Wang Jinle, Yang Bing, Tian Honglei, Wang Wenbin, Sang Xu
State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, China.
CRRC Qingdao Sifang Co., Ltd., Qingdao 266111, China.
Materials (Basel). 2025 May 27;18(11):2524. doi: 10.3390/ma18112524.
This study systematically investigates the optimization design and mechanical performance of carbon fiber-reinforced polymer (CFRP) load-carrying structures for subway driver cabins to meet the lightweight demands of rail transit. Through experimental testing and micromechanical modeling, the mechanical properties of CFRP and foam core materials were characterized, with predicted elastic constants exhibiting an error of ≤5% compared with experimental data. A shape optimization framework integrating mesh morphing and genetic algorithms achieved a 22% mass reduction while preserving structural performance and maintaining load-carrying requirements. Additionally, a stepwise optimization strategy combining free-size, sizing, and stacking sequence optimization was developed to enhance layup efficiency. The final design reduced the total mass by 29.1% compared with the original model, with all failure factors remaining below critical thresholds across three loading cases. The increased failure factor confirmed that the optimized structure effectively exploited the material's potential while eliminating redundancy. These findings provide valuable theoretical and technical insights into lightweight CFRP applications in rail transit, demonstrating significant improvements in structural efficiency, safety, and manufacturability.
本研究系统地研究了用于地铁驾驶室的碳纤维增强聚合物（CFRP）承载结构的优化设计和力学性能，以满足轨道交通的轻量化需求。通过实验测试和微观力学建模，对CFRP和泡沫芯材的力学性能进行了表征，预测的弹性常数与实验数据相比误差≤5%。一个集成网格变形和遗传算法的形状优化框架在保持结构性能和承载要求的同时实现了22%的质量减轻。此外，还开发了一种结合自由尺寸、尺寸和铺层顺序优化的逐步优化策略，以提高铺层效率。最终设计与原始模型相比总质量降低了29.1%，在三种加载情况下所有失效因子均保持在临界阈值以下。增加的失效因子证实了优化后的结构有效地利用了材料的潜力，同时消除了冗余。这些发现为CFRP在轨道交通中的轻量化应用提供了有价值的理论和技术见解，证明了在结构效率、安全性和可制造性方面的显著改进。
