Lightweight Design and Analysis of Four-Wing UAV Fuselage

Structure Based on Topology Optimization

Guo Xiang, Yan Zhu

, Xingqun Cheng and Chang Liu

Liaocheng University, Shandong, China

Keywords: Four-Wing UAV, Fuselage Structure, Lightweight Design, Topological Optimization, Finite Element Analysis.

Abstract: The lightweight fuselage construction of unmanned aerial vehicles (UAVs), which are often utilized in the

military, agricultural, and other sectors, is a crucial element in enhancing their durability. First, the fuselage

structure of a small four-wing UAV for aerial photography is designed. Then, using the SolidWorks

program to create the 3D model of the fuselage structure and the Inspire software to do the variable density

topology optimization, the optimized model's mass is reduced by 51.5%. In the end, the static and dynamic

properties of the model before and after optimization are compared after being static and dynamically

analyzed using the ANSYS finite element analysis software. The results demonstrate that the optimized

model's strength and stiffness are within the permissible stress range and that it does not exhibit resonance

phenomena in a limited operating condition, proving the viability of optimization.

INTRODUCTION

Because of its advantages of low development cost,

reusable, safe, and reliable, UAV has seen increased

application in recent years in the military, aerospace,

agricultural (Li Bo - Dong Xulei), and other areas. A

composite UAV wing structure was created by

Zhang Qingsong and colleagues employing the

continuous topology optimization design approach

under the SIMP method (Zhang Qingsong, 2023).

The optimum volume is reduced by 35% and the

fatigue life of the sensitive area is examined using

the wing volume ratio as the limitation condition.

The analysis's findings demonstrate that the

improved wing structure satisfies the design

specifications. By utilizing the variable density

topology optimization approach and the OptiStruct

structure optimization platform, Liu Wenbin et al.

created the topology optimization model for the

outer cylinder pillar of the UAV landing gear. The

model's static properties were compared before and

after optimization, and it was shown that the

optimized model could cut weight by 20% while still

maintaining design specifications for strength (Liu

Wenbin, 2014).

By utilizing topology optimization technology,

predecessors have made some advancements in the

field of UAV lightweight and have provided a

reference scheme for use in this field; however, the

majority of research focuses on the structure of

UAV landing gear and wings, and there are few

studies on the optimization of the fuselage structure.

This study optimizes the fuselage structure of a tiny

four-wing UAV using the variable density topology

optimization method, offering yet another reference

approach for the development of lightweight UAVs.

FUSELAGE STRUCTURE

DESIGN

2.1 Integrated Layout

The four-wing UAV's general fuselage structure is a

cross-type arrangement, which is further separated

into "ten" layout and "X" configuration (Imang Eko

Saputro, 2019), as shown in Figure 1. The cross-over

"X" layout method was chosen because it has been

demonstrated to offer higher overall performance, a

more robust structure, and greater flexibility (Zhong

Jianwei, 2018).

The four-wing UAV's minimum wheelbase is a

crucial factor in determining its total size. Following

selection of the layout strategy, the wheelbase may

be established in accordance with the UAV's

intended use. The schematic layout of the UAV's

wheelbase design is shown in Figure 2, where L is

the frame's wheelbase, r

max

is the rotor's maximum

110

Xiang, G., Zhu, Y., Cheng, X. and Liu, C.

Lightweight Design and Analysis of Four-Wing UAV Fuselage Structure Based on Topology Optimization.

DOI: 10.5220/0012275600003807

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Seminar on Artiﬁcial Intelligence, Networking and Information Technology (ANIT 2023), pages 110-116

ISBN: 978-989-758-677-4

radius when the wheelbase is fixed, and r

is the

rotor's operational range. The four-wing UAV's

design primarily focuses on achieving airborne

shooting tasks; as a result, the weight requirement is

low and a two-blade paddle rotor with a 200mm

operating range is used.

max

22Lr=×

(1)

max

1.05

rr≥

(2)

According to formula 1 and 2, the wheelbase is

finally determined to be 600mm.

Combined with the working requirements and

lightweight criteria of the four-wing UAV, ABS is

selected as the material, and its material parameters

are shown in Table 1.

Figure 1: Placement scheme.

Figure 2: Design philosophy.

Table 1: ABS Material parameter.

Modulus of

elasticity

Poisson

ratio

Density

Yield

strength

2000MPa 0.35 1060kg/m3 45MPa

According to the above parameters, the three-

dimensional model was finally established by using

SolidWorks 3D modeling software, as shown in

Figure 3.

Figure 3: Fuselage 3D model.

Lightweight Design and Analysis of Four-Wing UAV Fuselage Structure Based on Topology Optimization

111

Figure 4: Vertical motion force.

2.2 Status Analysis

Four-wing UAVs often fly in a condition that

involves vertical motion, pitch motion, roll motion,

and yaw motion (Song Siqin, 2021). The focus of

this research is vertical motion since it places the

UAV in the most force on the fuselage. One

diagonal rotor rotates clockwise and the second

diagonal rotor revolves counterclockwise as the

UAV flies upward. The UAV rises when the lift

force produced by the whole rotor is higher than the

weight of the aircraft. The UAV drops when the lift

force produced is less than the weight of the aircraft.

The drone hovers in the air when lift equals weight

of the aircraft. It is not difficult to draw the

conclusion that the spiral wing end perpendicular to

the boom and the force of the UAV's own load are

the principal forces acting on the fuselage of the

four-winged UAV. The drone weighs 1.4 kg by

itself and 2.5 kg when loaded. Figure 4 depicts the

force situation, where F is the lift force, G is its own

gravitational pull, and f is the load. Since 4F=G+f is

an obvious conclusion, it follows that M

=0.975kg is

the weight that must be supported by a single

cantilever. The load force that a single cantilever

must resist during the vertical movement of the

UAV is 2M

according to the principle of 2 times

thrust weight ratio, hence the traction force that the

propeller must generate F

=2M

g=19.11N

(gravitational acceleration g=9.8m/s).

The final three-dimensional model was created

using SolidWorks 3D modeling software in

accordance with the aforementioned criteria, as

shown in Figure 3. In the ANSYS Static Structural

Module, the constraint, load, and grid division are

applied to the imported 3D model. The static

characteristic cloud map is then produced. A vertical

lift force of 19.11N was applied to the location

where brushless motors were mounted throughout

the fuselage, as illustrated in Figure 3, using the

whole fuselage as the study object. In order to assure

the accuracy of the results, inertial release is

introduced to replace the boundary condition since

every UAV structure is in a free state when in flight.

By using the patch adaptation approach, the 23,592

mesh units and 41,766 mesh nodes of the tetrahedral

mesh were identified. After analyzing the static

properties, the maximum deformation and

equivalent stress nephogram was produced, as

shown in Figure 5.

The highest deformation of the fuselage structure

occurs around the rotors, as shown in Figure 5(a),

and the maximum displacement under difficult

operating circumstances is 0.390mm. The four-

winged UAV's flight and control are little impacted

by this distortion. As noted in Figure 5 (b), the

maximum equivalent stress of the fuselage structure

is also present around the rotors and is 2.838 MPa,

which still leaves a significant gap when compared

to the ABS material's 45 MPa yield strength. As a

result, there is still room for weight drop and the

fuselage structure won't look to be failing from

fatigue.

(a) Maximum deformation cloud image

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112

(b) Equivalent stress cloud image

Figure 5: Pre-optimization statics.

2.3 Fuselage Modal Analysis

Harmonious Response Analysis

During the actual flight, the four-wing UAV will

experience periodic vibration brought on by the

brushless motor of the power unit rotating (

Ren

Shuaiyang, 2021

), and this vibration has the most

influence on the four-wing UAV's flying process. In

order to minimize resonance between the excitation

source and the enhanced rotor folding mechanism,

which would result in the failure of the UAV

mechanical structure, the modal analysis of the

fuselage structure and the harmonious response

analysis may be used to understand its inherent

frequency characteristics. In this step, the dynamic

analysis of the fuselage model is performed using

ANSYS software to guarantee the logic and

dependability of the structural design.

The four-wing UAV's fuselage's chosen

brushless motor can run at a maximum speed of

5500 r/min, hence the highest frequency at which it

can operate without adversely impacting the

fuselage's condition is 92 Hz. Table 3 displays the

modal analysis of the UAV fuselage. The harmonic

response analysis of the fuselage is conducted to

produce the vertical motor direction displacement-

frequency curve at various frequencies, as shown in

Figure 6. This is predicated on the assumption that

the vibration of the fuselage caused by the brushless

motor changes in accordance with the simple

harmonic law. Combining the aforementioned study,

it is determined that the fuselage structure's first

order natural frequency is 200.09Hz, which is

significantly higher than the brushless motor's

working frequency and can successfully prevent the

development of resonance phenomena. Figure 6

shows that the four-wing UAV's displacement at its

maximum operating frequency is similarly

extremely modest, so it won't have an impact on the

UAV's flight.

Figure 6: Amplitude diagram.

Lightweight Design and Analysis of Four-Wing UAV Fuselage Structure Based on Topology Optimization

113

Figure 7: Topology optimization flow chart.

TOPOLOGY OPTIMIZATION

DESIGN BY VARIABLE

DENSITY METHOD

3.1 Topology Optimization Process

To increase the durability of four-wing UAVs,

topology optimization aims to provide a lighter

fuselage construction. Design engineers and

designers can use the Inspire program as an early

idea design tool (

Carlo Ferro, 2016

). The software

makes sure that technology supports the

development of designs that put a strong emphasis

on functionality and producibility. It makes it simple

and quick to develop and create conceptual product

prototypes that are architecturally flawless.

The program Inspire's Optistruct solver is

utilized in this work to optimize the fuselage model.

Figure 7 depicts the whole optimization procedure.

3.2 Optimized Result

The 3D model was imported into the Inspire

software with the four-wing UAV's fuselage

structure as the optimization object. A reasonable

optimization area was then designed in accordance

with the design requirements and experience,

removing as many redundant materials from the

model as possible to produce the desired effect. The

final optimized fuselage structural model is depicted

in Figure 8 with the objective of maximum rigidity.

Before optimization, the fuselage weighed

66.158 grams; after optimization, it weighed 34.08

grams. Topology optimization helped to lower the

weight by 51.5%, which increased the four-wing

UAV's endurance.

PERFORMANCE

VERIFICATION

4.1 Static Performance Comparison

The topologically optimized three-dimensional

model is imported into the ANSYS Static Structural

module for static analysis once again to see whether

the model's strength and stiffness criteria for the

four-wing UAV are met. Figure 9 displays the

deformation cloud picture and corresponding stress

cloud image.

Table 2 displays the static analysis outcomes for

the fuselage structure both before and after

optimization. The maximum deformation and stress

after optimization are 1.127mm and 11.793MPa,

respectively, and the rise is within the controlled

range, satisfying the design criteria of the four-wing

UAV statically.

Table 2: Comparison of results of static analysis.

Max

Deformation

Maximum

Stress

MPa

Quality/g

Primitive 0.390 2.838 66.158

Optimize 1.127 11.793 32.078

Figure 8 Optimized model.

4.2 Dynamic Performance Comparison

The dynamic properties of the optimized model can

be determined through modal analysis of the

optimized fuselage structure and harmonious

response analysis. The analysis can then be used to

determine whether the altered size and shape

following topology optimization has an effect on the

strength and stiffness of the UAV during normal

operation. The harmonic response curve of the

improved model is shown in Figure 10. The

optimized fuselage will exhibit reasonably

noticeable vibration at 165Hz and 285Hz, as can be

shown in the picture, however these two frequencies

are far higher than the maximum operating

frequency of 92Hz.

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(a) Maximum deformation cloud image

(b) Equivalent stress cloud image

Figure 9 Static analysis results of optimized fuselage mechanism.

The second frequency, which lowers by 45.86Hz

after optimization, has the largest change out of the

first six frequencies, as demonstrated in Table 3's

findings of the modal study performed before and

after the optimization of the fuselage structure. The

optimal frequency, which may successfully prevent

the occurrence of resonance phenomena, is

nevertheless much higher than the UAV's maximum

operating frequency of 92Hz. The study shown

above demonstrates that the UAV fuselage can also

Lightweight Design and Analysis of Four-Wing UAV Fuselage Structure Based on Topology Optimization

115

fully assure that the structural dynamic

characteristics after topology optimization fulfill the

design criteria, therefore this topology optimization

technique is applicable.

Table 3: Comparison of modal analysis results.

Frequency

Hz Primitive Optimize

firs

-stage 200.90 156.66

Second stage 202.59 156.73

Third stage 239.64 221.90

Fourth stage 489.72 469.32

Fifth stage 550.15 530.26

Sixth stage 646.43 630.73

Figure 10: Amplitude diagram.

CONCLUSION

1)Design and analysis are done on the fuselage of a

tiny, four-wing UAV that is primarily employed for

high-altitude shooting. The "X" layout concept is

used, and ABS is chosen as the material, taking into

account features like dependable construction, fluid

movement, and lightweight.

2)SolidWorks was used to model the fuselage

structure in three dimensions, and the Inspire

software's Optistruct structure optimization platform

was used to perform topological optimization on the

original fuselage mechanism. The weight of the

fuselage construction was ultimately decreased by

51.5% with the purpose of maximum rigidity, which

is significant for enhancing the UAV's endurance.

3)The static and dynamic properties of the

fuselage structure before and after topology

optimization were examined using ANSYS finite

element software. The static and dynamic properties

of the optimized model satisfied the design criteria

under the actual operating circumstances when the

static and dynamic parameters of the model were

compared between before and after optimization.

This optimization plan offers another theoretical

point of reference for structural lightweight design.

ACKNOWLEDGMENTS

This work was supported by the Natural Science

Foundation of Shandong Province (ZR2020ME113);

Innovation and Entrepreneurship Training Program

for College Students (CXCY2023122); Innovation

and Entrepreneurship Training Program for College

Students (CXCY2023155); Scientific Research Fund

of Liaocheng University (311102133311101910).

REFERENCES

Li Bo, Fang Kuncheng, Zhang Enyang, et al. Optimization

design and analysis of composite wing structure of a

certain electromagnetic-launch unmanned aerial

vehicle[J]. Composite Materials Science and

Engineering, 2015(12):5-11.

Xu Jingming, Shang Shuqi, Wang Dongwei, et al. Static

analysis and optimization design of heavy load

agricultural UAV[J]. Agricultural Mechanization

Research, 2023,45(10):16-23.

Dong Xulei, Zhu Ronggang, He Jianliang, et al. Military

application of UAV swarm based on blockchain[J].

Electronics Optics & Contral, 2023, 30(2):56-62+81.

Zhang Qingsong, Jia Shan, Chen Jin-bao, et al.

Configuration design and topology optimization of a

single wing for the hybrid unmanned aerial vehicle[J]. J

Tsinghua Univ (Sci & Technol), 2023,63(03):423-432.

Liu Wenbin, Zhang Ming, et al. Topology optimization of

an UAV landing gear structure[J]. Mechanical Science

and Technology for Aerospace Engineering, 2014,

33(11): 1753-1757.

Imang Eko Saputro, Alief Wikarta, Ali Muhtar. Topology

optimization on geometry of 3D printed “Impulse RC

Alien 4 Inch” racing quadcopter frame with polylactic

acid material. AIP Conference Proceedings 10

December 2019; 2187 (1): 050012. https://doi.org/

10.1063/1.5138342.

Zhong Jianwei, Zhong Xiaohua, Lu Minghui, et al.

Improved Design of Lightweight Structure of four-

rotor UAV [J]. China New Technology and New

Products, 2018(10):18-19.

Song Siqin, Wu Gang, Zhang Wenjing. Lightweight of

UAV based on the lattice structure characterized by

additive manufacturing[J]. Journal of Machine

Design, 2021,38 (06):25-29.

Ren Shuaiyang, Gao Aimin, Zhang Yong, et al. Finite

element analysis and topology optimization of folding

mechanism of six-rotor plant protection UAV[J].

Chinese Journal of Agricultural Mechanization,

2021,42 (09):53-58+194.

Carlo Ferro, Roberto Grassi, et al. Additive Manufacturing

Offers New Opportunities in UAV Research. Procedia

CIRP,2016,41:1004-1010. https://doi.org/10.1016/

j.procir.2015.12.104.

ANIT 2023 - The International Seminar on Artiﬁcial Intelligence, Networking and Information Technology

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