Aiming at the problems of low accuracy and cumbersome calculation of automobile wind resistance based on neural network, an automobile wind resistance prediction model based on Sparrow Search Algorithm optimized Elman neural network is proposed. Firstly, a numerical simulation model of a certain automobile is constructed, and the wind resistance value is obtained through STAR-CCM+ simulation and the wind resistance prediction dataset of the whole vehicle is established. Then, the prediction effect of the model is verified by comparing with the real car test, and at the same time, it is compared and analyzed with the prediction results of Elman, SSA-Elman, and BP neural network models and the results of the real car data. The experimental results show that the SSA-Elman wind resistance prediction model has a high degree of agreement with the results of real-vehicle tests, and the model can effectively predict the wind resistance of the car.
Prediction of Automobile Aerodynamic Drag Coefficient for a MPV Car Based on Sparrow Search Algorithm
2024-03-29
1367020 byte
Conference paper
Electronic Resource
English
Convertible top improves aerodynamic drag coefficient
Automotive engineering | 1984
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