Research Article Analytical Design and Optimization of an Automotive Rubber Bushing Jonathan Rivas-Torres, 1 Juan C. Tudon-Martinez , 1 Jorge de-J. Lozoya-Santos, 2 Ricardo A. Ramirez-Mendoza, 2 and Andrea Spaggiari 3 1 Universidad de Monterrey, Ignacio Morones Prieto 4500, Jes´ us M. Garza, 66238 San Pedro Garza Garc´ ıa, NL, Mexico 2 Tecnol´ ogico de Monterrey, Av. E. Garza Sada, Col. Tecnol´ ogico, 64849 Monterrey, NL, Mexico 3 Universit` a degli Studi di Modena e Reggio Emilia, Via Giovanni Amendola, 2, 42122 Reggio Emilia, Italy Correspondence should be addressed to Juan C. Tudon-Martinez; juan.tudon@udem.edu Received 6 November 2018; Revised 3 February 2019; Accepted 20 February 2019; Published 26 March 2019 Academic Editor: Jussi Sopanen Copyright © 2019 Jonathan Rivas-Torres et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e ride comfort, driving safety, and handling of the vehicle should be designed and tuned to achieve the expectations defined in the company’s design. e 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. is 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. 1.Introduction Bushings are used in the automotive industry to improve ride comfort, safety, and handling. With the continued development of chassis dynamics, the ability of the sus- pension to execute precisely defined movements in response to applied forces has become more important. Chassis dy- namics engineers require that suspension components ex- ecute precisely specified movements in many different directions. e required force-displacement behaviors lead to increased expectations for the design of the bushings. In order to achieve the current level of noise attenuation, rubber bushings and mounts have been used to solve a number of conflicts between the requirements for vehicle handling and cabin acoustics. e high-frequency charac- teristics of the rubber-metal components themselves are dependent not only on the properties of the materials but also on the geometries and assembly techniques used [1]. During the vehicle development process, optimization of the rubber products is also needed to have target stiffness curves [2]. Design objectives usually include structural weight and cost [3]. Ride comfort and harshness performance of the vehicle can be improved by optimizing the characteristics of the suspension system components [4]. ere is some related work that can be found in the literature about optimizing techniques in automotive applications, specifically in sus- pension components. Kaya [2] performed an optimization ofshapeofarubberbushingusingaPascalcodebasedonthe differential evolution algorithm. is method is particularly suited where there is no relationship between the objective function and the design variables. Kaldas et al. [4] developed an optimization technique to improve vehicle ride comfort and harshness using a genetic algorithm to determine the Hindawi Shock and Vibration Volume 2019, Article ID 1873958, 13 pages https://doi.org/10.1155/2019/1873958