Temperature Prediction Method of Electronic Equipment Cabin Based on Stochastic Configuration Network

During the flight of Unmanned Aerial Vehicle (UAV), some inadequate thermal control ways often lead to the failure of airborne electronic equipment, so it is very necessary to predict the thermal response of electronic equipment. The traditional temperature modeling method may be difficult to obtain accurate thermal response. However, the SCN model based on stochastic algorithm may be a good solution because it automatically determines the range of random parameters and doesn't consider the heat transfer mechanism in details. Therefore, a relative accurate thermal model can be obtained. In this paper, a flight thermal experiment of a UAV electronic equipment cabin was simulated in a Low-Pressure Environment (LPE) chamber. Based on the experimental data, the temperature prediction model for electronic equipment was built by using the SCN method. The results indicate that the presented model can predict the thermal response of UAV electronic equipment during the whole flight process with great accuracy.