基于粒子群的小型无人机低过载压缩空气发射参数选择和优化算法

doi:10.12382/bgxb.2024.0014

摘要/Abstract

摘要：

为进一步完善无人机压缩空气发射过程中的内弹道特性研究,基于压缩空气发射系统的结构和工作机理,利用热力学、气体动力学理论建立发射过程内弹道模型,通过仿真计算和发射试验验证模型的有效性。探究脉冲阀面积、脉冲阀全开启时间、高/低压室初始容积对发射过程内弹道性能参量的变化规律,运用基于子母弹原理的改进粒子群优化算法对发射参数进行优化设计,分析并验证优化结果的有效性。研究结果表明:脉冲阀面积对无人机峰值过载呈正相关影响,并对气体的质量流量影响显著;增大脉冲阀全开启时间可以有效降低无人机的峰值过载;高压室容积主要通过改变气体质量流量从而对内弹道性能进行影响,并且高压室容积越大对高/低压室的压差变化越明显;合理增大低压室容积可以有效降低峰值加速度的大小,并对无人机出筒速度影响较弱,有利于提高无人机在发射过程中的稳定性;改进粒子群优化算法可以有效优化小型无人机低过载压缩空气发射参数选择。所得研究结果对无人机压缩空气发射参数选择、设计试验和工程化应用具有一定的理论指导意义。

关键词: 无人机, 压缩空气发射系统, 内弹道特性, 粒子群优化算法

Abstract:

To further improve the internal ballistic characteristics during the compressed air launch process of unmanned aerial vehicles (UAVs),an internal ballistic model of the launch process is established by utilizing the thermodynamics and gas dynamics theories based on the structure and working mechanism of the compressed air launch system.The validity of the model is verified through simulation calculations and launch tests.The variation patterns of internal ballistic performance parameters with respect to the area and full-open time of pulse valve and the initial volumes of high- and low-pressure chambers are studied.An improved particle swarm optimization (PSO) algorithm based on the submunition principle is used to optimize the launch parameters,and the effectiveness of the optimized results is analyzed and verified.The results show that the pulse valve area has a positive correlation with the peak overload of UAV and significantly affects the mass flow rate of gas.The peak overload of UAV can be effectively reduced by increasing the full-open time of pulse valve.The volume of high-pressure chamber mainly influences the internal ballistic performance by altering the gas mass flow rate,and a larger volume of high-pressure chamber results in more noticeable changes in the pressure difference between the high-and low-pressure chambers.Reasonably increasing the low-pressure chamber volume can effectively reduce the peak acceleration while having a minor effect on the exit velocity of UAV,thereby enhancing the stability of UAV during launch process.The improved PSO algorithm effectively optimizes the parameter selection for low-overload compressed air launch of small UAVs.The research outcomes provide theoretical guidance for the selection,design,testing,and engineering application of compressed air launch parameters of UAVs.

Key words: unmanned aerial vehicle, compressed air launch system, internal ballistic characteristics, particle swarm optimization algorithm

中图分类号:

TJ768.2⁺1

张奉林, 董轶昊, 辛建社, 郭丽萍, 谷雪晨, 曲家琦. 基于粒子群的小型无人机低过载压缩空气发射参数选择和优化算法[J]. 兵工学报, 2025, 46(2): 240014-.

ZHANG Fenglin, DONG Yihao, XIN Jianshe, GUO Liping, GU Xuechen, QU Jiaqi. Parameter Selection and Optimization Algorithm for Low-overload Compressed Air Launch of Small Unmanned Aerial Vehicles Based on Particle Swarm Optimization[J]. Acta Armamentarii, 2025, 46(2): 240014-.

图/表 39

图1 压缩空气发射物理模型简图和参数符号定义

Fig.1 Schematic diagram and parameters definition of compressed air launch model

图2 无人机发射过程受力分析图

Fig.2 Force analysis of UAV launching process

表1 仿真参数

Table1 Simulation parameter

参数	数值
绝热指数r	1.4
气体常数R/(J·kg^-1·K^-1)	287.05
空气定容比热c_v/(J·kg^-1·K^-1)	717.6
发射筒长L/m	1.03
发射角度L/(°)	30
低压室横截面积S_l/m²	0.020 1
弹托面积A_T/m²	0.016 7
脉冲阀流通面积S_P/m²	0.001 3
脉冲阀全开时间t_P/ms	30
高压室初始温度T_h0/K	298
低压室初始容积V₀/m²	0.003 3
低压室初始温度T₀/K	298
低压室初始压强p₀/Pa	101 325

图3 不同压强下无人机加速度随时间变化曲线

Fig.3 Changing curves of acceleration over time under different pressures

图4 不同压强下无人机速度随时间变化曲线

Fig.4 Changing curves of velocity over time under different pressures

图5 不同压强下气体质量流量随时间变化曲线

Fig.5 Changing curves of gas mass flow over time under different pressures

图6 不同压强下高压室温度随时间变化曲线

Fig.6 Temperature variation curves of the high-pressure chamber over time under different pressures

图7 不同压强下高/低压室温差随时间变化曲线

Fig.7 Variation curves of temperature difference between high and low pressure chambers over time under different pressures

图8 压缩空气发射装置结构简图

Fig.8 Schematic diagram of the structure of compressed air launch device

图9 压缩空气发射装置装配

Fig.9 Compressed air launch device assembly

图10 压缩空气发射试验图

Fig.10 Compressed air launch test diagram

表2 发射试验参数

Table 2 Parameters of compressed air launch test

参数	数值
模拟无人机质量/kg	7
弹托质量/kg	1
储气罐容积/L	25
发射筒直径/mm	160
发射筒长/mm	1030

图11 试验加速度与仿真结果对比

Fig.11 Comparison of experimental and simulated accelerations

图12 试验与仿真结果对比

Fig.12 Comparison of experimental and simulated results

表3 试验出筒速度

Table 3 Comparson of experimental and simulated ejecting velocities

参数	高压室压强/MPa
参数	0.6	0.7	0.8
高速摄像机拍摄速度/(m·s^-1)	30.89	32.07	33.99
仿真出筒速度/(m·s^-1)	32.16	33.42	35.68
误差/%	4.11	4.04	4.97

表4 试验峰值过载

Table 4 Comparson of experimental and simulated peak accelerations

参数	高压室压强/MPa
参数	0.6	0.7	0.8
试验峰值加速度/(m·s^-2)	756.34	820.49	931.08
仿真峰值加速度/(m·s^-2)	745.49	809.30	920.56
误差/%	1.43	1.36	1.13

图13 脉冲阀面积随时间变化曲线

Fig.13 Pulse valve area-time curve

图14 不同阀门面积下无人机加速度随时间变化曲线

Fig.14 Changing curves of acceleration over time in the case of different valve areas

图15 不同阀门直径下质量流量随时间变化曲线

Fig.15 Changing curves of mass flow over time in the case of different valve diameters

图16 不同阀门直径下高压室温度随时间变化曲线

Fig.16 Changing curves of temperature of high pressure chamber over time in the case of different valve diameters

图17 不同阀门直径下高压室压强随时间变化曲线

Fig.17 Pressure curves of high pressure chamber over time undein the caser different valve diameters

图18 不同阀门开启时间下阀门面积随时间变化曲线

Fig.18 Changing curves of valve area over time at different valve opening times

图19 不同阀门开启时间下加速度随时间变化曲线

Fig.19 Changing curves of acceleration over time at different valve opening times

图20 不同阀门开启时间下速度随时间变化曲线

Fig.20 Changing curves of speed over time at different valve opening times

图21 不同阀门开启时间下气体质量流量随时间变化曲线

Fig.21 Changing curves of gas mass flow over time at different valve opening times

图22 阀门开启时间30ms下高低压室压强变化曲线

Fig.22 Pressure changes of high and low pressure chambers at the opening time of valve 30ms

图23 不同高压室容积下无人机加速度随时间变化曲线

Fig.23 Pressure changes of high and low pressure chambers at the opening time of 30ms

图24 不同高压室容积下无人机速度随时间变化曲线

Fig.24 Changing curves of velocity over time under different volumes

图25 不同高压室容积下气体质量流量随时间变化曲线

Fig.25 Changing curves of gas mass flow over time under different volumes

图26 不同高压室容积下高压室温度随时间变化曲线

Fig.26 Changing curves of temperature of high pressure chamber over time under different volumes

图27 不同高压室容积下高低压室温差随时间变化曲线

Fig.27 Changing curves of temperature differences of high and low pressure chamber over time under different high pressure chamber volumes

图28 不同低压室容积下无人机加速度随时间变化曲线

Fig.28 Changing curves of UAV acceleration over time under different low pressure chamber volumes

图29 不同低压室容积下无人机速度随时间变化曲线

Fig.29 Changing curves of UAV velocity over time under different low pressure chamber volumes

图30 不同低压室容积下气体质量流量随时间变化曲线

Fig.30 Changing curves of gas mass flow over time under different low pressure chamber volumes

图31 不同低压室容积下高/低压室温差随时间变化曲线

Fig.31 Changing curves of temperature difference of high/low pressure chambers over time under different low pressure chamber volumes

图32 基于子母弹原理的改进PSO算法计算流程图[22]

Fig.32 CBPSO computational flowchart[22]

图33 每代加速度适应度值变化

Fig.33 The change of acceleration fitness value in each iteration

表5 发射参数优化对比结果

Table 5 Comparison of launch parameter optimization results

发射参数	PSO算法	CBPSO算法
高压室压强/MPa	0.673	0.792
高压室容积/L	21	35
低压室容积/L	8.5	13.0
脉冲阀全开时间/ms	80.3	86.9
阀门直径/mm	64.8	35.2
速度/(m·s^-1)	31.05	30.02
加速度/(m·s^-2)	605.78	495.47

图34 优化前后加速度对比

Fig.34 Accelerations before and after optimization

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