Structural optimization design of thermal and mechanical characteristics for run-flat tires

Run-flat tire (RFT) allows the vehicle to continue driving even when the tire is deflated. Compared to a normal tire, there are significant differences in heat generation and mechanical performance under zero pressure, which causes a decrease in the driving range of the RFT. This study focuses on pneumatic RFTs and proposes a standardized simulation process. The tire force-displacement curve obtained through static tests shows good agreement with the simulation results. The thermal performance design parameters of the RFT are established, and simulations combined with neural network algorithms optimize its thermal and mechanical performance. The results indicate that the PSO-BP model achieves an R 2 greater than 0.96, demonstrating the accuracy of the optimization method. For self-supporting run-flat tires, improvements are observed in Mises, normal contact pressure, and maximum temperatures by up to 7.01%. In the case of inserts supporting run-flat tires, lightweight performance increased by 25.34%, and the maximum tread temperature decreased by 5.2%, though radial stiffness was reduced by 7.47%. This study established a Thermal and mechanical simulation process applicable to RFTs and utilized a neural network for optimized design, laying the foundation for the subsequent structural design of RFTs and the simulation of multi-field coupling.