Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm
Airfoil optimization is an essential task in the aerodynamic layout design of the unmanned aerial vehicle (UAV). An objective optimization function was constructed based on the airfoil power factor and handling stability at various attack angles. The parametric mathematical model of the airfoil and...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/2828198 |
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| _version_ | 1850157259488755712 |
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| author | Tieying Jiang Liang Jiang |
| author_facet | Tieying Jiang Liang Jiang |
| author_sort | Tieying Jiang |
| collection | DOAJ |
| description | Airfoil optimization is an essential task in the aerodynamic layout design of the unmanned aerial vehicle (UAV). An objective optimization function was constructed based on the airfoil power factor and handling stability at various attack angles. The parametric mathematical model of the airfoil and aerodynamic parameter proxy model of airfoil were constructed using the Hicks-Henne improved function and CFD solution sample, focusing on the issues with particle swarm optimization algorithms such as slow convergence, a tendency to fall into local optimal solutions, and oscillation at a late stage; an optimization method for the low-speed airfoil of a small UAV based on improved particle swarm optimization was developed. When compared to standard particle swarm optimization, selective regenerative particle swarm optimization, and improved particle swarm optimization, the results indicate that the maximum thickness of the optimized rear airfoil decreases from 19.77% to 18.76%, the number of iterations decreases from 112 to 31, and the search speed of the improved particle swarm optimization significantly improves; the CFD results indicate that the optimized rear airfoil exhibits superior aerodynamic performance. On average, the airfoil’s maximum lift-to-drag ratio is increased by 11.9%, its maximum power factor is increased by 12.5%, and its pitching moment is reduced by 8.4%. Within the UAV’s speed range, the aerodynamic performance is stable. |
| format | Article |
| id | doaj-art-2d2bbdc2d7364d63a27dc9f3b7dce6a4 |
| institution | OA Journals |
| issn | 1687-5974 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-2d2bbdc2d7364d63a27dc9f3b7dce6a42025-08-20T02:24:14ZengWileyInternational Journal of Aerospace Engineering1687-59742022-01-01202210.1155/2022/2828198Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization AlgorithmTieying Jiang0Liang Jiang1Aerospace Times FeiHong Technology Company LimitedAerospace Times FeiHong Technology Company LimitedAirfoil optimization is an essential task in the aerodynamic layout design of the unmanned aerial vehicle (UAV). An objective optimization function was constructed based on the airfoil power factor and handling stability at various attack angles. The parametric mathematical model of the airfoil and aerodynamic parameter proxy model of airfoil were constructed using the Hicks-Henne improved function and CFD solution sample, focusing on the issues with particle swarm optimization algorithms such as slow convergence, a tendency to fall into local optimal solutions, and oscillation at a late stage; an optimization method for the low-speed airfoil of a small UAV based on improved particle swarm optimization was developed. When compared to standard particle swarm optimization, selective regenerative particle swarm optimization, and improved particle swarm optimization, the results indicate that the maximum thickness of the optimized rear airfoil decreases from 19.77% to 18.76%, the number of iterations decreases from 112 to 31, and the search speed of the improved particle swarm optimization significantly improves; the CFD results indicate that the optimized rear airfoil exhibits superior aerodynamic performance. On average, the airfoil’s maximum lift-to-drag ratio is increased by 11.9%, its maximum power factor is increased by 12.5%, and its pitching moment is reduced by 8.4%. Within the UAV’s speed range, the aerodynamic performance is stable.http://dx.doi.org/10.1155/2022/2828198 |
| spellingShingle | Tieying Jiang Liang Jiang Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm International Journal of Aerospace Engineering |
| title | Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm |
| title_full | Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm |
| title_fullStr | Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm |
| title_full_unstemmed | Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm |
| title_short | Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm |
| title_sort | optimization of uav airfoil based on improved particle swarm optimization algorithm |
| url | http://dx.doi.org/10.1155/2022/2828198 |
| work_keys_str_mv | AT tieyingjiang optimizationofuavairfoilbasedonimprovedparticleswarmoptimizationalgorithm AT liangjiang optimizationofuavairfoilbasedonimprovedparticleswarmoptimizationalgorithm |