Ply Optimization of Backrest Skeleton of Carbon Fiber Reinforced Plastic Car Seat Based on Grey Euclidean Relational Analysis Method

In this paper, an improved grey Euclidean relational analysis method based on Euclidean distance was proposed, which was based on the traditional grey relational analysis method. This method was applied to the material-structure integrated design of the backrest skeleton of a car seat. Firstly, the steel backrest skeleton of a car seat was replaced by carbon fiber reinforced plastics (CFRP), and the backrest skeleton was designed as an integrated structure. Its weight was reduced by 1.69 kg (39.12 %) while still meeting various seat performance test requirements. Then, the effect of the ply design on the performance of car seats with CFRP was studied, and the optimal layer scheme of CFRP backrest skeleton of car seats was obtained by combining the grey Euclidean relational analysis method. Finally, the method proposed in this paper was compared with the widely used method. The results showed that the optimization schemes obtained by the two methods greatly improved performance indicators, especially L_R_2 which had an improvement rate of 13.31 %. Additionally, the proposed method reduced computing resources by 95 %, indicating its ability to effectively balance optimization results and calculation efficiency.