复合式无人机机翼设计及其自适应优化

张威; 谭蒙; 刘亚枫; 聂永斌; 栾悦

doi:10.19527/j.cnki.2096-1642.1091

复合式无人机机翼设计及其自适应优化

doi: 10.19527/j.cnki.2096-1642.1091

航天时代飞鹏有限公司, 江苏昆山 215332

详细信息

作者简介:
张威(1994—)男, 博士, 主要研究方向为气动设计、气动优化等。E-mail: optz2023@163.com

通讯作者:
栾悦(1994-)女, 工程师, 主要研究方向为数据分析、统计分析等。E-mail: optl2022@163.com

中图分类号: V211.3
计量
- 文章访问数: 56
- HTML全文浏览量: 11
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2023-10-22
- 修回日期: 2023-12-26

Wing Design and Adaptive Optimization of a Compound Drone

Aerospace Times Feipeng Co., Kunshan 215332, China

摘要

摘要: 随着人类社会的进步和城市物流的兴起, 以复合式无人机为代表的无人机技术进入了快速发展阶段。在复合式无人机的研制周期中, 气动优化设计选型扮演着非常重要的角色。针对基于代理模型的气动优化技术, 对其关键参数自适应筛选和设计空间自适应更新进行了研究, 形成了参数/空间自适应气动寻优平台, 有效提高了气动优化过程中的寻优效率和搜索能力。针对一款复合式无人机提出机翼初步设计方案, 并对其进行自适应气动寻优。优化翼根、翼梢翼型及由此生成的优化三维机翼在设计升力系数为1.0时的升阻比均提高5%以上, 且对应迎角均减小2°以上。无人机机翼失速特性及滚转操控能力均得到有效提升。
- 复合式无人机 /
- 机翼设计 /
- 自适应优化 /
- 参数筛选 /
- 空间更新
Abstract: With the growing demand for unmanned transportation, the rise of compound drones is imperative. Aerodynamic optimization design plays a significant role in the development cycle of compound drones. Researches were performed on key parameter adaptive screening and design space adaptive updating of surrogate-based aerodynamic optimization techniques. A parametric/spatial adaptive aerodynamic optimization platform was established, which can improve the optimization efficiency and search capability effectively in the process of aerodynamic optimization. A preliminary design scheme of wing for a compound drone was presented, and adaptive aerodynamic optimization was carried out. The lift-to-drag ratios of the optimized wing root and tip airfoils and the resulting optimized wing were all increased by over 5%, with design lift coefficients equaling to 1.0, and the corresponding angles of attack were also reduced by more than 2°. The stall characteristics and the roll control ability of the wing were improved simultaneously.
- compound drones /
- wing design /
- adaptive optimization /
- parameter screening /
- space updating

HTML全文

图 1 一款复合式无人机概念外形

Figure 1. Conceptual shape of a compound drone

下载: 全尺寸图片幻灯片

图 2 自适应气动寻优算法流程图

Figure 2. Flow chart of parametric/spatial adaptive aerodynamic optimization algorithm

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图 3 NACA4412翼型计算网格示意图

Figure 3. Computational mesh diagram of NACA4412 airfoil

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图 4 网格无关性验证结果

Figure 4. Verification result of mesh independence

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图 5 翼根翼型优化迭代历程

Figure 5. Iteration of wing root airfoil optimization

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图 6 优化前后翼型形状及压力系数分布对比

Figure 6. Comparisons of shape and surface pressure coefficient between airfoils before and after optimization

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图 7 优化前后翼型性能对比

Figure 7. Performance comparison between airfoils before and after optimization

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图 8 优化前后机翼性能对比

Figure 8. Performance comparison between wings before and after optimization

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图 9 优化前后机翼上翼面极限流线分布(上：初始机翼；下：优化机翼)

Figure 9. Limiting streamline distribution on upper surface of wings before and after optimization (upper: original wing; lower: optimized wing)

下载: 全尺寸图片幻灯片

表 1 无人机设计参数

Table 1. Conceptual design parameters of a drone

design parameter	value
maximum take-off weight/kg	500
wing area/m²	7.5
cruising altitude/m	1 000
cruising speed/(km/h)	130

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表 2 无人机机翼设计参数

Table 2. Wing geometry design parameters of a drone

design parameter	value
wing area/m²	7.5
wing span/m	10
aspect ratio	13.33
taper ratio	0.5
mean aerodynamic chord/m	0.777
angle of sweepback at trailing edge/(°)	0
dihedral angle/(°)	0

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表 3 方差分析表

Table 3. Variance analysis

source	S	df	MS	F value	P value
A	S_A	df_A	MS_A	F_A	P_A
B	S_B	df_B	MS_B	F_B	P_B
…	…	…	…	…	…
error	S_E	df_E	MS_E
total	S_T	df_T

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表 4 参数空间更新伪代码

Table 4. Pseudo-code of parameter space updating

Input： original parameter space[x_{il, old}, x_{iu, old}]^k，temporary optimal points(x_{1, opt}, x_{2, opt}, …, x_{k, opt})
Process:
1. For i=1, 2, …, k Do:
2. If x_{i, opt} -x_{il, old} ≤ 0.1\|x_{iu, old}-x_{il, old} \| Then
3. x_{il, new}=(3x_{il, old}－x_{iu, old})/2, x_{iu, new}=(x_{il, old}+ x_{iu, old})/2;
4. Else if x_{iu, old}-x_{i, opt}≤ 0.1\|x_{iu, old}-x_{il, old} \| Then
5. x_{il, new}=(x_{il, old}+ x_{iu, old})/2, x_{iu, new}=(－x_{il, old}+3x_{iu, old})/2;
6. Else
7. x_{il, new}=x_{il, old}, x_{iu, new}=x_{iu, old};
8. End if
9. End for
Output： new parameter space[x_{il, new}-x_{iu, new}]^k

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表 5 网格无关性验证参数

Table 5. Parameters of mesh independence verification

mesh parameter	coarse mesh	middle mesh	dense mesh
chord point number	81	121	161
y⁺	5.0	1.0	0.5
total mesh number	24 764	36 844	48 924

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表 6 计算工况

Table 6. Calculation conditions

H/m	V/(km/h)
1 000	130

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表 7 翼根翼型设计升阻比的方差分析表

Table 7. Variance analysis of design lift-to-drag ratio of root airfoil

source	S	df	MS	F value	P value
U_{1, root}	14.19	1	14.19	152.00	25.77
U_{2, root}	17.88	1	17.88	191.56	32.47
U_{3, root}	0.95	1	0.95	10.20	1.73
U_{4, root}	0.06	1	0.06	0.62	0.11
U_{5, root}	0.00	1	0.00	0.01	0.00
U_{6, root}	1.03	1	1.03	11.02	1.87
U_{7, root}	1.01	1	1.01	10.81	1.83
L_{1, root}	2.22	1	2.22	23.80	4.03
L_{2, root}	0.73	1	0.73	7.82	1.33
L_{3, root}	6.95	1	6.95	74.49	12.62
L_{4, root}	0.16	1	0.16	1.74	0.29
L_{5, root}	5.86	1	5.86	62.74	10.64
L_{6, root}	0.48	1	0.48	5.13	0.87
L_{7, root}	1.96	1	1.96	21.03	3.56
error	1.59	17	0.09		2.89
total	55.07	31			100.00

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表 8 关键参数筛选结果

Table 8. Screening results of key parameters

root design parameters				tip design parameters
U_{1, root}	U_{2, root}	U_{3, root}	U_{4, root}	U_{1, tip}	U_{2, tip}	U_{3, tip}	U_{4, tip}
U_{5, root}	U_{6, root}	U_{7, root}		U_{5, tip}	U_{6, tip}	U_{7, tip}
L_{1, root}	L_{2, root}	L_{3, root}	L_{4, root}	L_{1, tip}	L_{2, tip}	L_{3, tip}	L_{4, tip}
L_{5, root}	L_{6, root}	L_{7, root}		L_{5, tip}	L_{6, tip}	L_{7, tip}

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表 9 翼根翼型参数空间变化情况

Table 9. Parameter space variation of wing root airfoil

parameter	original space		latest space		optimal
parameter	lower	upper	lower	upper	optimal
L_{1, root}	-0.26	-0.2	-0.14	-0.08	-0.091
L_{3, root}	-3.9	-2.9	-1.9	-0.9	-1.404 4
L_{5, root}	-3.9	-2.9	-0.9	0.1	-0.001 2
L_{7, root}	0.1	0.13	0.16	0.19	0.184
U_{1, root}	0.23	0.31	0.19	0.27	0.193 6
U_{2, root}	1.8	2.4	1.8	2.4	2.17
U_{3, root}	2.3	3.1	3.5	4.3	4.27
U_{4, root}	5.9	7.9	5.9	7.9	6.03
U_{6, root}	1.4	1.8	3.0	3.4	3.13

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表 10 优化翼型气动性能变化情况

Table 10. Aerodynamic performance variation of optimal airfoils

aerodynamic performance		original	optimal	variation
root airfoils	K_{C_L=1, root}	64.83	70.11	+8.14%
	α_{C_L=1, root}	5.38°	3.12°	-2.26°
	α_{stall, root}	14.5°	14.5°	+0.0°
	θ_stall	0.159 8	0.140 4	-0.019 4
tip airfoils	K_{C_L=1, tip}	62.61	67.17	+7.28%
	α_{C_L=1, tip}	4.83°	1.93°	-2.90°
	α_{stall, tip}	14.5°	13.0°	-1.5°
	θ_tip	0.122 0	0.109 9	-0.012 1

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复合式无人机机翼设计及其自适应优化

doi: 10.19527/j.cnki.2096-1642.1091

作者简介:
张威(1994—)男, 博士, 主要研究方向为气动设计、气动优化等。E-mail: optz2023@163.com

通讯作者:
栾悦(1994-)女, 工程师, 主要研究方向为数据分析、统计分析等。E-mail: optl2022@163.com

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Wing Design and Adaptive Optimization of a Compound Drone

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复合式无人机机翼设计及其自适应优化

doi: 10.19527/j.cnki.2096-1642.1091

作者简介: 张威(1994—)男, 博士, 主要研究方向为气动设计、气动优化等。E-mail: optz2023@163.com

通讯作者: 栾悦(1994-)女, 工程师, 主要研究方向为数据分析、统计分析等。E-mail: optl2022@163.com

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出版历程

Wing Design and Adaptive Optimization of a Compound Drone

计量

出版历程

目录

联系我们

友情链接

作者简介:
张威(1994—)男, 博士, 主要研究方向为气动设计、气动优化等。E-mail: optz2023@163.com

通讯作者:
栾悦(1994-)女, 工程师, 主要研究方向为数据分析、统计分析等。E-mail: optl2022@163.com