高空长航时太阳能无人机总体设计要点分析

高空长航时（HALE）太阳能无人机（UAV）的基本工作原理与常规动力飞机相比有显著的区别,体现在飞机总体设计方法上有其独到之处,方案设计中还需要对一些关键技术细节进行认真权衡。阐述了高空长航时太阳能无人机总体设计中遵循的重量不变和能量平衡原则的机理,同时从太阳能无人机巡航平飞功率需求、布局形式选取、飞行剖面优化和临近空间使用环境影响等方面出发,研究了太阳能无人机总体设计中的若干注意事项,主要结论可用于高空长航时太阳能无人机总体设计和方案优化。     

Flight trajectory optimization of sun-tracking solar aircraft under the constraint of mission region

The optimal yawing angle of sun-tracking solar aircraft is tightly related to the solar azimuth angle, which results in a large arc flight path to dynamically track the sun position. However, the limited detection range of payload usually requires solar aircraft to loiter over areas of interest for persistent surveillance missions. The large arc sun-tracking flight may cause the target area on the ground to be outside the maximum coverage area of payload. The present study therefore develops an optimal flight control approach for planning the flight path of sun-tracking solar aircraft within a mission region. The proposed method enables sun-tracking solar aircraft to maintain the optimal yawing angle most of the time during daylight flight, except when the aircraft reverses its direction by turning flight. For a circular region with a mission radius of 50 km, the optimal flight trajectory and controls of an example Λ-shaped sun-tracking solar aircraft are investigated theoretically. Results demonstrate the effectiveness of the proposed approach to optimize the flight path of the sun-tracking aircraft under the given circular region while maximizing the battery input power. Furthermore, the effects of varying the mission radius on energy performance are explored numerically. It has been proved that both net energy and energy balance remain nearly constant as the radius constraint varies, which enables the solar aircraft to achieve perpetual flight at almost the same latitude as the large arc flight. The method and results presented in this paper can provide reference for the persistent operation of sun-tracking solar aircraft within specific mission areas.     

Dynamic temperature prediction of electronic equipment under high altitude long endurance conditions

Unmanned Aerial Vehicle (UAV) is developing towards the direction of High Altitude Long Endurance (HALE). This will have an important influence on the stability of its airborne electronic equipment using passive thermal management. In this paper, a multi-node transient thermal model for airborne electronic equipment is set up based on the thermal network method to predict their dynamic temperature responses under high altitude and long flight time conditions. Some relevant factors are considered into this temperature prediction model including flight environment, radiation, convection, heat conduction, etc. An experimental chamber simulating a high altitude flight environment was set up to survey the dynamic thermal responses of airborne electronic equipment in a UAV. According to the experimental measurement results, the multi-node transient thermal model is verified without consideration of the effects of flight speed. Then, a modified way about outside flight speed is added into the model to improve the temperature prediction performance. Finally, the corresponding simulation code is developed based on the proposed model. It can realize the dynamic temperature prediction of airborne electronic equipment under HALE conditions.     

国外高空长航时无人机动力技术的发展

高空长航时无人机是一种可在18—24km高空范围飞行、巡航时数不少于24h的无人机，在军用和民用领域都有广阔的应用前景。但是，由于高空长航时无人机的飞行任务与常规飞机的相比有很大不同，因此，为其动力装置的发展带来了很多新的技术挑战。     

高空长航时无人机总体参数多目标优化

以高空长航时无人机的总体方案研究为背景,对高空长航时无人机总体参数建立了多目标优化模型,运用多目标遗传算法进行优化设计,最后通过建立的计算机程序得出优化结果.多目标优化用于高空长航时无人机总体参数优化,可以更加合理地评价高空长航时无人机的总体参数的最佳组合,避免设计上的缺陷,提高设计效率.结果表明,高空长航时无人机优化后的总体性能得到改善,说明该方法适用于高空长航时无人机总体方案的优化设计,对方案研究有一定参考价值.     

Energy-optimal trajectory planning for solar-powered aircraft using soft actor-critic

High-Altitude Long-Endurance (HALE) solar-powered Unmanned Aircraft Vehicles (UAVs) can utilize solar energy as power source and maintain extremely long cruise endurance, which has attracted extensive attentions from researchers. Trajectory optimization is a promising way to achieve superior flight time because of the finite solar energy absorbed in a day. In this work, a method of trajectory optimization and guidance for HALE solar-powered aircraft based on a Reinforcement Learning (RL) framework is introduced. According to flight and environment information, a neural network controller outputs commands of thrust, attack angle, and bank angle to realize an autonomous flight based on energy maximization. The validity of the proposed method was evaluated in a 5-km radius area in simulation, and results have shown that after one day-night cycle, the battery energy of the RL-controller was improved by 31% and 17% compared with those of a Steady-State (SS) strategy with a constant speed and a constant altitude and a kind of state-machine strategy, respectively. In addition, results of an uninterrupted flight test have shown that the endurance of the RL controller was longer than those of the control cases.     

Impact of mission requirements and constraints on conceptual launch vehicle design

The objective of this paper is to analyse the impact of mission requirements and constraints on both the optimum vehicle design and the effects on flight path selection for two types of reusable two-stage-to-orbit launch vehicles. The first vehicle type considered provides horizontal take-off and landing capabilities and is intended to be propelled by an airbreathing propulsion system during stage 1 flight. The second vehicle type assumes a vertical launch and is accelerated by a rocket propulsion system during the booster stage ascent flight. The analysis employs a design tool for simultaneous system and mission optimization. It consists of a CAD-based preliminary vehicle design tool, aerodynamic and aerothermodynamic calculation software, flight simulation programs, and a two-level decomposition optimization algorithm enabling simultaneous system and flight optimization. The results to be presented show that the cruise flight requirement for an European launched mission of the airbreathing vehicle results in a loss of 60 % payload mass as compared to a mere accelerated ascent for a near equatorial mission into the same target orbit assuming constant take-off mass. The strong dependencies of mission requirements on both the optimal vehicle design and the ascent performance are determined for the rocket-powered vehicle type by varying the inclination and altitude of the target orbit.     

Effective control allocation using hierarchical multi-objective optimization for multi-phase flight

For different flight phases in an overall flight mission, different control and allocation preferences should be pursued considering lift, drag or maneuverability characteristics. The multi-objective flight control allocation problem for a multi-phase flight mission is studied. For an overall flight mission, different flight phases namely climbing, cruise, maneuver and gliding phases are defined. Firstly, a multi-objective control allocation problem considering drag, lift or control energy preference is constructed. Secondly, considering different control preferences at different flight phases, the analytic hierarchical process method is used to construct a comprehensive performance index from different objectives such as lift or drag preferences. The active set based dynamic programming optimization method is used to solve the real-time optimization problem. For the validation, the Innovative Control Effector (ICE) tailless aircraft nonlinear model and the angular acceleration measurements based adaptive Incremental Backstepping (IBKS) are used to construct the validation platform. Finally, an overall flight mission is simulated to demonstrate the efficiency of the proposed multi-phase and multi-objective flight control allocation method. The results show that the comprehensive performance index for different phases, which are determined from the Analytic Hierarchy Process (AHP) method, can suitably satisfy the preference requirements for different flight phases.     

一种飞行器投放分离气动力辨识修正方法

空中投放发射的大翼面飞行器的分离轨迹与姿态受载机干扰流场影响更加明显,对分离时干扰气动数据库的准确性提出了更高要求。针对投放分离干扰气动力特点,提出了一种简化的差量气动力模型,并给出了一套飞行数据处理与参数预估计的方法。分离段飞行数据的辨识结果与六自由度飞行动力学仿真结果说明了提出的差量气动模型与相关数据处理方法的有效性。用辨识结果对气动数据库进行修正提高了数据库的准确度,可提高分离安全飞行仿真分析的精度。     

Autonomous mission reconstruction during the ascending flight of launch vehicles under typical propulsion system failures

In recent years, Chinese Long March(LM) launchers have experienced several launch failures, most of which occurred in their propulsion systems, and this paper studies Autonomous Mission Reconstruction(AMRC) technology to alleviate losses due to these failures. The status of the techniques related to AMRC, including trajectory and mission planning, guidance methods,and fault tolerant technologies, are reviewed, and their features are compared, which reflect the challenges faced by AMRC technology...     

飞行器体系优化设计问题

针对传统的飞行器设计与体系（SOS）设计相互独立造成的飞行器实际作战效能不足的问题,对同时考虑飞行器与体系耦合设计的飞行器体系优化设计问题展开研究。首先,根据体系工程（SOSE）原理给出了耦合飞行器设计与体系结构设计的飞行器体系优化设计问题的基本概念与通用数学定义;其次,基于多层体系架构,构建了飞行器体系设计优化模型,提出了包含问题定义、体系架构建模、学科建模、优化求解4个步骤的通用建模求解流程;最后,以巡飞/精确打击武器协同作战为例,构建了面向任务成本最低、时间最短的协同作战体系最优化问题并对其进行优化求解。与先设计飞行器后设计体系结构的解耦设计结果对比表明,解耦优化设计忽略了体系结构与飞行器的强耦合特征,无法最优化体系效能;耦合优化设计能够获得体系效能最大化的飞行器设计方案。     

并联混合动力齿轮传动涡扇发动机建模与性能分析

为对比探究未来大推力航空混合动力系统与传统航空发动机的优劣,本文依托某概念型齿轮传动涡扇(Geared turbofan,GTF)发动机,设计了一个并联航空油-电混合动力系统(hybrid GTF,hGTF),在Matlab /Simulink数字仿真软件中建立相匹配的电动力模型以及氮氧化物NOx排放和噪声预测等性能参数计算模型,并在稳态和飞行任务剖面下初步分析了电动力系统的引入对原基线GTF发动机的性能改变状况。稳态仿真结果表明,大推力等级的并联油-电混合动力系统中,至少需要兆瓦级的电动力系统进行匹配;当电动力系统处于电动模式时,可能会带来低压压气机喘振的隐患;当电动力系统处于再生模式时,电能源相当于经过了电能到机械能再到电能的二次效率损失,不建议采用。飞行任务剖面动态仿真结果表明,相比于传统GTF发动机,hGTF推进系统的燃油消耗率最高下降15%,总燃油消耗节省8.3%, NOx总排放量减少18.8%,各部件起飞噪声总声压级减少1.5~3.3dB。分析结果表明采用并联混合动力系统具有显著提升省油、减排效果的能力,同时也具有一定的降噪潜力。     

多太阳能无人机覆盖路径优化方法

为解决传统电动无人机在覆盖作业时存在的续航时间短的问题,提出应用多架太阳能无人机进行覆盖作业。首先,在建立了应用于覆盖作业的太阳能无人机的能量模型的基础上,提出了能量流动效率这一指标来评价太阳能无人机在作业过程中对能量的利用率。其次,针对边界存在障碍物的凹多边形区域和内部含障碍物的多边形区域,以总作业完成时间最短为优化目标,提出基于无向图搜索方法的覆盖路径优化模型,定义约束方程限制无人机按照一定规则访问无向图中的节点,通过混合整数线性规划的方法求解每架无人机的最优飞行路径。再次,考虑无人机转弯时的姿态变化对能量流动效率的影响,将总作业完成时间最短和总能量流动效率最高同时作为优化目标,建立双目标优化方程,在首先以作业时间最短为优化目标进行求解的基础上,通过有限遍历的方式选择使能流效率和作业时间相对最优的覆盖飞行方向及飞行路径。大量仿真实验表明,所提的优化模型选取不同的优化目标,应用于不同形状的待覆盖区域,适用性广,在工程上应用范围广、可行性强。     

飞机总能量控制系统的研究Ⅰ——原理分析与系统设计

飞机总能量控制是一种全新的综合飞行/推力控制技术,从控制飞机总能量的变化与分配出发,全面解决纵向飞行轨迹控制与速度控制之间的耦合问题;进而建立起一体化的综合飞行控制系统。用多变量系统解耦控制理论研究了这种控制系统,首先分析了总能量控制的基本思想,建立起包含飞机纵向姿态控制回路和发动机推力控制回路的飞机质点能量运动模型,然后利用输出反馈和V规范型前馈解耦策略,对此系统进行解耦分析,设计出能实现飞行轨迹与速度间解耦控制的总能量控制律,并确定出系统的设计条件;最后以波音(Boeing)707飞机为对象,进行了具体的系统设计。     

高空长航时飞翼无人机用涡扇发动机关键技术

自无人机诞生并应用于实战以来,无人机技术得到了迅猛的发展。随着各领域高科技技术的进步,战场环境趋于复杂,作战任务向高危对抗战场拓展,高空长航时飞翼无人机成为各国研究的热点。本文论述了高空长航时飞翼无人机对涡扇发动机的要求,结合航空发动机基本原理分析了关键设计参数对涡扇发动机性能的影响,总结了高空长航时飞翼无人机用涡扇发动机面临的关键问题及研究进展,对于高空长航时飞翼无人机用涡扇发动机的选型及适应性改进设计具有重要的参考价值。     

超长航时太阳能无人机关键技术综述

超长航时太阳能无人机（UAV）以其高效节能、原理上可实现无限巡航的特点受到广泛关注，而其独特的设计指标与任务特性也对各项关键技术提出了较高要求。多设计要素的高度耦合意味着不同于常规飞行器的总体设计方法，低密度、低速度的飞行条件使其具有明显的低雷诺数气动特性，柔性超大展弦比机翼带来了复杂的气动弹性问题，低翼载荷特性与较大的风场扰动增加了控制难度，极端的飞行环境与苛刻的任务指标对能源、动力系统带来了新挑战，飞行性能对能源系统的高度依赖开辟了飞行轨迹优化的研究方向。本文梳理了超长航时太阳能无人机关键技术的研究现状，在此基础上对各项技术中的难点问题进行了阐释，并对超长航时太阳能无人机未来发展趋势进行了展望。     

可重复使用飞行器导航制导控制技术展望

针对当前可重复使用飞行器的发展现状,总结了其特点、优势和发展趋势.通过飞行任务,分析了可重复使用飞行器所面临的复杂环境特性和飞行控制特性.从飞行控制角度出发,概括了可重复使用飞行器导航制导控制所面临的技术挑战,包括高精度导航技术、多约束航迹优化技术、再入段和能量管理段的制导技术以及强耦合强不确定强鲁棒姿态控制技术等.最后,针对技术挑战,对可重复使用飞行器导航制导控制技术提出了若干建议.     

民机自动飞行模式设计规范与适航性分析

民机自动飞行系统对降低飞行员工作负荷、提高飞行安全性具有重要作用.分析了自动飞行系统飞行模式设计的相关适航规范要求,研究了模式设计的基本方法和软件开发工具,以及适航符合性验证方法.开发了一种飞行模式设计与仿真平台,基于MATLAB/Stateflow设计飞行模式及其切换机制,采用MATLAB/GUI接收驾驶员操作输入,并调用飞行动力学模型进行实时仿真.形成一个集模式设计、仿真和验证一体化的闭环平台,可用于民机飞行模式的设计和适航性分析.     

虚拟现实技术在飞行器级间分离仿真中的应用

主要讨论应用虚拟现实技术进行飞行器级间分离仿真分析的方法。给出了飞行器级间分离仿真时用于控制飞行器模型运动的虚拟世界结构，并且据此建立了一个包括飞行器模型和场景模型的虚拟世界。基于Matlab和Simulink，还给出了将虚拟世界与其它的计算程序结合起来的方法，实现计算、仿真、显示一体化。基于此框架，通过流体力学、飞行力学计算以及级间相对姿态和位置的计算和分析．研究讨论了飞行器级间分离碰撞干扰问题，为级间分离方案和分离机构设计提供了依据。     

燃料电池无人机能源管理与飞行状态耦合

开展了燃料电池/锂电池（简称燃锂）混合动力无人机的能源管理与飞行状态耦合研究。综合顶层飞行任务规划与底层能源系统管理，以动力系统模型为耦合点联立能源系统与无人机运动方程，建立能源状态与运动状态耦合模型。针对燃锂混合最紧密的爬升过程，以迎角、转速和燃料电池的放电功率作为控制变量，建立了燃料消耗最小的能源管理与航迹规划耦合最优控制问题，研究不同爬升高度对最优控制过程的影响，并与模糊控制能源管理策略进行对比分析。针对大功率短时爬升和小功率长时巡航的典型任务特点，建立了燃锂最优混合问题。研究了最优的锂电池容量和燃料电池功率水平的混合量，以及爬升和巡航两阶段最优功率分配和飞行状态，分析了不同巡航目标高度对最优混合量和飞行状态的影响。结果表明：采用能源与航迹耦合的最优控制策略在给出最优功率流分配的同时，能够很好地兼顾飞行状态控制；对燃锂混合和飞行状态的综合优化可以有效地处理爬升和巡航阶段的能源需求矛盾，在给出最优燃锂混合量和飞行状态的同时，降低整个任务过程的燃料消耗。