Structural optimization of knuckle under load uncertainty considerations

LIU Ying1,2, YAN Yang3, CHEN Tian-fu3, PANG Qiu4
(1.Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of
Technology, Wuhan 430070, China; 2.Hubei Collaborative Innovation Center for Automotive Components
Technology, Wuhan 430070, China; 3.Hubei Triring Forging Co.Ltd., Xiangyang 441700, China;
4.School of Mechanical and Electrical Engineering, Wuhan Donghu University，Wuhan 430212，China)

Abstract: Aiming at the problems of light weight design difficulty caused by complex geometric shape of automotive aluminum alloy knuckles, bearing random loads, harsh working conditions, and strict safety requirements, the structure optimization and design methods of the knuckle were investigated. The multi-body dynamic model of the double-wishbone suspension was established to get the load of the steering knuckle under typical working conditions. On account of the finite element simulation analysis of steering knuckle, the method of topology optimization to weight reduction design of steering knuckle was adopted. Based on the topological optimization results, the method of interval uncertainty robust optimization was used to perform the quadratic optimization of the steering knuckle, and the robustness of the optimization results was improved by considering the random load of the steering knuckle. A doublelayer nesting optimization model was designed for iterative calculation. On the other hand, the method of nonrepetition saturation factorial design was used to improve the efficiency of the quadratic optimization process and reduce the number of tests. The results indicate that the aluminum alloy steering knuckle can be lightweight and the weight reduction ratio can reach 7% on the basis of reducing the maximum stress value, and the performance of the steering knuckle can meet the technical requirements under the durability test.

Key words: lightweight design; aluminum alloy knuckle; topology optimization; interval uncertainty; structural optimization