摘要
基于叶素动量理论及涡流理论的螺旋桨快速设计方法,由于设计采用的叶素气动力与真实情况存在差异,设计的螺旋桨存在拉力偏差,且不能保证较高的效率。为解决此问题,采用螺旋桨数值模拟的结果对设计进行修正。假设桨叶叶素最大升阻比对应的气动力沿径向相同,可通过数值模拟结果反解该气动力,再根据所得气动力进行螺旋桨的重新设计,建立耦合CFD修正的螺旋桨快速设计方法。结果表明,对于太阳能无人机小型螺旋桨的设计,本文设计方法一方面能够较好地满足拉力要求,另一方面相比于传统设计方法螺旋桨效率可提高2.75%。在采用代理优化的方法对螺旋桨翼型进行优化后,相比于传统设计方法螺旋桨效率进一步提高了3.95%。且该方法只需进行少量的CFD计算即可,相比于直接采用数值模拟优化螺旋桨的弦长及扭转角分布,设计周期更短。
The propeller design method based on the blade element momentum theory and the vortex theory has the problem of thrust deviation and cannot guarantee high efficiency due to the difference of the aerodynamic force of blade element between the design and the real situations.In order to solve this problem,the design is corrected by the numerical simulation of the propeller.Assuming that aerodynamic force of blade element along the radial direction is constant,the aerodynamic force can be inversely solved by numerical simulation results.Then the propeller is redesigned by the obtained aerodynamic force to establish a quick design method of propeller.The results show that the proposed design method can satisfy the design thrust in the small propeller design for solar energy UAV,and improve propeller efficiency by 2.75% compared with the traditional design method.And the efficiency of the propeller is further improved by 3.95% compared with the traditional design method after optimizing the airfoil of the propeller.Moreover,this method only needs to perform a small amount of CFD calculation,and the design cycle is shorter than directly using the numerical simulation to optimize the chord length and the twist angle distribution of the propeller.
作者
郭佳豪
周洲
范中允
GUO Jiahao;ZHOU Zhou;FAN Zhongyun(School of Aeronautics,Northwestern Polytechnical University,Xi’an 710072,China)
出处
《航空学报》
EI
CAS
CSCD
北大核心
2020年第2期67-76,共10页
Acta Aeronautica et Astronautica Sinica
基金
装备预研项目(41411020401)
陕西省重点研发项目(2018ZDCXL-GY-03-04)
民机专项(MJ-2015-F-009)
太仓创新引领专项计划(TC2018DYDS24)。
关键词
太阳能无人机
螺旋桨
叶素动量理论
多重参考系法
代理模型
优化设计
高效率
solar energy UAV
propeller
blade element momentum theory
multiple reference frames
surrogate model
optimization design
high efficiency
