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In order to solve the problems of long time, high cost and low efficiency in the lightweight design and optimization process of new automobile frame, the lightweight optimization design method of new automobile frame based on deep learning algorithm was proposed. According to the load and length of the target frame, a mathematical model is established with the minimum weight of the longitudinal beam as the objective function and the boundary conditions, strength, stiffness and stability of the longitudinal beam as the constraints. In MATLAB, the radial basis function neural network algorithm is used to optimize the cross section of the frame longitudinal beam, and the optimal cross section size of the target longitudinal beam is obtained. The finite element models of the new frame 1 obtained from the optimization design and the new frame 2 obtained from the experience design are established respectively, and the working conditions of the two are compared and analyzed by using ANSYS. The experimental results show that frame 1 is 19.5% lighter than frame 2 on the premise of meeting the requirements of frame design and use.
Conclusion:
The lightweight optimization design idea is feasible.
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