analysis and Fatigue Life Prediction of Rubber Suspension Based on DOE and CAE Technologies

DAI Jian-hui:School of Mechanical Engineering, Anhui University of Technology;SONG Chong-zhi:School of Mechanical Engineering, Chaohu University;WANG Long-yu:Anhui Tuosheng Auto Parts Co., Ltd.   

  1. 1. School of Mechanical Engineering, Anhui University of Technology, Maanshan Anhui 243002; 2. School of Mechanical Engineering, Chaohu University, Chaohu Anhui 238024; 3. Anhui Tuosheng Auto Parts Co., Ltd. Guangde Anhui 242200
  • Received:2023-10-25 Online:2023-11-25 Published:2024-05-28

Abstract: This paper addresses the issue of not being able to quickly determine the parameters of the main spring under the required static stiffness during the early design stage of the rubber suspension of the powertrain, and improving its fatigue life. A method using Taguchi design and finite element analysis is proposed. Orthogonal experimental design of rubber suspension parameters is conducted using Minitab, and a finite element model is established in ABAQUS to analyze the vertical (V-direction) static stiffness of the suspension. The goal is to improve the number of fatigue lives under the condition of meeting the set target stiffness of the suspension. Through regression analysis, the relationship between vertical static stiffness, fatigue life, and various parameters is obtained, and the response function of stiffness and fatigue life is established. Using the response optimizer, the parameters of the main spring are obtained. Through finite element analysis, it is found that the fatigue life of the suspension has increased by 62.76% within the allowable range of static stiffness, providing a reference for the early design and development of rubber suspensions.

Key words: rubber suspension, orthogonal test, finite element analysis, static stiffness, fatigue life

CLC Number: 

  • TQ332