Weight Optimization and Reliability Prediction of an Automobile Torque Arm Subjected to Cyclic Loading

Abstract

The demands for lightweight, high-performance, low-cost structures are dramatically increasing, and that draws attention to research in the field of structural optimization. Designs of lightweight structures have become more important, especially in the automobile industry. The goal of this study is to obtain the optimum shape of an automobile torque arm and predict its reliability. Torque arm, part of the rear suspension, is subjected to cyclic loading. The stresses developed in the structure should not exceed the allowable stress, and fatigue life is another constraint due to cyclic loading. The optimization of torque arm requires calculation of the stresses and the fatigue life many times; therefore surrogate models (response surface approximations and Kriging) are used in this study to reduce the computational cost. Surrogate based optimization of the torque arm is performed by using the Optimization Module of ANSYS Workbench. After the optimum shape is determined, the reliability prediction of the torque arm is performed. In reliability prediction, tail modeling method, an adaptation of a powerful result from extreme value theory in statistics related to the distribution of exceedances, is utilized.