Optimization of the Aerodynamic Shape of UAVs Based on Multiple Regression-SLSQP Algorithm

In view of the problem that for the aerodynamic shape layouts formed by the interactions of different aerodynamic components under different flight indicators, there is a lack of a universal aerodynamic optimization method, making it difficult to achieve the optimal aerodynamic shape layout of the combination of various aerodynamic components according to the design indicators, an optimization design method for the aerodynamic shape layout of unmanned aerial vehicles (UAVs) based on the multiple regression - SLSQP (Sequential Least Squares Programming) algorithm is proposed. Taking a certain long - endurance fixed - wing UAV as an example, its aerodynamic shape layout is optimized to improve its maximum flight range performance. A database of aerodynamic performance influencing factors is constructed through the layout of each aerodynamic shape component, and a multiple regression model is constructed based on this to obtain the corresponding relational expressions. Finally, the SLSQP algorithm is used to solve for the optimal aerodynamic shape under the constraint conditions. Verified by calculations using CFD software, the results show that this method has high accuracy, with a prediction error of less than 1%. The maximum range performance has been improved by nearly 4 percentage points, providing a valuable reference for the design optimization of the aerodynamic shape layout of fixed - wing UAVs.