Shape optimization of lower control arm considering multi-disciplinary constraint condition by using progress meta-model method

This paper presents shape optimization of lower control arm considering multi-disciplinary (stiffness, strength and durability) constraint conditions. As non-linearity of strength and durability is large out of the design constraint conditions and performance indexes are defined as min-max values, sensitivity is not reflected and instead, a sequential approximate optimization (SAO) method using a meta-model is suggested. In order to verify the efficiency of the suggested design method, shape optimization design of a 1 piece-typed lower control arm for compact cars is conducted. The design target aims to meet the multi-disciplinary (stiffness, strength and durability) design constraint conditions and at the same time, intends to minimize the weight. Design variables are 3 shape vectors and 1 thickness while design constraint conditions include 2 stiffness, 12 strength and 26 durability variables, featuring a big design problem. As a result, the design problem is solved in total 3 interation and the optimal model meets all of the design constraint conditions and reduces the weight by about 200 grams comparing with that of the initial model. Thus, the suggested design method is an appropriate method suitable for shape optimization design.