Dual-scale parametric modeling and optimal design method of CFRP automotive roof beam

The application of CFRP in car body is more and more extensive, which brings new challenges to the parametric modeling and design of body components. This study takes the structural shape as the macroscale design pa-rameters of CFRP parts, takes the lamination scheme as the mesoscale design parameters. The mesoscale para-metric design and modeling methods are studied and coupled with existing macroscale parametric models to develop a dual-scale full parametric model. On this basis, the dual-scale parametric optimization method is established, which can regulate the performance by freely switching and merit matching of each scale parameter. This method is applied to the optimal design of CFRP automotive roof beam. The shape of the cross section, and variable-thickness lamination scheme are optimized collaboratively according to the three-point bending stiff-ness of the beam. The product is manufactured and tested according to the design results to verify the feasibility of proposed methods, achieving a 13.5% weight reduction, 11.2% increase in load capacity, and 19.3% increase in bending stiffness. This study provides theoretical basis and common technique for the parametric modelling and design of CFRP parts, enables the direct evaluation of part performance with different macro-shapes and meso-lamination schemes.

Automated summary

The study focuses on the parametric modeling and design of CFRP body components for cars. The macroscale design parameters are the structural shape, while the mesoscale design parameters are the lamination schemes. A dual-scale full parametric model is developed by combining the macroscale and mesoscale parametric models. A dual-scale parametric optimization method is established to regulate the performance by switching and matching each scale parameter. The method is applied to the optimal design of a CFRP automotive roof beam, resulting in weight reduction, increased load capacity, and bending stiffness.