基于HyperMesh的汽车中控台装配变形仿真分析与优化

针对汽车中控台在装配时泡棉压缩所引起的变形问题，通过压缩试验测得泡棉的应力-应变曲线，基于HyperMesh建立（computer aided engineering，CAE）模型并使用LS-DYNA进行求解。同时建立实际模型，以相关安装点的变形量为基准，对比实际值与仿真值，对仿真模型进行验证。基于验证后的仿真模型，研究泡棉材料、仪表板材料和仪表板厚度对安装点变形量的影响，得到最优参数方案。结果表明：仿真值与实际值的误差在±20%以内，符合工程应用要求，验证了CAE模型的合理性；在模型中，泡棉材料对安装点变形量的影响最大，仪表板厚度次之，仪表板材料最小；泡棉材料为聚乙烯（polyethylene，PE），仪表板材料为聚碳酸酯（polycarbonate，PC）+丙烯腈-丁二烯-苯乙烯（acrylonitrile butadiene styrene，ABS），仪表板厚度为3 mm时，相关安装点变形量的平均值为1.041 mm，方差为0.062 mm²，变形量最接近目标值，且分布最均匀。

Simulation Analysis and Optimization of the Automobile Central Console Assembly Deformation Based on Hyper Mesh

According to the deformation problem caused by the foam compression during the assembly of the automobile central console, the stress-strain curve of the foam was measured by the compression test, the computer aided engineering (CAE) model was established based on HyperMesh and solved by LS-DYNA. At the same time, the actual model is established, and based on the deformation of the relevant installation point, the simulation model is verified by comparing the actual value with the simulation value. Based on the verified simulation model, the influence of foam material, instrument panel material and instrument panel thickness on the deformation of the installation point was studied, and the optimal parameter scheme was obtained. The results show that the error between simulation value and actual value is within ±20%, which meets the requirements of engineering application and verifies the rationality of CAE model. In the model, the foam material shows the greatest influence on the deformation of the installation point, the thickness of the instrument panel is the second one, and the material of the instrument panel is the smallest. When the foam material is polyethylene (PE), the instrument panel material is polycarbonate (PC) + acrylonitrile butadiene styrene (ABS), and the thickness of the instrument panel is 3 mm, the average deformation value of the relevant installation point is 1.041 mm, and the variance is 0.062 mm². The deformation is the closest to the target value and the most evenly distributed.