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A novel non-pneumatic safety tire, namely mechanical elastic wheel (ME-Wheel), has been developed recently to solve problems, including tire bursting and flat tire, of typical pneumatic tires. This paper aims to predict the life of the ME-Wheel accurately and settle the problem of lower lifespan.

This study proposes a new method to establish a novel model of virtual proving ground based on finite element analysis, and by combining with the random vibration damage analysis method, the life of an ME-Wheel is predicted precisely. Next, the weak parts and infinite life parts of the ME-Wheel are investigated from the perspective of constant life design, and an approximate response surface model is developed, which is suitable for the ME-Wheel. Then, the optimal results of the ME-Wheel are obtained, including tire modal, mass and its lifetime.

It is found that the proposed methods can provide a reliable theoretical basis for further improving the structural design and material selection of ME-Wheel parts. The results show that the improved ME-Wheel can reduce the weight and greatly improve the ability of anti-resonance, and the lifetime of ME-Wheel has significantly improved.

A new type of non-pneumatic tire (ME-Wheel) has been developed to avoid problems with traditional tires, such as tire leaking or puncture. A new method to establish a novel model of virtual proving ground based on finite element analysis has been proposed. The weakest key component of the ME-Wheel is determined. The life, mass and modal of the ME-Wheel are optimized.

A general approach for the construction of global approximations to structural behaviour using response surface methodology is presented. The computation and use of these approximations are demonstrated using a semi‐solid tyre example. The use of these global approximations to the responses made it viable to utilise the capabilities of non‐linear analysis software in design optimisation. The insight gained from a preliminary low fidelity model was utilized in a two‐stage approach to achieve the maximum benefit from a more expensive high fidelity model. The resulting high‐accuracy approximations greatly reduced the cost of subsequent design calculations such as multidisciplinary and discrete optimisation.