A Theoretical Optimization Method Of Drawbead In Automotive Panel Forming Based On Plastic Flow Principles

Automobile industry is the important carrier of "Made in China 2025" strategy,and the intelligent manufacturing of panel dies is the key technology of automobile industry.Drawbead,which is an important process parameter of panel dies,plays a vital role on the forming quality of automotive panels.In order to get rid of the current situation that the drawbead design relies on the experience of technical personnel,many scholars have studied the drawbead optimization methods.Existing optimization methods,which have a very low efficiency,are not suitable for the process optimization of complex automotive panels forming,and the existing commercial software has no practical optimization module.Therefore,the study of an efficient and practical drawbead optimization method in automotive panel forming has an important value of theoretical research and practical application.Under the support of the National Industrial Restructuring,Upgrading and Foundation Strengthening Project(Implementation Plan of Automotive Precise Multistage High-Efficiency Progressive Die for Automobiles),a new theoretical optimization method of drawbead in the forming process of automotive panels is presented by establishing a digital model of forming defects,plastic flow principles and an iterative learning control model.Essentially different from the existing common optimization methods,which are on the basis of mathematics or imitating natural phenomena,the method in this paper,which accurately reflects the relationship between the forming defects and the plastic flow principles,has higher optimization efficiency for multi-variable and multi-objective drawbead optimization of complex automotive panels.In order to accurately describe the defect generation and evolution,a digital model of forming defects in automotive panel stamping is established.Conventional forming defects are judged and qualified by the forming limit diagram.Special forming defects,which cannot be judged by the forming limit diagram,are judged by the new digital model proposed.The establishment of the perfect digital model of forming defects is the precondition of the accurate drawbead optimization results.In order to reflect the relationship between the drawbead and the forming defects in the optimization process,drawbead optimization principles are established based on the plastic flow theory.A fracture-direction affected principle and a sector affected principle are proposed to determine the drawbead zones,which can improve the forming defects.A principle of the feeding resistance of the characteristic section line and a strain-state affected principle are proposed to determine the influence degree of the drawbead restraining force to the forming defects.The drawbead optimization principles,which can determine the influence degree of the drawbead to the forming defects,ensure the accuracy and rapidity of drawbead optimization.In order to accurately determine the search direction and adjustment quantity in drawbead optimization process,an iterative learning control model,which consists of a forming quality evaluation function of drawbead segments and a learning updating law,is established.The forming quality evaluation function of drawbead segments,which evaluates the global defect degree in the affected zone of drawbead,can determine the search direction from the perspective of the plastic flow theory,and improves the efficiency.The learning updating law,which considers the forming quality deviation and has learning abilities,can further accelerate the convergence speed.On the basis of the iterative learning control model,a new theoretical optimization method of drawbead is put forward.Compared with the existing optimization method,the method has a higher optimization efficiency and accuracy.In order to verify the effectiveness of the theoretical drawbead optimization method,the optimization method is integrated into FAST AMP,which is a forming simulation software of automotive panels developed independently,and some typical parts are chosen to test the drawbead optimization.The optimization results demonstrate that this optimization method can accurately reflect the relationship between drawbeads and forming defects,and control the generation of forming defects.It not only reduces the dependence on the design experience,but also improves the optimization efficiency,which is of great significance to improve the intelligent level of die design for automotive panels.