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

Xu Zhang; Yongzheng Jiang; Lian Tao; Yibing Zhang

doi:10.47297/taposatWSP2633-456926.20250602

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

Volume 6, Issue 2

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Optimization of the Aerodynamic Shape of UAVs Based on Multiple Regression-SLSQP Algorithm
Optimization of the Aerodynamic Shape of UAVs Based on Multiple Regression-SLSQP Algorithm
1.Hunan Provincial Key Laboratory of Mechanical Equipment Health Maintenance
2.Hunan University of Science and Technology, Hunan Xiangtan 411201
Vol. 6, Issue 2, Pages: 133-143(2025)
Published：25 February 2025
DOI：10.47297/taposatWSP2633-456926.20250602
Accepted：

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Zhang Xu,Jiang Yongzheng,Tao Lian,et al.Optimization of the Aerodynamic Shape of UAVs Based on Multiple Regression-SLSQP Algorithm[J].Theory and Practice of Science and Technology,2025,06(02):133-143.
DOI：

Zhang Xu,Jiang Yongzheng,Tao Lian,et al.Optimization of the Aerodynamic Shape of UAVs Based on Multiple Regression-SLSQP Algorithm[J].Theory and Practice of Science and Technology,2025,06(02):133-143. DOI： 10.47297/taposatWSP2633-456926.20250602.

摘要

Abstract

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.

关键词

Keywords

references

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