考虑动态滑翔性能的仿生机翼优化设计

张珅玮; 向涛; 张航

doi:10.7652/xjtuxb202601014

您当前的位置：

首页 >

文章列表页 >

考虑动态滑翔性能的仿生机翼优化设计

专题　“双碳”背景下的污染控制与资源化利用 | 更新时间：2026-01-15

- 考虑动态滑翔性能的仿生机翼优化设计
- Optimized Design of Bionic Wings Considering Dynamic Soaring Performance
- 西安交通大学学报 2026年60卷第1期页码：137-149
- 作者机构：
  
  长安大学工程机械学院，710064，西安
- 作者简介：
  
  作者简介：张珅玮（2000—），男，硕士生；
  张航（通信作者），男，讲师，硕士生导师。
- 基金信息：
  
  国家自然科学基金资助项目(52202435);中央高校基本科研业务费资助项目(300102254206);西安市科协青年人才托举计划资助项目。(959202313091)
- DOI：10.7652/xjtuxb202601014
  中图分类号： V221
- 收稿：2025-03-31，
  
  纸质出版：2026-01-10
- 稿件说明：
移动端阅览
张珅玮, 向涛, 张航. 考虑动态滑翔性能的仿生机翼优化设计[J]. 西安交通大学学报, 2026,60(1):137-149.

ZHANG Shenwei, XIANG Tao, ZHANG Hang. Optimized Design of Bionic Wings Considering Dynamic Soaring Performance[J]. Journal of Xi'an Jiaotong University, 2026, 60(1): 137-149.
张珅玮, 向涛, 张航. 考虑动态滑翔性能的仿生机翼优化设计[J]. 西安交通大学学报, 2026,60(1):137-149. DOI： 10.7652/xjtuxb202601014.

ZHANG Shenwei, XIANG Tao, ZHANG Hang. Optimized Design of Bionic Wings Considering Dynamic Soaring Performance[J]. Journal of Xi'an Jiaotong University, 2026, 60(1): 137-149. DOI： 10.7652/xjtuxb202601014.

摘要

为解决当前无人机续航能力有限的问题，基于信天翁的动态滑翔飞行机制，对考虑动态滑翔性能的仿生机翼进行优化设计，旨在提升无人机的动态滑翔性能与环境适应能力。根据信天翁的翅膀结构特点，建立了三段式仿生机翼的参数化模型，并选择展长、弦长、上反角和后掠角作为设计变量。基于已有研究成果，以最大升阻比为优化目标，结合动态滑翔的动力学模型构建了仿生机翼的优化模型。为了提高优化效率，利用神经网络拟合函数构建了仿生机翼的升力和阻力系数代理模型，并结合遗传算法对优化模型进行求解。仿真结果表明，优化后的机翼相较于基于图像测量的平直仿生机翼，在多个关键指标上实现显著提升：最大升阻比提高了13.73%，最小风梯度降低了16.23%，最大迎角增加了60%，最大升力系数增加了5.9%，最大总能量增加了33.61%。研究结果表明，优化后的仿生机翼具有更好的动态滑翔性能、更强的环境适应性及能量获取和利用能力。该研究为高动态滑翔能力的长续航仿生无人机的设计与优化提供了新的方法与思路。

Abstract

To address the limited endurance of current unmanned aerial vehicles (UAVs)，an optimized design of bionic wings considering dynamic soaring performance is proposed based on the dynamic soaring mechanism of albatrosses，aiming to enhance the dynamic soaring performance and environmental adaptability of UAVs.Based on the structural characteristics of albatross wings，a parametric model of a three-segment bionic wing is established，with wingspan，chord length，dihedral angle，and sweep angle selected as design variables.Building on existing research，an optimized model for bionic wings is constructed with the maximum liftto-drag ratio as the optimization objective，incorporating the dynamic model of dynamic soaring. To enhance optimization efficiency，a surrogate model for the lift and drag coefficients of the bionic wing is developed using neural network fitting functions，and the optimized model is solved using a genetic algorithm.Simulation results show that compared to a straight bionic wing based on image measurement，the optimized wing achieves significant improvements in multiple key performance indicators：the maximum lift-to-drag ratio increases by 13.73%，the minimum wind gradient decreases by 16.23%，the maximum angle of attack increases by 60%，the maximum lift coefficient increases by 5.9%，and the maximum total energy increases by 33.61%.The results demonstrate that the optimized bionic wing exhibits better dynamic soaring performance，stronger environmental adaptability，and enhanced energy acquisition and utilization capabilities.This study provides new methods and insights for the design and optimization of long-endurance bionic UAVs with high dynamic soaring capabilities.

关键词

Keywords

references

MANLEY W R.The soaring of birds[J].Nature, 1883,28(713):198-198.

JOUVENTIN P,WEIMERSKIRCH H.Satellite tracking of wandering albatrosses[J].Nature,1990,343(6260):746-748.

MIR I,EISA S A,MAQSOOD A.Review of dynamic soaring:technical aspects,nonlinear modeling perspectives and future directions[J].Nonlinear Dynamics,2018,94(4):3117-3144.

LAWRANCE N R J,SUKKARIEH S.A guidance and control strategy for dynamic soaring with a gliding UAV[C]//2009 IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA:IEEE,2009:3632-3637.

DEITTERT M,RICHARDS A,TOOMER C A,et al.Engineless unmanned aerial vehicle propulsion by dynamic soaring[J].Journal of Guidance,Control, and Dynamics,2009,32(5):1446-1457.

SACHS G,TRAUGOTT J,NESTEROVA A P,et al.Experimental verification of dynamic soaring in albatrosses[J].The Journal of Experimental Biology, 2013,216(22):4222-4232.

SACHS G,GRÜTER B,HONG Haichao.Performance enhancement by wing sweep for high-speed dynamic soaring[J].Aerospace,2021,8(8):229.

SACHS G.Kinetic energy in dynamic soaring:inertial speed and airspeed[J].Journal of Guidance,Control, and Dynamics,2019,42(8):1812-1821.

RICHARDSON P L.Upwind dynamic soaring of albatrosses and UAVs[J].Progress in Oceanography, 2015,130:146-156.

BONNIN V,BENARD E,MOSCHETTA J M,et al. Energy-harvesting mechanisms for UAV flight by dynamic soaring[J].International Journal of Micro Air Vehicles,2015,7(3):213-229.

LISSAMAN P.Wind energy extraction by birds and flight vehicles[J].Technical Soaring,2007 ,31 (2):52-60.

WANG Wei,AN Weigang,SONG Bifeng.Modeling and application of dynamic soaring by unmanned aerial vehicle[J].Applied Sciences,2022,12(11):5411.

BARNES J P.How flies the albatross:the flight mechanics of dynamic soaring[C]//World Aviation Congress & Exposition.Warrendale,PA,USA:SAE International,2004:2004-01-3088.

HONG Haichao,LIU Luoqin,HOLZAPFEL F,et al. Dynamic soaring under different atmospheric stability conditions[J].Journal of Guidance,Control, and Dynamics,2023,46(5):970-977.

PENHALLURICK J.The number of albatross (diomedeidae)species[J].The Open Ornithology Journal,2012, 5:32-41.

GOTO Y,WEIMERSKIRCH H,FUKAYA K,et al. Albatrosses employ orientation and routing strategies similar to yacht racers[J].Proceedings of the National Academy of Sciences of the United States of America, 2024,121(23):e2312851121.

SACHS G.In-flight measurement of upwind dynamic soaring in albatrosses[J].Progress in Oceanography, 2016,142:47-57.

STEMPECK A,HASSANALIAN M,ABDELKEFI A. Aerodynamic performance of albatross-inspired wing shape for marine unmanned air vehicles[C]//2018 Aviation Technology,Integration,and Operations Conference.Reston,VA,USA:AIAA,2018:AIAA 2018-3899.

GAO Siyang,ZHANG Bangcheng,SUN Jianwei.Research on the design method of a bionic suspension workpiece based on the wing structure of an albatross[J].Applied Bionics and Biomechanics,2019,2019:2539410.

CHANG E,CHIN D D,LENTINK D.Bird-inspired reflexive morphing enables rudderless flight[J].Science Robotics,2024,9(96):eado4535.

KULKARNI S,VASKAR R,MASANE A.Design and analysis of spanwise morphing wing to increase the overall efficiency of the aircraft[J].Journal of Emerging Technologies and Innovative Research,2019,6 (4):852-857.

MIR I,MAQSOOD A,AKHTAR S.Optimization of dynamic soaring maneuvers for a morphing capable UAV[C]//AIAA Information Systems-AIAA Infotech @ Aerospace.Reston,VA,USA:AIAA,2017:AIAA 2017-0678.

JEYAN D,MATH EW B C.Albatross and falcon inspired bionic UAV:an aerodynamic analysis[J].International Journal of Aviation Psychology,2021,8 (3):1-22 .

AN Weigang,SHI Fuzhen,HE Shibei,et al.Aerodynamic design and optimization of bionic wing based on wandering albatross[C]//Proceedings of the International Conference on Aerospace System Science and Engineering 2020.Berlin,Germany:Springer Nature, 2021:517-535.

ZHANG Hang,ZHANG Shenwei,XIANG Tao .Effects of bio-inspired wing dihedral variations on dynamic soaring performance of unmanned aerial vehicles[J].Drones, 2024,8(11):623.

GHAFARIASL P,MAHMOUDAN A,MOHAMMADI M,et al.Neural network-based surrogate modeling and optimization of a multigeneration system[J].Applied Energy,2024,364:123130.

STEMPECK A,HASSANALIAN M,ABDELKEFI A.Impacts of airfoil characteristics on the aerodynamic loads for albatross-inspired fixed wing drones[C]//2018 Applied Aerodynamics Conference. Reston, VA,USA:AIAA,2018:AIAA2018-3176.

NITHIYAPATHI C,SREELAKSHMY P S,SUMAN M.Aerodynamic characterization of an albatross wing for bio-inspired unmanned aerial vehicle[J]. Materials Today:Proceedings,2021 ,37(Part 2):1659-1664.

PELLERITO V,HASSANALIAN M,SEDAGHAT A,et al.Performance analysis of a bioinspired albatross airfoil with heated top wing surface:experimental study[C]//AIAA Propulsion and Energy 2019 Forum.Reston,VA,USA:AIAA,2019:AIAA 2019-4319.

刘丽娜,吴国新.Profili与Fluent环境下风力机翼型气动性模拟设计[J].北京信息科技大学学报(自然科学版),2014,29(1):68-70.

LIU Lina,WU Guoxin.Wind turbine airfoil aerodynamic simulation design based on Profili & Fluent[J]. Journal of Beijing Information Science & Technology University(Science and Technology Edition),2014,29 (1):68-70.

SHAFFER S A,WEIMERSKIRCH H,COSTA D P. Functional significance of sexual dimorphism in wandering albatrosses,Diomedea exulans[J].Functional Ecology,2001,15(2):203-210.

ZHAO Y J.Optimal patterns of glider dynamic soaring[J].Optimal Control Applications and Methods, 2004,25(2):67-89.

刘多能.固定翼无人机动态滑翔机理与航迹优化研究[D].长沙:国防科学技术大学,2016.

PATTERSON M A,RAO A V.A general-purpose MATLAB software for solving multiple-phase optimal control problems:version 2.3[EB/OL].(2016-12-12)[2025-02-14]. https://gpops2.com/resources/gpops2 UsersGuide.pdf.

王为,安伟刚,宋笔锋,等.仿信天翁变形翼动态滑翔获能特性[J].航空学报,2024,45(24):63-78.

WANG Wei,AN Weigang,SONG Bifeng,et al.Dynamic soaring performance of albatross-inspired morphing wing[J].Acta Aeronautica et Astronautica Sinica,2024,45(24):63-78.

刘思奇,白俊强.小型无人机总体参数对动态滑翔能力的影响[J].哈尔滨工程大学学报,2020,41 (6):817-823.

LIU Siqi,BAI Junqiang.Influence of small UAV parameters on dynamic soaring ability[J].Journal of Harbin Engineering University, 2020, 41 (6):817-823.

吕达,苏浩秦,李筠,等.变形仿生飞翼跨介质无人机外形设计与航行仿真[J].兵器装备工程学报, 2022,43(12):59-66.

LYU Da,SU Haoqin,LI Yun,et al.Configuration design and navigation simulation of deformable bionic flying-wing aerial-aquatic unmanned vehicles[J]. Journal of Ordnance Equipment Engineering,2022,43 (12):59-66.

郑鹏,刘健,宋维,等.拉丁超立方抽样评估方法改进研究[J].核电子学与探测技术,2017,37(7):734-738.

ZHENG Peng,LIU Jian,SONG Wei,et al.Preliminary study on improved Latin hypercube sampling[J]. Nuclear Electronics & Detection Technology,2017, 37(7):734-738.

宋磊,杨华,解静峰,等.基于改进涡格法的飞翼布局飞机稳定性导数计算[J].南京航空航天大学学报, 2014,46(3):457-462.

SONG Lei,YANG Hua,XIE Jingfeng,et al.Predicting stability derivatives of flying wing aircraft based on improved vortex lattice method[J].Journal of Nanjing University of Aeronautics & Astronautics, 2014,46(3):457-462.

MELIN T.Avortex lattice MATLAB implementation for linear aerodynamic wing applications[D].Stockholm:Royal Institute of Technology,2000.

TORRES G E,MUELLER T J.Low aspect ratio aerodynamics at low Reynolds numbers[J].AIAA Journal,2004,42(5):865-873.

OYELADE O N,EZUGWU A E,SAHA A K,et al. Deep learning at the service of meta heuristics for solving numerical optimization problems[J].Neural Computing and Applications,2025,37(27):22493-22528.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

离子液体改性燃料的电流体动力学效应研究

EBSILON软件在热电联产系统优化中的应用综述

语义区分和子图整合驱动的知识图谱表示学习方法

不同板叠材料热声热机能量转换过程数值模拟研究

冷库水平空气幕热湿阻隔性能数值模拟研究