Optimization Of The Hot Stamping Forming Process For High Strength Steel Laser Tailored Welding Plate B-pillar Based On Response Surface Methodology

The use of high-strength steel hot stamping forming technology can improve the strength of car body components while also reducing their weight,and is currently widely used in the manufacturing of car body parts.Taking the automobile B-pillar studied in this article as an example,reasonable control of the distribution of mechanical properties of the material can be achieved by combining the low strength and high strength areas of the formed parts,which can better ensure the safety of the automobile.This project uses laser tailor-welded blanks made of Usibor1500 P and Ductibor500 steel plates as the substrate.The numerical optimization of the hot stamping process for high-strength steel laser tailorwelded blanks is studied through isothermal uniaxial tensile testing,finite element simulation,response surface methodology,genetic algorithm,and hot stamping experiments.The research content of this article is as follows:This article conducted isothermal uniaxial tensile tests on the two substrates of highstrength steel laser welded blanks,Usibor1500 P and Ductibor500,respectively.The thermal physical properties of the relevant materials were obtained through the tests,and the stressstrain curves under different temperature and strain rate conditions were analyzed.Two constitutive models of high-strength steel plates were established and modified.The curves fitted by the modified constitutive model can more accurately describe the rheological stress changes of the two high-strength steel plates during the hot stamping process compared to the original curves.In the ABAQUS simulation environment,the main characteristic U-shaped section of the B-pillar studied in this paper was selected as the research object,and a thermomechanical coupling model of the hot stamping process was established.The finite element simulation of the hot stamping process was carried out using speed,temperature,time,and friction coefficient as control parameters for numerical simulation,The effectiveness of the thermal coupling model and data for the hot stamping process of high-strength steel laser welded blanks has been demonstrated through analysis of simulation results and experimental verification.Conduct single factor simulation experiments on different process parameters,analyze the influence of different process parameters on the hot stamping forming stage,and find the following laws: as the initial temperature of the mold increases,the maximum equivalent stress of the sheet gradually decreases,and the thinning rate gradually increases;As the stamping speed continues to increase,the maximum equivalent stress of the sheet gradually decreases,and the thinning rate also gradually decreases.At the end of the forming process,the maximum temperature of the sheet gradually increases;As the initial temperature of the mold gradually increases,the maximum equivalent stress of the sheet gradually decreases,the thinning rate continuously increases,and the highest temperature at the end of sheet forming gradually increases.As the friction coefficient increases,the maximum equivalent stress of the plate shows a large trend,and the maximum thinning rate also shows an increasing trend.By combining numerical simulation and response surface modeling with multiobjective genetic algorithm,the simplified U-shaped parts of the automotive B-pillar hot stamping process parameters are optimized.The process parameters are friction coefficient,stamping speed,initial temperature of the sheet metal,and initial temperature of the mold.The maximum equivalent stress and thinning rate after forming are used as the objectives to determine the forming quality.The experiment is designed using the Box Behnken Design experimental design method in response surface.Establish a second-order response surface model between process parameters and forming quality objectives,and optimize process parameters by combining genetic algorithms.Verify the optimized process parameters through simulation analysis and experimental methods.