摘要
针对分布式电推进(DEP)构型等具有多螺旋桨特征的飞行器,发展了通过优化螺旋桨滑流来达到提高机翼升阻比的方法。提出了一种可以获得目标诱导速度分布的螺旋桨设计方法,基于面元法发展了一套可以快速计算螺旋桨机翼干扰的气动程序Prop-wing,基于Kriging代理模型建立了一套高效的优化方法获得最优的螺旋桨诱导速度分布提高机翼升阻比。优化结果显示当拉力保持相同时,螺旋桨桨毂附近的轴向诱导速度越大,下游机翼的升阻比越大。在不对螺旋桨功率进行限制时,优化后的螺旋桨使得下游的翼段阻力相比较安装最小能量损失设计的螺旋桨的翼段减少了18.75%,而翼段升阻比提升达到了25.63%,当优化螺旋桨功率被限制后,翼段升阻比提升为9.62%。虽然升阻比的提升需要付出螺旋桨效率下降的代价,但是研究还是给分布式动力滑流的利用提供了一种思路。
For the multi-propeller aircraft with distributed electric propulsion(DEP) configuration, a method to improve the lift-to-drag ratio of the wing was developed by optimizing the propeller slipstream. A propeller design method which can obtain the target induced velocity distribution was proposed. Based on the panel method, an aerodynamic program Prop-wing that can quickly calculate the propeller-wing interference was developed. An efficient optimization method based on Kriging surrogate model was established to obtain the optimal induced velocity distribution and raise the lift-to-drag ratio of the wing. The optimization results showed that the larger axial induced velocity near the propeller hub meant the larger lift drag ratio of the downstream wing. When the power of the propeller was not limited, the optimized propeller can reduce the drag of the downstream wing-segment by 18.75% and increase the lift-to-drag ratio of wing-segment by 25.63% compared with the propeller with the minimum energy loss;when the power of the optimized propeller was limited, the lift-to-drag ratio of the wing-segment increased to 9.62%. Although the lift-to-drag ratio is raised at the cost of propeller efficiency reduction, the research still provides an idea for the use of distributed propeller slipstream.
作者
薛臣
周洲
范中允
李旭
XUE Chen;ZHOU Zhou;FAN Zhongyun;LI Xu(School of Aeronautics,Northwestern Polytechnical University,Xi'an 710072,China;Science and Technology on Unmanned Aerial Vehicle La boratory,Northwestern Polytechnical University,Xi'an 710065,China)
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2021年第1期104-118,共15页
Journal of Aerospace Power
基金
装备预研项目(41411020401,41411010403)
大院大所创新计划(TC2018DYDS24)。