An Optimal Design of Vehicle Swing Door Using Metamodeling Techniques

In side-closures’ design, mass reduction provides numerous benefits in addition to reduced cost. This paper presents a Meta model based non-linear durability optimization to develop a lightweight structure for vehicle swing door. A surrogate model developed is using Kriging methodology and the thickness of the door components are given as input design variables. Adaptive Multi-Objective Genetic Algorithm (AMGA), a nonlinear optimization technique, is used in this study, to formulate the mass minimization under durability constraints. The optimized swing door design shows the overall mass saving of ~10% over initial design in terms of frame and sag deflection. The present investigation shows better effectiveness and practical applicability to develop the lightweight structure for the vehicle swing door. From the comparative study, Kriging method is found to be more effective in terms of measuring the accuracy, robustness and efficiency of the results than the Radial basis function (RBF).