Regular Article

Determining optimal suspension system parameters for spring fatigue life using design of experiment

¹ Centre for Integrated Design for Advanced Mechanical Systems (PRISMA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
² Departmental Chair of Mechatronics, University of Duisburg-Essen, 47057 Duisburg, Germany

^* e-mail: knnthkong@hotmail.com

Received: 4 October 2018
Accepted: 28 September 2019

Abstract

This paper presents the optimization of spring fatigue life associated with suspension system parameters using the design of experiment approach. The effects of suspension parameters on spring fatigue life were analyzed because this process can improve spring fatigue life from a distinct perspective. A quarter car model simulation was performed to obtain the force time histories for fatigue life prediction where the suspension parameters were adjusted. Multiple input regression and interaction plots were conducted to identify the interaction between these parameters. A full factorial experiment was performed to determine the optimal suspension settings that would maximize the spring fatigue life. For the regression, a high R ² value of 0.9078 was obtained, indicating good fitting. The established regression showed normality and homoscedasticity for consistent prediction outcome. Reducing the spring stiffness and sprung mass while enhancing the damping coefficient is therefore suggested to enhance fatigue life.