比例式变推力固体姿控发动机非稳态特性研究

为了研究比例式变推力固体姿控发动机的内流场非稳态特性,建立了比例针栓推力器的二维轴对称计算模型,基于动网格技术模拟入口压强随喉部面积变化而变化的推力器工作模式,得到了内流场各性能参数的变化规律。结果表明:在非稳态工作过程中,内流场会出现典型的亚音速回流区、斜激波和流动分离等特征,入口压强、针栓壁面及喷管壁面压强均随针栓靠近喉部而增大,推力器推力逐渐上升,实现了推力连续调节。开关频率会加剧针栓前进过程中头部压强波动。针栓头部收敛角越大,其头部回流区越小。当喉部面积一定时,燃速压强指数越高,发动机压强与推力变化范围越大,为实现预设的推力调节范围,需要选择合适的燃速压强指数。     

后摆心潜入式喷管柔性接头力学特性数值仿真

针对后摆心潜入式喷管柔性接头在燃气压力与摆动联合载荷下,弹性件与增强件的力学特性计算问题,建立了对称刚体-柔性体结合的几何模型;采用了有限元方法,获取了柔性接头在燃气压力、摆动载荷及联合载荷下应力、弹性比力矩分布规律。研究表明:随着燃气压力增大,弹性比力矩降低;随摆角增大,弹性比力矩增大。文中的数值仿真方法,可以应用于柔性接头力学特性的计算,为柔性接头强度的安全性评估提供指导。     

基于反电势形状函数法的无刷直流电动机直接转矩控制

采用两相导通模式时通过逆变器开关状态不能确定电压空间矢量,现有方案是通过实时测量3个相电压来解决这一问题,但系统变得复杂;此外现有方案在转矩观测中包含的微分项会降低控制精度,增大计算量,影响系统实时性。针对这两点不足,提出反电势形状函数法,在软件中实现了相电压的实时计算,使转矩观测变得简洁,更易于工程实用。最后给出的仿真与实验结果证明了反电势形状函数法用于无刷直流电机直接转矩控制中的可行性与有效性。     

一种民用飞机电作动舱门集中式控制方案研究

在未来飞机多/全电化和机电综合管理的发展趋势下,舱门作动器逐渐由机电作动取代了传统的液压、机械作动。针对目前民用飞机舱门分散式独立控制杂、乱、散的局面,提出一种用于电作动舱门的集中式控制方案。对该集中式控制方案下如何实现电机的伺服控制、舱门的并行控制以及接近传感器感应距离值的修改进行设计,并搭建舱门作动系统模拟装置及电机加载试验平台,对集中式控制的架构及电机伺服控制进行试验验证。结果表明：本文提出的电作动舱门集中式控制方案是可行的,该方案能够大幅减少舱门线缆数量,降低舱门系统的复杂度,提高系统可靠性及可维护性。     

SolidWorks二次开发在燃面计算中的应用

以SolidWorks二次开发接口为基础,探讨了参数化设计在固体火箭发动机装药燃面计算中的应用.通过不同的药柱建模方法实现了固体药柱的装药计算,发展了一种更为简单准确的燃面计算方法.计算结果表明,理论计算和试验结果吻合得较好,能够较好地模拟固体药柱的燃烧过程,可以满足工程计算上的需要,为固体装药的燃面计算提供了新的思路和方法.      

基于滑模变结构的永磁同步电机精确线性化控制

 永磁同步电机是一个多变量、非线性、强耦合系统,从非线性动态数学模型出发,应用精确线性化理论,实现了永磁同步电机系统的输入-输出线性化与解耦。通过线性化模型设计速度跟踪控制律,用指数滑模变结构控制器来设计电流调节器,算法简单实用,提高了速度跟踪的快速性和精确性。仿真和实验结果表明,该控制策略具有理想的动态性能和良好的鲁棒性。     

基于自动代码生成技术的永磁同步电机控制

为缩短电机控制系统软件开发周期,减少手写代码人力消耗,将自动代码生成技术应用于机载燃油泵用电机控制系统的软件开发中,介绍了自动代码生成技术的特点及开发流程,在MATLABSimulink环境下搭建了基于矢量控制算法的永磁同步电机系统控制模型,通过实验将模型自动生成为嵌入式代码,成功的实现了电机的闭环控制,极大地提高了开发效率,达到了预期成果。     

Three-dimensional numerical analysis on combustion performance and flow of hybrid rocket motor with multi-segmented grain

This paper presents the combustion characteristics in hybrid rocket motors with multisegmented grain through three-dimensional numerical simulations. Multi-segmented grain is composed of several thin grains with two or more ports. The numerical model consists of Navier-Stokes equations with turbulence, solid fuel pyrolysis, chemical reactions, a fluid–solid coupling model and a regression rate model. The simulations adopt 90% Hydrogen Peroxide(HP) and PolyEthylene(PE) as the propellant combinati...     

探空火箭图像压缩算法研究

结合探空火箭图像系统需求, 提出了一种基于小波变换编码, 即基于MSPIHT的自适应差分算术编码(MSPIHT Adaptive Differential Arithmetic Coding for image, MADAC)的图像压缩算法. 该算法对经过量化编码之后的数据 进行熵编码. 实验结果表明, MADAC算法具备探空火箭图像系统所要求的分辨 率、帧速率及压缩率可调的功能, 且易于硬件实现.     

Dynamic neighborhood genetic learning particle swarm optimization for high-power-density electric propulsion motor

To maximize the power density of the electric propulsion motor in aerospace application, this paper proposes a novel Dynamic Neighborhood Genetic Learning Particle Swarm Optimization (DNGL-PSO) for the motor design, which can deal with the insufficient population diversity and non-global optimal solution issues. The DNGL-PSO framework is composed of the dynamic neighborhood module and the particle update module. To improve the population diversity, the dynamic neighborhood strategy is first proposed, which combines the local neighborhood exemplar generation mechanism and the shuffling mechanism. The local neighborhood exemplar generation mechanism enlarges the search range of the algorithm in the solution space, thus obtaining high-quality exemplars. Meanwhile, when the global optimal solution cannot update its fitness value, the shuffling mechanism module is triggered to dynamically change the local neighborhood members. The roulette wheel selection operator is introduced into the shuffling mechanism to ensure that particles with larger fitness value are selected with a higher probability and remain in the local neighborhood. Then, the global learning based particle update approach is proposed, which can achieve a good balance between the expansion of the search range in the early stage and the acceleration of local convergence in the later stage. Finally, the optimization design of the electric propulsion motor is conducted to verify the effectiveness of the proposed DNGL-PSO. The simulation results show that the proposed DNGL-PSO has excellent adaptability, optimization efficiency and global optimization capability, while the optimized electric propulsion motor has a high power density of 5.207 kW/kg with the efficiency of 96.12%.