太阳能/氢能无人机总体设计与能源管理策略研究

针对小型低空长航时电动无人机需求,给出了太阳能/氢能混合能源动力系统集成方案和小型低空长航时无人机构型。针对典型任务剖面,综合考虑太阳能电池和氢燃料电池特性,提出了一种考虑全机重量能量耦合关系的总体设计方法和任务剖面驱动的能源管理策略;建立了能源系统模型,给出了能源控制流程,开发了能源管理仿真平台。以1.5 kg任务载荷为例,完成了无人机总体方案设计,仿真分析了各种能源特性对飞行结果的影响。结果表明:能源管理策略能够根据任务剖面的要求合理配置能源系统的功率,满足各阶段的功率需求;无人机在冬至日航时为21 h、夏至日可实现跨昼夜飞行;在能源系统重量相同情况下,该混合能源无人机的航时分别是纯锂电池无人机和燃料电池无人机的5.5倍和1.2倍。     

六旋翼无人机单个旋翼失效后性能变化研究

针对六旋翼城市物流无人机RA3在一个旋翼失效后继续巡航的性能参数变化问题进行了研究。综合考虑了无人机的飞行特点，建立了飞行任务剖面各阶段模型，包括悬停、爬升、降落和巡航阶段，通过搭建测试平台和进行试验获得动力参数。模型算例表明：当无人机的一个旋翼失效后继续飞行，剩余工作旋翼的转速和功率均会增大；虽然各个旋翼的功率和能耗有所增加，但是同样的电池电量提供的续航里程与无故障正常巡航时基本相同。     

高空长航时无人机航迹优化研究

主要探讨了高空长航时无人机的最省油的爬升-巡航航迹。采用改进了的遗传算法,求解了无人机从起飞到达目标区的最优航迹,并与传统的飞行方式作了比较。结果表明,采用改进了的遗传算法得到的航迹可以有效地减少无人机的耗油量,具有明显的经济、军事意义。     

混合动力系统建模及能量管理策略应用

针对混合动力系统能量管理问题，在Matlab/Simulink 平台下建立1.8 kW 质子膜燃料电池和锂电池部件级模型，基于部 件级模型建立燃料电池/ 蓄电池混合动力系统模型，采用有限状态机方法建立能量管理模块，制定功率需求计划进行仿真。结果表 明：质子膜燃料电池和锂电池部件模型符合实际特性，燃料电池/ 蓄电池混合动力系统模型工作正常，直流总线电压相对稳定，所 用拓扑结构具有保护储能部件的优点，系统实际功率分配符合能量管理策略。验证了燃料电池/ 蓄电池混合动力系统模型用于能 量管理策略的可行性。     

太阳能无人机能源系统的初步设计方法

正太阳能无人机与燃料无人机、电动无人机的最根本区别在于能源系统,因为太阳能无人机在空中飞行过程中仅依靠太阳能电池阵列转换太阳光照辐射能来产生电能,而不用中途降落添加燃料或为电池充电,可以实现超长时间的空中巡航,在军事及民用领域都有很广阔的应用前景。太阳能无人机的能源系统直接影响全机的输出功率和质量,主要由太阳能电池阵列、锂电池、最大功率跟踪(Maximum Power Point Tracking,MPPT)控制器等部分     

考虑局部遮挡的太阳能无人机能源控制

针对太阳能无人机在飞行状态下可能出现的太阳能电池局部遮挡情况，开展相应的太阳能电池最大功率点追踪算法和能源控制研究。通过将发光亮度引入相对吸引力计算过程对萤火虫算法进行改进，实现了局部阴影情况下太阳能电池最大功率点的高效追踪。以此为基础，设计了考虑局部遮挡情况下太阳能无人机的太阳能电池/蓄电池混合能源状态机控制规则。以"蒲公英I"无人机为例，建立了太阳能电池阵列模型，开展了考虑局部遮挡情况下太阳能电池最大功率点追踪仿真实验；基于"蒲公英I"飞行剖面，开展了考虑局部遮挡情况的混合能源控制仿真试验。研究结果表明：改进的萤火虫算法可以实现在局部阴影情况下太阳能电池最大功率点的有效跟踪，与萤火虫算法相比收敛时间更短、且功率波动幅度更小；采用改进萤火虫算法和状态机能源管理策略，在考虑局部遮挡的飞行状态下可以实现太阳能电池/蓄电池之间的合理功率分配与控制。     

燃料电池无人机混合电源动态平衡能量管理策略

飞机电推进的动力系统趋于混合能源形式的发展方向，不同类型的源具有不同的特性，混合能源协调工作的方式可以提高动力系统的性能。本文所研究的飞机电推进系统的能源形式为燃料电池和锂电池所做成的混合能源。针对无人机动力系统工况的特殊性，本文在基于规则的能量管理策略研究基础上，提出了一种基于燃料电池氢气消耗的动态平衡能量管理策略，使燃料电池和辅助电源的能量消耗处于相对平衡的状态，避免了其中一种电源能量先耗尽的情况，可以满足多种工况的变化，提高了混合电源的能量利用率和稳定性，保证了无人机动力系统的可靠性。通过仿真分析结果证明了可行性，最后设计了能量管理系统的硬件并进行了实验验证，通过对实验结果计算分析验证了该能量管理策略的可行性。     

燃料电池无人机动力系统方案设计与试验

针对燃料电池为主能源的无人机（UAV）动力系统,设计了纯燃料电池动力系统、燃料电池/蓄电池（简称燃蓄）被/主动混合动力系统3种拓扑结构方案。以空冷质子交换膜燃料电池为例,搭建了燃料电池动力系统方案一体化试验平台。考虑阶梯型和阶跃型2种加载形式,试验研究了燃料电池自身的动态特性和启动特性。以阶梯型功率剖面的加载形式,试验研究了纯燃料电池动力系统放电特性;以无人机典型任务剖面作为加载形式,开展燃蓄被/主动混合动力系统对比试验研究。试验结果表明：纯燃料电池动力方案适用于低机动小型无人机,燃蓄被动混合方案可满足小型无人机大机动飞行,燃蓄主动混合方案系统可适应中大型无人机更长航时飞行。     

基于绿色能源的分布式混合电推进系统性能分析

基于绿色能源的电推进飞行器是是航空运输业实现碳中和的重要技术途径。本文旨在利用理论分析和数值计算的手段,研究基于绿色能源的分布式混合电推进系统的性能,重点关注锂电池和固体氧化物燃料电池(SOFC)在航程和载荷方面的影响。本研究构建了一个包含多种能源形式的混合电推进系统架构,并基于能量流建立了功率传递模型,推导出综合考虑部件特征参数、能量分配参数、飞行气动参数的电推进系统航程方程和载荷方程。研究结果显示,在航程方面,锂电池的能量分配系数和能量密度对飞机航程有显著影响,特别是在能量密度阈值之上,增加锂电池的能量分配系数对提升航程有正收益。此外,SOFC的能量分配系数和效率的增加也提高了飞机航程,特别是在其高值区域。在载荷方面,上述锂电池和SOFC参数对飞机零燃料质量(MZF)和有效载荷具有重要影响,尤其在高能量密度、高效率和高能量分配系数的情况下飞机的载荷性能改善最佳。参数敏感性分析揭示了升阻比、边界层吸入(BLI)风扇效率、锂电池荷电状态(α_soc)和氢燃料剩余状态(α_soh)对航程的显著影响,其中在以往研究中较少出现的α_soc     

无人机爬升航迹优化设计研究

为改进无人机的飞行性能，应用可变误差多面体法求解了在垂直平面内的最经济和最快爬升轨迹。计算结果表明，经优化后的爬升航迹可以节省燃油，延长无人机的续航时间和有效任务时间，具有较好的性能收益。     

State of art on energy management strategy for hybrid-powered unmanned aerial vehicle

New energy sources such as solar energy and hydrogen energy have been applied to the Unmanned Aerial Vehicle(UAV), which could be formed as the hybrid power sources due to the requirement of miniaturization, lightweight, and environmental protection issue for UAV. Hybrid electrical propulsion technology has been used in UAV and it further enforces this trend for the evolution to the Hybrid-Powered System(HPS). In order to realize long endurance flight mission and improve the energy efficiency of UAV, many researching works are focused on the Energy Management Strategy(EMS) of the HPS with digital simulation, ground demonstration platforms and a few flight tests for the UAV in recent years. energy management strategy, in which off-line or on-line control algorithms acted as the core part, could optimize dynamic electrical power distribution further and directly affect the efficiency and fuel economy of hybrid-powered system onboard.In order to give the guideline for this emerging technology for UAV, this paper presents a review of the topic highlighting energy optimal management strategies of UAV. The characteristics of typical new energy sources applied in UAV are summarized firstly, and then the classification and analysis of the architecture for hybrid power systems in UAV are presented. In the context of new energy sources and configuration of energy system, a comprehensive comparison and analysis for the state of art of EMS are presented, and the various levels of complexity and accuracy of EMS are considered in terms of real time, computational burden and optimization performance based on the optimal control and operational modes of UAV. Finally, the tendency and challenges of energy management strategy applied to the UAV have been forecasted.     

Energy Management for Fuel Conservation in Transport Aircraft

Optimal control techniques have been applied to the problem of conserving fuel in C-141A aircraft. Numberical results form the basis for designing an on-board energy management system, which can automatically command fuel-optimal climb, cruise, and descent flight paths for a majority of this aircraft's missions.     

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.     

Mission-oriented cooperative 3D path planning for modular solar-powered aircraft with energy optimization

Modular Solar-Powered Aircraft(M-SPA) is a kind of High-Altitude Long-Endurance(HALE) aircraft which exploits the mission advantage of swarm UAV and the HALE advantage of large aspect-ratio SPA. M-SPA’s separated mode and combined mode give it the potential to maximize the mission efficiency with limited solar energy. In this paper, firstly, oriented by the mission of maximizing the cruise area, the overall design of the M-SPA is modeled, including the energy model, the aerodynamic model and the...     

基于自适应神经模糊推理算法的无人机电推进燃料电池供气系统性能优化

本文针对某无人机基于聚合物交换膜燃料电池和锂离子电池的混合动力电推进系统的应用,研究开发了一种基于自适应神经模糊推理系统的电源管理系统控制技术,以控制混合动力电力推进系统,同时优化燃料电池供气系统的性能。本文以所建立的某无人机混合电推进系统数学模型为研究对象,研究了燃料电池电流与燃料电池供气系统压缩机功率之间的关系,建立了燃料电池电流与最佳压缩机功率关系的参考模型。在参考模型的基础上,引入自适应控制器来优化燃料电池供气系统的性能。基于自适应神经模糊推理系统的控制器将压缩机的实际运行功率动态调整到参考模型中定义的最佳值。自适应控制器的在线学习和训练能力用来辨识燃料电池电流的非线性变化,并产生压缩机电机电压的控制信号,以优化燃料电池供气系统的性能。在Matlab 仿真环境中开发了质子交换膜燃料电池和锂离子混合动力电推进系统模型并对所设计的控制器进行了仿真分析,结果表明基于自适应神经模糊推理系统的控制器为燃料电池供气系统压缩机性能优化提供了一种新颖而全面的途径,使燃料电池供气系统获得最大净功率输出。将燃料电池系统的净功率输出与最佳压缩机功率和恒定压缩机功率进行了比较,结果表明优化的压缩机功率配置比恒定的压缩机功率配置节能2.62%。同时,燃料电池自适应神经模糊推理系统控制器优化了燃料电池供气系统的能量利用。     

New reference trajectory optimization algorithm for a flight management system inspired in beam search

With the objective of reducing the flight cost and the amount of polluting emissions released in the atmosphere, a new optimization algorithm considering the climb, cruise and descent phases is presented for the reference vertical flight trajectory. The selection of the reference vertical navigation speeds and altitudes was solved as a discrete combinatory problem by means of a graphtree passing through nodes using the beam search optimization technique. To achieve a compromise between the execution time and the algorithm's ability to find the global optimal solution, a heuristic methodology introducing a parameter called ‘‘optimism coefficient was used in order to estimate the trajectory's flight cost at every node. The optimal trajectory cost obtained with the developed algorithm was compared with the cost of the optimal trajectory provided by a commercial flight management system(FMS). The global optimal solution was validated against an exhaustive search algorithm(ESA), other than the proposed algorithm. The developed algorithm takes into account weather effects, step climbs during cruise and air traffic management constraints such as constant altitude segments, constant cruise Mach, and a pre-defined reference lateral navigation route. The aircraft fuel burn was computed using a numerical performance model which was created and validated using flight test experimental data.     

伸缩弹翼巡航导弹气动外形优化研究

基于一种伸缩弹翼改变巡航导弹外形的概念,提出超声速巡航与亚声速盘旋相结合的飞行任务,使用Missile Datcom作为气动计算的工具,分别对固定翼、两级伸缩翼和三级伸缩翼的外形参数进行了优化,使三种不同弹翼导弹完成相同飞行任务的燃料消耗分别最小,优化方法选取遗传算法与模式搜索法相结合的混合优化策略.优化结果显示,两级、三级伸缩翼巡航导弹相对固定翼巡航导弹燃料消耗量分别减少7.8%和12%,表明伸缩弹翼有效提高了巡航导弹在整个飞行任务中的气动性能.