Research on Key Technologies for Optimization of Forming Parameters of Aluminum Alloy Hood Outer Panel

Abstract

At present, computer technology and finite element software analysis technology have been widely used in the stamping and forming process of aluminum alloy hood outer plate to predict the possible quality defects in the stamping process, and effectively improve the quality and production efficiency of parts. The stamping and forming of the outer plate of the automobile aluminum alloy hood is a highly nonlinear process, and its forming quality involves many forming factors, if the variable design is not reasonable, it may lead to quality defects such as wrinkles or cracks of the molded parts. Due to the relatively complex shape and structure of the aluminum alloy hood outer plate and its high requirements for the quality of forming, it is difficult to obtain the optimal process parameters in a short time if the finite element software simulation optimization is carried out manually. The machine learning algorithm is applied to the research on the stamping and forming of the outer plate of the aluminum alloy hood, and the multi-objective genetic algorithm is used to optimize the stamping process parameters of the covers, which can meet the maximum thinning rate of the formed parts and control the rebound of the formed parts to a certain extent. How to combine machine learning algorithms with finite element simulations to reasonably adjust the process parameters in the stamping and forming process by using machine learning algorithms to meet the forming quality requirements of aluminum alloy hood outer plate has always been a research hotspot and difficulty in the field of aluminum alloy hood outer plate stamping.