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Analytical design and optimization of an automotive rubber bushing

*Corresponding author for this work
Research Output:
Contribution to journal
Article
Peer-review

Open access

Publication metrics

Metrics

SciVal
Citations
18
SciVal
FWCI
0.09
SciVal
Author count
5
SciVal
Paper percentile
28
Scopus
Citations

Abstract

The ride comfort, driving safety, and handling of the vehicle should be designed and tuned to achieve the expectations defined in the company's design. The ideal method of tuning the characteristics of the vehicle is to modify the bushings and mounts used in the chassis system. To deal with the noise, vibration and harshness on automobiles, elastomeric materials in mounts and bushings are determinant in the automotive components design, particularly those related to the suspension system. For most designs, stiffness is a key design parameter. Determination of stiffness is often necessary in order to ensure that excessive forces or deflections do not occur. Many companies use trial and error method to meet the requirements of stiffness curves. Optimization algorithms are an effective solution to this type of design problems. This paper presents a simulation-based methodology to design an automotive bushing with specific characteristic curves. Using an optimum design formulation, a mathematical model is proposed to design and then optimize structural parameters using a genetic algorithm. To validate the resulting data, a finite element analysis (FEA) is carried out with the optimized values. At the end, results between optimization, FEA, and characteristic curves are compared and discussed to establish the correlation among them.

Publication Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Article number

1873958

Journal (Volume, Issue Number)

Shock and Vibration (Volume 2019)

Publication milestones

  • Published - 26/03/2019

Publication status

Published - 26/03/2019

ISSN

1070-9622

Publication IDs

  • Scopus: 85064396916

Funding Details

-e authors thank Universidad de Monterrey and Università degli Studi di Modena e Reggio Emilia for their partial financial support to this research project.
FundersFunding numbersUniversidad de Monterrey-
UNIMORE
-