Performance Analysis and Multi-Objective Optimization of Functional Gradient Honeycomb Non-pneumatic Tires

Abstract The spoke as a key component has a significant impact on the performance of the non-pneumatic tire (NPT). The current research has focused on adjusting spoke structures to improve the single performance of NPT. Few studies have been conducted to synergistically improve multi-performance by optimizing the spoke structure. Inspired by the concept of functionally gradient structures, this paper introduces a functionally gradient honeycomb NPT and its optimization method. Firstly, this paper completes the parameterization of the honeycomb spoke structure and establishes the numerical models of honeycomb NPTs with seven different gradients. Subsequently, the accuracy of the numerical models is verified using experimental methods. Then, the static and dynamic characteristics of these gradient honeycomb NPTs are thoroughly examined by using the finite element method. The findings highlight that the gradient structure of NPT-3 has superior performance. Building upon this, the study investigates the effects of key parameters, such as honeycomb spoke thickness and length, on load-carrying capacity, honeycomb spoke stress and mass. Finally, a multi-objective optimization method is proposed that uses a response surface model (RSM) and the Nondominated Sorting Genetic Algorithm - II (NSGA-II) to further optimize the functional gradient honeycomb NPTs. The optimized NPT-OP shows a 23.48% reduction in radial stiffness, 8.95% reduction in maximum spoke stress and 16.86% reduction in spoke mass compared to the initial NPT-1. The damping characteristics of the NPT-OP have also been improved. The results offer a theoretical foundation and technical methodology for the structural design and optimization of gradient honeycomb NPTs.