Digital modeling and optimal design of tire carcass contour for durability performance enhancement

This study proposes a digital design method for the carcass contour, taking the Maximum Strain Energy Density (SED_max) at the tire shoulder as the evaluation index to systematically analyze the influence of different contour designs on tire durability. Optimization of the contour is then carried out using algorithmic methods to enhance durability. The optimization to achieve the collaborative improvement of tire durability and other mechanical properties is conducted. First, a finite element model (FEM) of a 12.00R22.5 all-steel radial truck tire is established and validated through static contact pressure distribution tests. Subsequently, the carcass contour is parameterized using Bézier curves to obtain a mathematical equation that represents the contour curve. Then, based on the contour design theory, the control points of the Bézier curve are selected as design variables. Using the orthogonal experimental method, nine distinct carcass contour design schemes are generated. Through range analysis, the influence of individual design variables on SED_max is identified, and a preliminary local optimal combination is obtained, resulting in a 7.03% reduction in SED_max. Finally, taking the orthogonal experimental schemes as sample data, a surrogate model is constructed via Gaussian Process Regression (GPR). The Multi-Island Genetic Algorithm (MIGA) is employed to determine the globally optimal carcass contour. The numerical results demonstrate that the optimized scheme achieves a 7.57% reduction in SED_max compared to the original design. Simultaneously, the optimized tire exhibits improved traction performance and more uniform carcass cord force distribution, thereby enhancing the overall mechanical properties of the tire.