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Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm
International Journal of Aerospace Engineering ( IF 1.1 ) Pub Date : 2022-07-12 , DOI: 10.1155/2022/2828198
Tieying Jiang 1, 2 , Liang Jiang 1, 2
Affiliation  

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.

中文翻译:

基于改进粒子群优化算法的无人机翼型优化

翼型优化是无人机气动布局设计中的一项重要任务。基于翼型功率因数和不同攻角下的操纵稳定性构建目标优化函数。采用Hicks-Henne改进函数和CFD解样本构建了翼型参数化数学模型和翼型气动参数代理模型,重点解决了粒子群优化算法收敛速度慢、容易陷入局部最优解等问题,并在后期振荡;提出了一种基于改进粒子群优化的小型无人机低速翼型优化方法。与标准粒子群优化相比,选择性再生粒子群优化,和改进的粒子群优化,结果表明优化后翼型的最大厚度从19.77%降低到18.76%,迭代次数从112次降低到31次,改进粒子群优化的搜索速度显着提高;CFD 结果表明,优化后的后翼型表现出优异的空气动力学性能。平均而言,翼型的最大升阻比提高了11.9%,最大功率因数提高了12.5%,俯仰力矩降低了8.4%。在无人机的速度范围内,气动性能稳定。改进后的粒子群优化搜索速度显着提高;CFD 结果表明,优化后的后翼型表现出优异的空气动力学性能。平均而言,翼型的最大升阻比提高了11.9%,最大功率因数提高了12.5%,俯仰力矩降低了8.4%。在无人机的速度范围内,气动性能稳定。改进后的粒子群优化搜索速度显着提高;CFD 结果表明,优化后的后翼型表现出优异的空气动力学性能。平均而言,翼型的最大升阻比提高了11.9%,最大功率因数提高了12.5%,俯仰力矩降低了8.4%。在无人机的速度范围内,气动性能稳定。
更新日期:2022-07-12
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