基于Polyflow仿真和Isight汽车油箱多目标工艺优化研究  

Research on Multi-objective Process Optimization Based on Polyflow Simulation and Isight of Automobile Fuel Tank

作　　者：王琳[1] 秦楠[1] 张宇白 WANG Lin;QIN Nan;ZHANG Yu-bai(School of Mechanical Engineering,Dalian University of Science and Technology,Dalian 116052,China)

机构地区：[1]大连科技学院机械工程学院,辽宁大连116052

出　　处：《塑料科技》2021年第1期120-124,共5页Plastics Science and Technology

摘　　要：为减小吹塑制件壁厚不均导致的翘曲问题,采用Polyflow软件对汽车油箱吹塑成型过程进行了模拟仿真,但是由于软件仿真计算过程极为缓慢,因此通过Isight软件首先对制件采用最优拉丁超立方抽样法随机采样,随后建立Kriging代理模型,减少软件仿真模拟时间,提高计算效率,并且通过模拟退火算法对代理模型进行全局寻优,对制件吹胀压力、吹胀时间、初始型坯温度以及初始型坯壁厚进行了多目标优化,以最终壁厚均匀性函数值为响应目标,从而获得一组最佳的工艺参数组合。结果表明:代理模型R2为0.97775,预测值与模拟值基本一致,模拟退火算法优化后最佳的成型工艺参数吹胀压力为0.304 MPa,吹胀时间为3.008 s,型坯初始温度为199.020℃,型坯初始壁厚为4.998 mm。为改善制件翘曲提供了一定的参考。In order to reduce the warpage problem caused by uneven wall thickness of blow molding parts,Polyflow software was used to simulate the blow molding process of automobile fuel tank.But because the software simulation process was very slow,therefore,the optimal Latin hypercube sampling method was used to randomly sample of the parts through the Isight software.Then the Kriging proxy model was established to reduce the simulation time of software and improve the computational efficiency.The global optimization of the proxy model was carried out through simulated annealing algorithm.Multi-objective optimization of blowing pressure,blowing time,initial parison temperature and initial parison wall thickness was carried out,and a group of optimal process parameters were obtained by taking the final wall thickness uniformity function value as the response objective.The results show that the R2 of the proxy model is0.97775,and the predicted value is basically consistent with the simulated value.The optimal forming process parameters optimized by the simulated annealing algorithm are blowing pressure 0.304 MPa,blowing time 3.008 s,initial parison temperature 199.020 ℃ and initial parison wall thickness 4.998 mm.It provides some reference for improving the warpage of the parts.

关 键 词：汽车油箱 最优拉丁超立方 Kriging代理模型 模拟退火算法 工艺优化 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术] TQ320.52[自动化与计算机技术—计算机科学与技术]