According to the honeycomb structure, the preliminary design of bionic wheel hub for finite element analysis, in the working condition of a wheel by the force is through the spokes pointing to the center, the working condition of two wheel by the force is through the two spokes pointing to the center, and the ordinary wheel stress and displacement value results compared, observed the maximum stress value appears in the connection between the center of the wheel and the spokes, and predict the fatigue life of the preliminary design of bionic wheel. Using finite element analysis and response surface optimization analysis method for numerical simulation, through two optimization results show that, in the use of response surface analysis model optimization, the optimized bionic wheel maximum stress is 109.34MPa, compared with the ordinary wheel maximum stress 119.77MPa, the maximum stress reduced by 8.7%. The mass of the ordinary wheel is 34.02Kg, using the response surface optimization method, the optimized wheel mass is 29.89Kg, the mass reduced by 12.13%. The optimized wheel fatigue analysis, in the stress of 109.34MPa, load loading times at least 4.217e+005, in the position at the junction with the half shaft. In line with the national standard GB/T 5334-2021[16] for commercial vehicle wheel fatigue life requirements.

The application of neural network model in engineering prediction is frequent. The BPE shell material was optimized, and the reliability of the new material was verified by modal simulation. The accuracy of finite element modeling was ensured by constrained mode experiments, and all variables were preprocessed by Latin hypercube sampling. The design parameters were determined by Monte Carlo simulation. Four different neural networks, including back propagation (BP), radial basis function (RBF), extreme learning machine (ELM) and wavelet neural network (WNN), are used to train and learn the dataset. The BPE weight reduction ratio was 14.3%, the stress was reduced by 18.6%, deformation displacement was reduced by 14.2%, and the first-order mode was increased by 29.1%.