摘要
为实现高空螺旋桨高效率和轻质量之间的权衡设计,提出一种考虑螺旋桨气动-结构性能的多学科多目标优化设计方法,理论上可得到约束条件下推力最大和质量最小的Pareto解集。但工程应用中,变量太多,可接受时间内仅能获得Pareto解集拟合趋势。为避免优化周期太长,提出以下阶段性优化方法。阶段1:根据上述Pareto解集拟合趋势和平台约束,确定最优桨径;阶段2:进行基于最优桨径的气动优化获得气动外形,结构优化获得结构方案。使用该方法对高空太阳能无人机螺旋桨优化,两个阶段耗时分别为96 h和4 h。对获得螺旋桨制造,仿真和试验,对比结果表明:推力最大误差为10.9%,质量误差为6.9%,刚度误差为15.2%,固有频率误差为15.4%,试验结果也表明该方法的合理有效性。
To accomplish the trade-off design of high-altitude propellers with high efficiency and light mass,a multi-disciplinary and multi-objective optimization design method was proposed by considering both aero-structure of the propeller.Theoretically,Pareto solution set with the objective of maximum thrust and minimum mass can be obtained.However,in practical engineering applications,due to large amount of optimization variables,only the fitting trend of the Pareto solution set was obtained in acceptable time.To avoid overlong optimization period,the staged optimization approach was proposed.Stage 1:the optimal propeller diameter was decided by the Pareto solution set fitting trend and constraints;Stage 2:the aerodynamic shape was obtained by aerodynamic optimization based on the optimal propeller diameter;the structural scheme was obtained through structural optimization.This approach was used to optimize the propeller for a solar-powered unmanned aerial vehicle,the two stages took 96 h and 4 h,respectively,the propeller was manufactured,simulated and tested.The comparison results showed that the maximum thrust error was 10.9%,the mass error was 6.9%,the stiffness error was 15.2%,and the natural frequency error was 15.4%;so the test results also demonstrated its rationality and validity.
作者
口启慧
王海峰
江泓鑫
聂波
KOU Qihui;WANG Haifeng;JIANG Hongxin;NIE Bo(School of Aeronautics,Northwestern Polytechnical University,Xi’an 710072,China)
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2024年第4期75-83,共9页
Journal of Aerospace Power
关键词
高空螺旋桨
多学科优化
PARETO解集
气动优化
结构优化
复合材料螺旋桨
试验验证
high-altitude propeller
multi-disciplinary optimization
Pareto solution set
aerodynamic optimization
structure optimization
composite propeller
test validation
