Optimization Of Forming Process And Multi-scale Co-simulation Of Composite Plastic Parts For Automotive Engine Bottom Protection Plate

With the development of automobile industry,lightweight design has become one of the important ways to solve the problems of air pollution and energy consumption.Fiber composites are widely used in automobile lightweight due to their excellent mechanical properties and lightweight properties.As one of the main molding methods of fiber composites,injection molding often has various defects.Therefore,it is necessary to optimize the injection process parameters to improve the molding quality of plastic parts and accurately evaluate their service performance.However,the traditional structural simulation methods often ignore the anisotropy of materials and the uneven distribution of fiber orientation,which makes it difficult to accurately predict the mechanical properties of the components.In order to solve the above problems,the multi-scale co-simulation method is adopted in this paper,and the influence of various factors on the mechanical properties and forming quality of plastic parts is considered comprehensively to obtain the best quality plastic parts.The main research contents are as follows:1.Taking standard tensile splines as the research object,based on the relevant theories of co-simulation,firstly,the orientation distribution of fibers was obtained through Moldflow,and then the stress-strain data of composites was predicted by Digimat.Then,the fiber orientation,residual strain and material model were mapped to the Ansys structure grid using Helius-PFA.Finally,the obtained co-simulation stress distribution was co MPared with the traditional simulation,which verified the feasibility of the multi-scale co-simulation method.2.The co-simulation method is applied to the bottom guard plate of automobile engine,and the modal and statics analysis results of the optimized structure are predicted accurately.The effect of gate number and fiber parameters on mechanical properties was investigated by multi-scale co-simulation method,and the appropriate pouring scheme and fiber parameters were determined by taking equivalent stress and total deformation as evaluation indexes.3.In order to improve the molding quality of plastic parts,the mold pouring system and cooling system were optimized.Firstly,the influence of three gate schemes on injection molding quality was explored,the optimality of four gate schemes was verified,and the sequential valve gate design was used to eliminate surface defects.Secondly,the initial cooling scheme and the form-following cooling scheme are co MPared,and the results show that the form-following cooling scheme can greatly improve the warping deformation and forming efficiency.Finally,the influence of cooling medium temperature and flow rate on the cooling effect is explored,and the better cooling medium parameters are determined.4.With mold temperature,melt temperature,injection time,pressure holding pressure,pressure holding time and cooling time as design variables,and warping deformation and maximum stress under co-simulation as optimization objectives,orthogonal experimental scheme was established;Combined with the signal-to-noise ratio algorithm and grey relational degree analysis method,the influence law of each factor on the comprehensive index is obtained.The RBF neural network model was established,and the optimal process parameter combination was obtained by using NSGA-Ⅱ algorithm after error analysis.The effectiveness of the optimization results was verified by simulation results.