Multi-objective optimization of ventilation hole on steel wheel

Objective: In this thesis, it is aimed to optimize the structural design of the ventilation hole in the steel wheel used in heavy commercial vehicles, which has successfully passed the radial fatigue and cornering fatigue tests, and to reduce the weight of the wheel so that it can meet the test values compared to the existing wheel. Material and Methods: In this study, 4 different ventilation types, von-mises stress on the disc, number of ventilations and rim weight were parameterized using ANSYS Mechanical. These 4 different ventilation type wheels are separately compared with the stress results on the disc and the rim weights of the wheel with ellipse ventilation. Response surface optimization was created to compare the values obtained from the Design of Experiment (DoE) using the Response Surface Optimization (RSO) module in Ansys Workbench. In order to find the optimized design from the response surface optimization, optimization was made using the Multi-Objective Genetic Algorithm (MOGA-II) method. Results: Maximum iteration number is 20, convergence stability percentage is 2%, maximum allowable Pareto percentage is 70%, initial sample number is optimized as 6000, the result is 1,3,3 and 3 candidate design points from round, slot, trapezoid and half-moon type vents was created, respectively. Conclusion: Compared to the current design of the ventilation type, characterized as half-moon from the obtained approaches, the optimized rim exhibited a reduced mass of 0.9 Kilograms by 2.05%, which indicates the effectiveness of the proposed method. Since a lighter result could not be obtained at the same stress values in the other three different ventilation types, a halfmoon type ventilation hole was preferred. Key Words: Design of Experiment, Multi-Objective Genetic Algorithm, Finite Element Method, Radial Fatigue Test, Response Surface Optimization