The Design Of Injection Mold For Automobile Refueling Cap And The Optimization Of Forming Process Parameteers

The development of the automobile industry is especially rapid in the last ten years.The massive consumption of energy by automobiles and the excessive emission of exhaust have also caused the environment to become worse.This problem has become a difficult problem facing the world today,and it is also a hot topic nowtodays.The application of lightweight technology on the body can reduce environmental pollution and reduce the weight of the car body,thereby reducing the consumption of resources and promoting the stable and continuous progress of the automotive industryThe material of the traditional automobile fuel filler cover is mostly ferrous metal material,which is heavier in weight and adopts a stamping forming manufacturing process,which has a higher manufacturing cost.However,the technology of replacing ferrous materials with high-molecular materials has now appeared.Direct injection molding effectively reduces the product molding cycle,reduces product weight,and reduces costs.This experiment will study the injection mold and analyze the injection molding technology and molding process parameters,optimize the design,and verify the simulation.The object of this research is the plastic filler cap of a certain car.The CATIA software will be used to design the structure of the filler cap of the car,and to design and analyze the injection mold of the filler cap.With the help of Moldflow2017,the injection molding process of the outer cover of the fuel filler is simulated,and the orthogonal test method be employed in discussing and studying the process parameters affecting the injection process,and multiple evaluation indicators are analyzed and verified by a comprehensive scoring method.The data is used to establish the BP neural network of the fuel filler cover warpage model,and the genetic algorithm is used to optimize the process parameters.The research content will be introduced from the following sections:(1)First,use CATIA software to model the fuel filler cover three-dimensionally,and analyze the feasibility of replacing plastic with plastic products.At the same time,use CAE software such as ANSYS to analyze the modal and stiffness of the fuel filler cover of the selected plastic material.Good material selection,in order that the modal and mechanical properties of the product can be met while improving.(2)UG was used to design the injection mold for the cover plate of automobile refueling mouth,including the calculation of the size of various internal components,and the determination of pouring and cooling system.After comparing the influence of pouring and cooling system under different schemes on injection molding,the best pouring system and cooling system was finally selected.(3)Five process parameters are selected,warpage and volume shrinkage are used as evaluation indexes to carry out orthogonal test combination design,Moldflow is used to carry out simulation analysis on each combination injection molding process,and mean and variance methods are used to evaluate the influence of each test factor on warpage and volume shrinkage,so as to determine the best combination of injection molding process parameters.(4)On the basis of orthogonal experiments,the BP neural network model of the filler cap plate is established.Genetic algorithm is used to optimize the process parameters in the injection molding process of the plastic filler cap plate for automobiles,and the best combination is determined within the allowable error range and the simulation results are obtained.Innovations in this research:(1)Use PA composite materials instead of metal materials,and use the theory of equal strength to design plastic filler caps,and at the same time check whether the stiffness and modalities meet the requirements,and use CAE software to simulate the best injection molding system and cooling system.(2)Use the BP neural network to construct the warping model of the plastic filler cover.With the help of genetic algorithm,the spatial parameters are encoded into chromosomes,and the genetic algorithm is used to optimize the trial algorithm to obtain the best process combination.