Multidisciplinary Design Optimization for an Electric Quadrotor Fixed-Wing Hybrid Unmanned Air Vehicle

ZHANG Hang; HUANG Yingzhuo

doi:10.7652/xjtuxb202308015

您当前的位置：

首页 >

文章列表页 >

Multidisciplinary Design Optimization for an Electric Quadrotor Fixed-Wing Hybrid Unmanned Air Vehicle

更新时间：2025-05-08

- Multidisciplinary Design Optimization for an Electric Quadrotor Fixed-Wing Hybrid Unmanned Air Vehicle
- Vol. 57, Issue 8, Pages: 148-160(2023)
- 作者机构：
  
  1. 长安大学工程机械学院,西安,710064
  2. 重庆凯瑞机器人技术有限公司,重庆,400799
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202308015
  CLC： TP221
- Online First：10 August 2023，
  
  Published：2023
- 稿件说明：
移动端阅览
ZHANG Hang, HUANG Yingzhuo. Multidisciplinary Design Optimization for an Electric Quadrotor Fixed-Wing Hybrid Unmanned Air Vehicle[J]. 2023, 57(8): 148-160.
DOI：

ZHANG Hang, HUANG Yingzhuo. Multidisciplinary Design Optimization for an Electric Quadrotor Fixed-Wing Hybrid Unmanned Air Vehicle[J]. 2023, 57(8): 148-160. DOI： 10.7652/xjtuxb202308015.

摘要

为解决当前电动复合四旋翼无人机设计中存在的布局选择缺乏理论依据、缺少旋翼模式下的抗风性能的分析和评估方法、两套动力系统独立进行设计和总体设计过程多数采用传统序列设计方法而未充分考虑几何外形、气动、配平和稳定性、动力系统、质量、旋翼模式下的抗风性能和续航性能等学科之间参数相互传递带来的复杂耦合关系等问题

根据所提基于代理模型的改进并行子空间优化算法

通过建立几何外形参数化模型和气动网格划分模型、各个飞行模式下的气动性能和飞行性能分析模型、旋翼模式下抗风性能的评估和分析模型以及已经提出的电动力系统模型

形成了电动复合四旋翼无人机的多学科优化设计(MDO)方法

并将该方法应用于一架小型电动复合四旋翼无人机的总体设计当中

基于优化设计结果制作了原理样机。原理样机的飞行实验结果显示飞行性能均满足设计要求

并且在起飞总质量降低约为2.8%的情况下

航时提升了约14.1%

最大可抗风速提升了约3.5%

表明了所提MDO方法的可行性和正确性

可为电动复合四旋翼无人机产品的研发和应用提供一定的理论指导。

Abstract

This paper addresses issues in the current design of electric quadrotor fixed-wing hybrid unmanned air vehicles(EH-UAVs)

including a lack of theoretical basis for the layout configuration selection

a lack of analysis and evaluation methods for the wind disturbance rejection capability in the quadrotor mode

the issue that design methods for the electric propulsion systems of most EH-UAVs are to design the quadrotor system and fixed-wing system independently

and the issue that design methods for the conceptual design are mainly the traditional sequence design methods without fully considering the complex coupling relationships caused by the mutual transfer of parameters between various disciplines such as geometric shape

aerodynamics

trimming and stability

propulsion system

weight

wind disturbance rejection capability in the quadrotor mode

and endurance performance. Based on the proposed improved surrogate model based concurrent subspace optimization(CSSO)architecture

this paper establishes a multidisciplinary optimization(MDO)method for the conceptual design of EH-UAVs. This is accomplished by building geometric shape parameterization models and aerodynamic grid division models

aerodynamic and flight performance analysis models for different flight modes

evaluation and analysis models for wind disturbance rejection capability in the quadrotor mode

and the proposed electric propulsion system models. The proposed MDO method and the discipline analysis models are applied to the conceptual design process of a small EH-UAV. A prototype of the EH-UAV is fabricated based on the MDO results. The flight test results of the prototype show that the flight performance meets the design requirements

and with a 2.8% reduction in takeoff weight

the endurance time is improved by approximately 14.1%

and the maximum wind speed that the EH-UAV can resist is increased by approximately 3.5%. This verifies the feasibility and correctness of the MDO method proposed in this article

which can provide guidance for the research and application of EH-UAVs.

关键词

Keywords

references

GÜÇLÜ A, ARIKAN K B, KURTULUS D F. Attitude and altitude stabilization of fixed wing VTOL unmanned air vehicle [C]//AIAA Modeling and Simulation Technologies Conference. Reston, VA, USA: AIAA, 2016: 2016-3378.

ÇAKICI F, LEBLEBICIO A, LU M K. Design and analysis of a mode-switching micro unmanned aerial vehicle [J]. International Journal of Micro Air Vehicles, 2016, 8(4): 221-229.

DEWI P T, HADI G S, RAMADHAN KUSNAEDI M, et al. Design of separate lift and thrust hybrid unmanned aerial vehicle [J]. The Journal of Instrumentation, Automation and Systems, 2015, 2(2): 45-51.

TYAN M, NGUYEN N V, KIM S, et al. Comprehensive preliminary sizing/resizing method for a fixed wing-VTOL electric UAV [J]. Aerospace Science and Technology, 2017, 71: 30-41.

FINGER D F, BRAUN C, BIL C. The impact of electric propulsion on the performance of VTOL UAVs [C]//Deutscher Luft-und Raumfahrtkongress(DGLR). Munich, Germany: [s.n.], 2017: 1-18.

赵长辉, 杨五兵, 李波, 等. 固定翼四旋翼复合飞行器 [C]//2014(第五届)中国无人机大会论文集.北京: 航空工业出版社, 2014: 50-55.

张飞. 垂直起降固定翼无人机研究 [D]. 南昌: 南昌航空大学, 2019.

RAYMER D P. Enhancing aircraft conceptual design using multidisciplinary optimization [D]. Stockholm, Sweden: Royal Institute of Technology, 2002: 1-4.

PAPAGEORGIOU A, ÖLVANDER J. The role of multidisciplinary design optimization(MDO)in the development process of complex engineering products [C]//21st International Conference on Engineering Design(ICED 17). [S.l.]: [s.n.], 2017: 109-118.

余雄庆. 飞机总体多学科设计优化的现状与发展方向 [J]. 南京航空航天大学学报, 2008, 40(4): 417-426.

YU Xiongqing. Multidisciplinary design optimization for aircraft conceptual and preliminary design: status and directions [J]. Journal of Nanjing University of Aeronautics Astronautics, 2008, 40(4): 417-426.

SIMPSON T W, BOOKER A J, GHOSH D, et al. Approximation methods in multidisciplinary analysis and optimization: a panel discussion [J]. Structural and Multidisciplinary Optimization, 2004, 27(5): 302-313.

韩忠华. Kriging模型及代理优化算法研究进展 [J]. 航空学报, 2016, 37(11): 3197-3225.

HAN Zhonghua. Kriging surrogate model and its application to design optimization: a review of recent progress [J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(11): 3197-3225.

韩忠华, 许晨舟, 乔建领, 等. 基于代理模型的高效全局气动优化设计方法研究进展 [J]. 航空学报, 2020, 41(5): 25-65.

HAN Zhonghua, XU Chenzhou, QIAO Jianling, et al. Recent progress of efficient global aerodynamic shape optimization using surrogate-based approach [J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(5): 25-65.

MARTINS J R R A, LAMBE A B. Multidisciplinary design optimization: a survey of architectures [J]. AIAA Journal, 2013, 51(9): 2049-2075.

张科施. 飞机设计的多学科优化方法研究 [D]. 西安: 西北工业大学, 2006.

李响. 多学科设计优化方法及其在飞行器设计中的应用 [D]. 西安: 西北工业大学, 2004.

胡添元. 飞翼布局飞机总体多学科设计优化研究 [D]. 南京: 南京航空航天大学, 2010.

唐伟. X翼尾坐式小型飞行器关键设计问题研究 [D]. 西安: 西北工业大学, 2019.

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

RAYMER D P. Aircraft design: a conceptual approach [M].6th ed. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018.

ZHANG Hang, SONG Bifeng, LI Fan, et al. Multidisciplinary design optimization of an electric propulsion system of a hybrid UAV considering wind disturbance rejection capability in the quadrotor mode [J]. Aerospace Science and Technology, 2021, 110: 106372.[22] ZHANG Hang, SONG Bifeng, WANG Haifeng, et al. A method for evaluating the wind disturbance rejection capability of a hybrid UAV in the quadrotor mode [J]. International Journal of Micro Air Vehicles, 2019, 11: 1756829319869647.

张航, 宋笔锋, 王海峰, 等. 固旋翼无人机垂直起降阶段抗风特性及其影响因素 [J]. 系统工程与电子技术, 2019, 41(7): 1525-1535.

ZHANG Hang, SONG Bifeng, WANG Haifeng, et al. Wind resistance and influencing factors of quadrotor fixed-wing vertical take-off and landing hybrid unmanned aerial vehicle [J]. Systems Engineering and Electronics, 2019, 41(7): 1525-1535.

QUAN Quan. Introduction to multicopter design and control [M]. Singapore: Springer Singapore, 2017.

DAI Xunhua, QUAN Quan, REN Jinrui, et al. An analytical design-optimization method for electric propulsion systems of multicopter UAVs with desired hovering endurance [J]. IEEE/ASME Transactions on Mechatronics, 2019, 24(1): 228-239.

VIANA F A C, VENTER G, BALABANOV V. An algorithm for fast optimal Latin hypercube design of experiments [J]. International Journal for Numerical Methods in Engineering, 2010, 82(2): 135-156.

MathWorks. Neural net fitting [EB/OL]. [2022-10-10]. https://www.mathworks.com/help/deeplearning/ref/neuralnetfitting-app. html.

赖宇阳, 姜欣, 方立桥, 等. Isight参数优化理论与实例详解 [M]. 北京: 北京航空航天大学出版社, 2012.

YUSOFF Y, NGADIMAN M S, ZAIN A M. Overview of NSGA-II for optimizing machining process parameters [J]. Procedia Engineering, 2011, 15: 3978-3983.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A Fast Calculation Method for Thermal Flow Fields in Transformer Windings Based on PI-DeepONet

Windage Loss and Flow Characteristics in Impeller Back Gaps of sCO2 Radial Inflow Turbines

Bi-Level Multi-Obj ective Optimization of a Wind-Solar Coupled Hydrogen Production System Based on the Synergy of Hybrid Electrolyzer Arrays

Diffusion Characteristics and Influencing Factors in Case of Hydrogen Leakage from Fuel Cell Vehicles Running in Tunnels

Turbulent Kinetic Energy Dissipation Mechanism of Supercritical Carbon Dioxide Leakage Flow in a Scallop Bionic Seal Cavity

Related Author

No data

Related Institution

No data

⁰