Article(id=1322941593405235395, tenantId=1146029695717560320, journalId=1322258626896822465, issueId=1322941226537857309, articleNumber=null, orderNo=null, doi=10.13700/j.bh.1001-5965.2026.0440, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1782662400000, receivedDateStr=2026-06-29, revisedDate=null, revisedDateStr=null, acceptedDate=1787241600000, acceptedDateStr=2026-08-21, onlineDate=1793343454933, onlineDateStr=2026-10-30, pubDate=1793376000000, pubDateStr=2026-10-31, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793343454933, onlineIssueDateStr=2026-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793343454933, creator=13701087609, updateTime=1793343454933, updator=13701087609, issue=Issue{id=1322941226537857309, tenantId=1146029695717560320, journalId=1322258626896822465, year='2026', volume='52', issue='10', pageStart='3237', pageEnd='3676', issueExtLink='null', onlineDate='null', pubDate='1793376000000', pubDateStr='2026-10-31', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1793343367466, creator='13701087609', updateTime=1793344760378, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322947068926505286, tenantId=1146029695717560320, journalId=1322258626896822465, issueId=1322941226537857309, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322947068926505287, tenantId=1146029695717560320, journalId=1322258626896822465, issueId=1322941226537857309, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3563, endPage=3579, ext={EN=ArticleExt(id=1322941593585590468, articleId=1322941593405235395, tenantId=1146029695717560320, journalId=1322258626896822465, language=EN, title=Research progress and key technologies of hydrogen fuel cell UAVs, columnId=null, journalTitle=Journal of Beijing University of Aeronautics and Astronautics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Due to their high energy density and zero emissions, hydrogen fuel cell UAVs have become a vital means of overcoming the endurance limitations of traditional lithium-battery-powered UAVs in the context of a growing low-altitude economy and the development of green aviation. This paper provides a comprehensive review and systematic categorization of the development and key technologies of hydrogen-fuel cell UAVs, along with a reasonable outlook on their future evolution, to serve as a valuable reference for related research. In particular, the paper starts with a summary of the scientific advancements and developmental history of hydrogen-powered aircraft, the inherent benefits of hydrogen fuel cell powertrain systems, and the state of the art in hydrogen fuel cell unmanned aerial vehicles. Subsequently, a systematic analysis is conducted on the core technologies involved in hydrogen fuel cell UAVs, including hydrogen fuel cell technology, multi-source hybrid energy systems, airborne hydrogen storage technology, energy management strategies, and thermal management strategies. Lastly, a summary of the study’s significant findings is provided, and future research directions are indicated by matching the state of these important technologies' research with the real-world difficulties they face.

, authors=Weiqiang XU1, 2, *, Bingxin ZHANG2, He ZHU1, Li CHEN3, authorsList=Weiqiang XU, Bingxin ZHANG, He ZHU, Li CHEN, authorCompany=null, correspAuthors=Weiqiang XU, authorNote=null, correspAuthorsNote=
E-mail:
, copyrightStatement=Copyright © 2026 Journal of Beijing University of Aeronautics and Astronautics. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322941597477904601, articleId=1322941593405235395, tenantId=1146029695717560320, journalId=1322258626896822465, language=CN, title=氢燃料电池无人机研究进展与关键技术, columnId=null, journalTitle=北京航空航天大学学报, columnName=, runingTitle=null, highlight=null, articleAbstract=

在低空经济崛起与绿色航空发展的背景下,氢燃料电池混合动力无人机凭借高能量密度和零排放等优势,成为突破传统锂电无人机续航瓶颈的关键路径。基于此,对氢动力无人机的发展及其涉及的关键技术进行总结和梳理,并对氢燃料电池混合动力无人机未来的发展进行合理展望,旨在为相关研究提供参考。对氢动力航空器的发展历程和技术演替、氢燃料电池动力系统的优势以及氢燃料电池无人机的发展现状进行概述;对氢燃料电池混合动力无人机涉及的氢燃料电池技术、多源混合能源系统技术、机载储氢技术、能量管理策略以及热管理策略进行系统梳理;结合氢能无人机各关键技术的研究现状及其实际应用中所面临的问题,对未来的发展方向进行合理展望。

, authors=徐伟强1, 2, *, 张炳鑫2, 祝赫1, 陈黎3, authorsList=徐伟强, 张炳鑫, 祝赫, 陈黎, authorCompany=null, correspAuthors=徐伟强, authorNote=null, correspAuthorsNote=
E-mail:
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罐体类型材料组成最大内压/MPa质量储氢密度/%
Ⅰ金属储瓶<201
Ⅱ纤维复合材料包覆的金属瓶<302
Ⅲ带金属衬垫的复合瓶35~703.9~5
Ⅳ带有聚合物内衬的复合瓶705
Ⅴ无内衬复合瓶>707.5
), ArticleFig(id=1322941603584811291, tenantId=1146029695717560320, journalId=1322258626896822465, articleId=1322941593405235395, language=CN, label=表1, caption=

5种高压储氢瓶的性能对比[61]

, figureFileSmall=null, figureFileBig=null, tableContent=
罐体类型材料组成最大内压/MPa质量储氢密度/%
Ⅰ金属储瓶<201
Ⅱ纤维复合材料包覆的金属瓶<302
Ⅲ带金属衬垫的复合瓶35~703.9~5
Ⅳ带有聚合物内衬的复合瓶705
Ⅴ无内衬复合瓶>707.5
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评价维度常用具体评价指标
氢耗瞬时氢气消耗率/任务周期总氢耗
能源利用效率燃料电池系统效率
动态响应特性功率跟踪精度、响应延时、电压波动范围
算法实时性与计算开销单步计算时间、训练时间/
收敛速度(学习类策略)
鲁棒性与适应性扰动及工况变化下主要性能指标的变化情况
), ArticleFig(id=1322941603760972061, tenantId=1146029695717560320, journalId=1322258626896822465, articleId=1322941593405235395, language=CN, label=表2, caption=

能量管理策略常见评价指标

, figureFileSmall=null, figureFileBig=null, tableContent=
评价维度常用具体评价指标
氢耗瞬时氢气消耗率/任务周期总氢耗
能源利用效率燃料电池系统效率
动态响应特性功率跟踪精度、响应延时、电压波动范围
算法实时性与计算开销单步计算时间、训练时间/
收敛速度(学习类策略)
鲁棒性与适应性扰动及工况变化下主要性能指标的变化情况
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氢燃料电池无人机研究进展与关键技术
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徐伟强 1, 2, * , 张炳鑫 2 , 祝赫 1 , 陈黎 3
北京航空航天大学学报 | 2026,52(10): 3563-3579
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北京航空航天大学学报 | 2026 , 52 (10) : 3563 -3579
氢燃料电池无人机研究进展与关键技术
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徐伟强1, 2, * , 张炳鑫2, 祝赫1, 陈黎3
作者信息
  • 1天目山实验室,杭州 311115
  • 2北京航空航天大学 航空科学与工程学院,北京 100191
  • 3西安交通大学 能源与动力工程学院,西安 710049
通讯作者:
Research progress and key technologies of hydrogen fuel cell UAVs
Weiqiang XU1, 2, * , Bingxin ZHANG2, He ZHU1, Li CHEN3
Affiliations
  • 1Tianmushan Laboratory,Hangzhou 311115,China
  • 2School of Aeronautic Science and Engineering,Beihang University,Beijing 100191,China
  • 3School of Energy and Power Engineering,Xi’an Jiaotong University,Xi’an 710049,China
  • Corresponding Author:
出版时间: 2026-10-31 doi: 10.13700/j.bh.1001-5965.2026.0440
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在低空经济崛起与绿色航空发展的背景下,氢燃料电池混合动力无人机凭借高能量密度和零排放等优势,成为突破传统锂电无人机续航瓶颈的关键路径。基于此,对氢动力无人机的发展及其涉及的关键技术进行总结和梳理,并对氢燃料电池混合动力无人机未来的发展进行合理展望,旨在为相关研究提供参考。对氢动力航空器的发展历程和技术演替、氢燃料电池动力系统的优势以及氢燃料电池无人机的发展现状进行概述;对氢燃料电池混合动力无人机涉及的氢燃料电池技术、多源混合能源系统技术、机载储氢技术、能量管理策略以及热管理策略进行系统梳理;结合氢能无人机各关键技术的研究现状及其实际应用中所面临的问题,对未来的发展方向进行合理展望。

无人机  /  氢燃料电池  /  混合动力  /  机载储氢  /  能量管理  /  热管理

Due to their high energy density and zero emissions, hydrogen fuel cell UAVs have become a vital means of overcoming the endurance limitations of traditional lithium-battery-powered UAVs in the context of a growing low-altitude economy and the development of green aviation. This paper provides a comprehensive review and systematic categorization of the development and key technologies of hydrogen-fuel cell UAVs, along with a reasonable outlook on their future evolution, to serve as a valuable reference for related research. In particular, the paper starts with a summary of the scientific advancements and developmental history of hydrogen-powered aircraft, the inherent benefits of hydrogen fuel cell powertrain systems, and the state of the art in hydrogen fuel cell unmanned aerial vehicles. Subsequently, a systematic analysis is conducted on the core technologies involved in hydrogen fuel cell UAVs, including hydrogen fuel cell technology, multi-source hybrid energy systems, airborne hydrogen storage technology, energy management strategies, and thermal management strategies. Lastly, a summary of the study’s significant findings is provided, and future research directions are indicated by matching the state of these important technologies' research with the real-world difficulties they face.

unmanned aerial vehicles  /  hydrogen fuel cells  /  hybrid power  /  on-board hydrogen storage  /  energy management  /  thermal management
徐伟强, 张炳鑫, 祝赫, 陈黎. 氢燃料电池无人机研究进展与关键技术. 北京航空航天大学学报, 2026 , 52 (10) : 3563 -3579 . DOI: 10.13700/j.bh.1001-5965.2026.0440
Weiqiang XU, Bingxin ZHANG, He ZHU, Li CHEN. Research progress and key technologies of hydrogen fuel cell UAVs[J]. Journal of Beijing University of Aeronautics and Astronautics, 2026 , 52 (10) : 3563 -3579 . DOI: 10.13700/j.bh.1001-5965.2026.0440
随着我国“十四五”规划的圆满收官及“十五五”规划的全面开启,低空经济已经成为我国发展的重点关注领域。《中华人民共和国国民经济和社会发展第十五个五年规划纲要》明确将“推进低空经济健康有序发展”“加快大载重固定翼无人机、长航时垂直起降航空器等新型低空装备研制”列为重要任务。这表明,以固定翼无人机、旋翼无人机等为代表的飞行平台,将成为低空经济的核心载体。这些无人机平台凭借其高机动性、优秀的任务适应性以及多元化的起降能力,在物流配送、应急救援、精准农业、线路巡检、航拍乃至军事等领域都有着广泛的应用[1-8]。然而,日益复杂的任务场景对无人机的作业半径、续航时间、载荷能力以及全天候工作能力提出了越来越高的要求。传统以化石燃料为主的动力系统虽然能提供较长的航时,但其高噪声、高排放特性给环境带来的负面影响也难以忽视[9]。为响应我国“双碳”目标及绿色航空装备发展愿景,转向电能驱动是最佳选择。
目前,主流的电能动力系统往往以锂电池为能量载体,尽管其具有零排放、低噪声以及高动态响应等优势,但受限于较低的能量密度,严重制约了无人机的续航时间与任务效能,无法满足当前作业环境对无人机提出的要求,上述不足在功耗敏感的电动旋翼平台上表现得尤为显著。因此,寻找一种兼具高能量密度与环境友好特性的新型电能载体,已成为突破无人机续航瓶颈的关键。在此背景下,氢能凭借其高能量密度与零排放特质,成为无人机动力系统转型的理想选择。
氢能作为一种零碳排放且来源广泛的清洁能源,契合世界各国的减碳、零碳政策,是全球能源转型的重要方向,将成为人类用来代替化石燃料的最佳选择之一。根据国际能源署(International Energy Agency, IEA)的数据,预计到2030年,世界氢能源生产能力将达到140~190 GW[10],这将为发展氢动力无人机提供充足的能源供应。最重要的是,氢的质量能量密度高达120 MJ/kg,使用氢能源设计的燃料电池混合动力系统能量密度为250~540 Wh/kg[11],与锂电池(130~200 Wh/kg)相比,氢能源的引入能够提供至少2倍于相同质量的锂电池所能提供的续航时间[12]。这一特性为破解电动无人机续航难题提供了极具潜力的解决方案。另外,氢燃料电池在具备高能量密度的同时实现了真正的零排放,其反应过程中唯一的产物是水,对环境完全无害。
同时,近年来我国对发展氢能航空器的政策支持也在不断增加,在国家大力发展新质生产力、推进“双碳”目标与低空经济战略的时代背景下,氢能与无人机产业的深度融合正成为科技创新的重要前沿。2020年6月发布的《无人机用氢燃料电池发电系统》(GB/T 38954—2020),统一了无人机氢燃料电池相关的要求[13];2022年3月发布的《氢能产业发展中长期规划(2021—2035年)》,要求积极探索燃料电池在船舶、航空器等领域的应用,推动大型氢能航空器研发[14];2023年10月发布的《绿色航空制造业发展纲要(2023—2035年)》,明确布局氢能航空关键技术研发及商业化运营模式探索[15];2026年3月,工业和信息化部、财政部、国家发展改革委联合印发《工业和信息化部 财政部 国家发展改革委关于开展氢能综合应用试点工作的通知》,明确将“航空器”列为氢能六大创新应用场景之一,单个试点城市群4年最高可获16亿元奖励资金,氢能无人机单架最高可获8万元专项补贴[16]。这标志着氢能无人机已从技术验证阶段正式迈入国家战略支持的规模化应用新阶段。这些都为氢燃料电池无人机的技术研发与应用提供了坚实的政策支持。
在此背景下,本文立足于“十五五”期间对绿色、长航时航空装备的研制需求以及氢能航空创新应用的政策导向,旨在对氢燃料电池无人机的发展现状及其涉及的氢燃料电池动力系统技术、机载储氢技术、能量管理与热管理策略等进行系统性的梳理与总结,以期为相关研究提供有效参考。
随着我国“双碳”目标的推进以及低空经济的兴起,氢动力航空技术经历了从大型固定翼验证机到各型无人机、从直接燃烧供能到电化学供能转化的深刻演进。
人类对氢动力飞行器的探索始于对高能量密度燃料的渴求。最早的将氢能源应用于航空领域的方案可以追溯到20世纪前期,德国Heinkel公司将气态氢用于其设计的涡轮喷气发动机作为燃料进行了相关测试[17]。虽然此次探索中氢能源并没有推动航空器飞向天空,却为后来的探索打开了思路。1988年,苏联成功试飞了全球首架以液氢为燃料的验证机Tu-155,如图1所示。虽然其采用的是氢内燃机动力系统,但它首次在工程层面证明了机载液氢储存与输送的可行性[18]。
进入21世纪,质子交换膜燃料电池(proton exchange membrane fuel cell,PEMFC)技术的成熟为航空动力系统的小型化、静音化提供了新路径。2008年,波音的燃料电池演示机采用氢燃料电池作为飞机的动力系统完成了巡航飞行[18],标志着氢能动力正式进入以燃料电池为主的新阶段。到这一阶段,对于氢动力航空器的研究仍然集中于固定翼平台,科研人员进行了大量的尝试来验证氢燃料电池作为航空器动力系统的可行性。
近年来,随着无人机产业与低空经济的爆发,氢燃料电池技术自然地向无人机领域迁移,并衍生出2条清晰的应用脉络:①在固定翼无人机上,科研人员依托其高升阻比的天然优势,利用高能量密度的氢燃料电池系统实现更长时间的持续监测、遥感、侦察等任务,极大地拓展了无人机的任务半径;②针对城市空中交通以及物流配送等场景,氢动力系统正成为多旋翼及电动垂直起降飞行器(electric vertical take-off and landing, eVTOL)破解锂电“续航瓶颈”的关键。面对垂直起降与悬停带来的高功耗需求,氢燃料电池凭借高能量密度与快速补能优势,显著提升了这类飞行平台的作业效能。目前,氢燃料电池系统已在固定翼长航时无人机、多旋翼无人机及新型eVTOL等多类飞行平台上展开了广泛的应用与探索。
在工业级无人机领域,作业效能直接受限于动力系统的性能。传统的化石燃料动力虽然能量密度高,但其高噪声、高振动以及碳排放问题,既不符合全球绿色环保的发展趋势,也限制了无人机在如自然保护区、城市静音区等环境敏感区域的作业能力。相比之下,电动无人机具有低噪声、低振动和运行过程零排放等特点,同时能够简化机械结构并降低维护成本,已成为当前无人机动力系统的重要发展方向。作为2类典型的电动动力方案,锂电池与氢燃料电池在应用中具有不同的性能特点,下面从5个方面进行对比分析:
1) 氢燃料电池动力系统的能量密度可达到传统锂电池的2倍以上,可显著延长无人机续航时间,扩大任务半径,使其更好地应对现代复杂的任务环境。
2) 氢燃料电池在产生电能的同时也伴随热量释放,这有利于维持动力系统工作温度,减缓低温环境对动力系统的不利影响,使得氢燃料电池在低温环境下也具有较好的工作适应性。
3) 相较于循环寿命有限、容量衰减显著的传统高能量密度锂电池,氢燃料电池系统在耐久性与长期运行稳定性方面具备显著优势。随着累计飞行时间增加,锂电池循环衰减及更换所带来的折旧成本逐步累积,而氢燃料电池较长的使用寿命有利于降低单位飞行时间的成本,使其长期综合运营成本低于纯电系统。
4) 氢燃料电池动力系统可以在数分钟内实现氢燃料的快速充装,相较于锂电池充电能够显著缩短补能时间,减少连续作业过程中的停机时间,从而提高设备利用率和作业效率。
5) 氢燃料电池动力系统保留了传统锂电池的清洁、低噪声、无碳排放的优点,保证了无人机的可作业范围,同时其工作过程无机械振动的特性也降低了很多精密机载设备搭载使用的难度。
综上,氢燃料电池无人机在续航能力、低温适应性、耐久性、快速补能以及长期运行稳定性与经济性等方面都具有明显优势。
目前,主流的氢动力无人机从构型上主要分为固定翼、多旋翼、复合翼无人机3类。其中,复合翼又可以视为固定翼的一个特殊子类。
固定翼无人机依靠机翼产生的气动升力维持飞行,其长航时特性与氢燃料电池的高能量密度特性具有极高的物理契合度。由于其巡航阶段仅需维持较低功率运行即可维持升力,该类构型能将氢能的化学能高效转化为推进功,从而实现超长时续航与更大的作业半径。凭借在广域覆盖与超长航时方面的绝对优势,固定翼无人机非常契合对载荷与续航能力要求较高且对起降场地限制相对宽松的任务场景,如大纵深区域的边境巡防、大面积海域的海事监察与搜救以及长距离油气管道与特高压电网的巡检等。
多旋翼无人机常通过多个旋翼产生的向下推力实现垂直起降与悬停,具备极高的机动灵活性与定点悬停精度。引入氢动力系统后,有效缓解了传统锂电多旋翼“载重小、续航短”的痛点,将作业时间由数十分钟提升至数小时量级。凭借垂直起降以及操作灵活的特性,多旋翼无人机非常适用于城市狭窄街巷、山区复杂地形等狭小的作业空间,具体应用如低空拍摄、城市物流配送、城市应急救援等。
复合翼融合了多旋翼的垂直起降能力与固定翼的高效巡航能力,通常采用“多旋翼+固定翼”的复合气动布局,这使其可满足复杂地形起降需求和长距离高效巡航,拓宽了使用场景,但是技术复杂度高、成本相对昂贵、维护难度较大。复合翼构型能够适用于起降条件受限但作业半径较大的场景,如海岛间的物流运输与物资投送(无需平整跑道)、山区与丛林的地理测绘与资源勘探及大面积林区的防火巡查等。
下面本文按照构型作为分类标准,简要介绍氢动力无人机的代表性机型。
固定翼无人机凭借其长航时、大载荷的优势,是氢能源无人机发展的重点平台,在军民2个领域中都发挥着相当重要的作用[20]。多年来,国内外研究人员在氢动力固定翼无人机方向进行了大量的探索和实践。
美国的Ion Tiger无人机搭载氢燃料电池动力实现了长时间续航,2009年,其首次试飞,在携带约2.27 kg有效载荷的情况下连续飞行26 h,创下了燃料电池动力飞机的非官方续航纪录[21-22]。2012年,同济大学与上海奥科赛飞机有限公司共同研发了“飞跃一号”氢动力固定翼无人机,该飞机翼展5 m,起飞重量20 kg,有效载荷1 kg,巡航速度30 km/h,续航时间2 h,使用一个1 kW的PEMFC作为动力[23]。2014年,武汉众宇动力系统科技有限公司研发出“天行者”燃料电池无人机,首飞实现了12 h的不间断飞行[24]。2025年4月20日,中国民用航空飞行学院多个二级学院团队联合研发的FC-30型氢燃料电池全工况增程式复合翼无人机,在成都国家级民用无人驾驶航空试验基地成功完成了首次全流程飞行测试,该机型的最长续航时间可达4 h,具备多次起降、长时间悬停及多次悬停的功能,成功实现了固定翼模态长航程与多旋翼模态长航时的兼顾[25]。哈尔滨工业大学重庆研究院研发的氢燃料电池复合翼无人机“青鸥-30B”搭载35 MPa高压储氢罐,续航时间长达12 h,最远可飞行900 km,且凭借其自主研发的氢燃料电池系统,获得了高达60%的能量转化效率。目前,“青鸥-30B”已广泛应用于电网巡检、森林巡检、边防巡检等场景,并成功在海拔3800 m以上的高原完成严苛测试[26]。部分典型机型如图2所示。
近年来,旋翼无人机在生活中的应用愈来愈广泛,尤其是多旋翼无人机,其凭借起降方便、灵活机动等优势,深受各个领域的青睐。国内外都开展了大量研究,并取得了许多成果,下面介绍其中的一些氢动力旋翼机成果。
我国在氢动力旋翼机领域起步较晚但发展势头迅猛。2023年,由浙江氢航科技有限公司设计的氢旋4号无人机顺利完成了−22 ℃下的低温巡检工作[28]。2024年8月,北京航空航天大学天目山实验室研发的“天目山一号”百公里级氢动力长航程多旋翼无人机首飞成功[23]。随着关键技术不断突破,“天目山一号”于2025年11月16日在北京航空航天大学杭州国际校园上空成功完成了不间断飞行188.605 km,总续航4 h17 min55 s的飞行挑战,创造了全新的世界纪录,并得到了吉尼斯世界纪录的官方认证[29]。同时,“天目山一号”还在−40 ℃的根河市进行了极寒环境下的飞行测试,证明了其良好的环境适应能力[30]。由陕西同尘和光低温科技有限公司和哈尔滨工业大学重庆研究院共同设计的“青鹞-10”氢动力多旋翼无人机在2025年完成了液氢能源的首次试飞,实现了超过3.5 h的连续飞行[31]。2026年,由氢鹏科技(浙江)有限公司设计的XC02与XC04这2款氢动力无人机在我国黑龙江省漠河市近−40 ℃的极寒环境中,圆满完成飞行测试,均实现了超150 min的连续稳定飞行[32]。国内氢动力旋翼无人机代表机型如图3所示。
国际上,各国对旋翼无人机技术的发展都十分重视。美国Flight-Wave Aerospace System公司研制的Jupiter-H2四旋翼无人机携带3 L压缩气态氢作为燃料,且在飞行过程中完全由燃料电池供电[23]。另外,美国Alaka'i Technologies公司推出了一款名为Skai的氢动力eVTOL,其采用六转子分布式动力设计,旨在解决未来城市空中的大载荷载人通勤任务[33]。韩国在氢动力无人机领域发展也十分迅速。韩国斗山集团旗下的斗山创新利用自研的氢燃料电池电源模块,设计出多款成熟的旋翼无人机平台,其中DT30N在负载后有效续航仍可达到2 h以上,且中间无需更换电池,大大提高了作业效率,尤其是需要低速精密测绘的领域[34]。
燃料电池常基于电化学原理将燃料中的化学能直接转化为电能,而不需要通过燃烧来获取能量,这使得此类装置在运行时噪声、振动都很微弱,且具有更高的效率。常用的燃料电池根据电解质种类不同可以分为以下几种:PEMFC、碱性燃料电池(alkaline fuel cell, AFC)、磷酸燃料电池(phosphoric acid fuel cell, PAFC)、熔融碳酸盐燃料电池(molten carbonate fuel cell, MCFC)、固体氧化物燃料电池(solid oxide fuel cell, SOFC)等。其中,相较于其他燃料电池而言,PEMFC具有质量轻、功率密度高、工作温度低、启动速度快等优点,是目前氢动力无人机中应用最为广泛的燃料电池。经典的PEMFC结构以及工作原理如图4所示,其由阴极和阳极两侧的流道、气体扩散层、催化层以及质子交换膜组成[35]。
在工作时,PEMFC中氢气经过阳极流道扩散至气体扩散层,最后进入催化层,在催化剂的作用下失去电子,并将质子通过质子交换膜传递至阴极侧。氧气经过阴极流道扩散至气体扩散层,最后进入催化层,在催化剂的影响下,与通过质子交换膜的质子以及来自外部电路的电子结合生成水,从而在阴极和阳极之间形成持续的电流以驱动工作设备。
通常情况下,PEMFC的阴极和阳极流道被设计在同一块导电板的正反两面,故而常称该导电板为双极板[36]。另外,气体扩散层、催化层和质子交换膜三者构成了电池的膜电极组件(membrane electrode assembly, MEA)[37]。在实际工程应用中,通过“双极板—膜电极—双极板”的交替堆叠,可将多个单体电池串联形成电池堆,从而显著提升其整体输出电压与功率密度。然而,这也使得传统的石墨双极板在电池系统总重中占到了相当大的比例。
为了更加契合航空领域轻量化与高功重比的要求,双极板材料和结构的优化已成为氢动力无人机燃料电池的重要研究方向之一。近年来,金属双极板凭借其在电堆轻量化方面的优势受到广泛关注。研究表明,同等条件下,与石墨双极板PEMFC电池堆相比,金属双极板堆输出电压高4%,质量减轻31%[38]。但是,金属双极板在运行中也面临着电化学腐蚀、金属离子析出等问题,为此高抗腐蚀、低接触电阻的表面涂层工艺成为金属双极板工程应用的关键技术瓶颈。目前,前沿的这一类型产品也有尝试使用钛基双极板,其比传统的不锈钢极板更轻。另外,由树脂基体掺杂石墨粉、碳纳米管等导电填料构成的复合材料双极板凭借轻量化、优异的抗震性与高韧性,也成为重要的发展方向,但其目前仍存在导电性和厚度之间的博弈,且内阻相较于金属双极板偏高,使得系统功率密度受限。
除了双极板材料与结构的优化,氢燃料电池热管理也是氢动力无人机亟需突破的核心技术之一,其直接影响PEMFC的性能与寿命。由于热力学与电化学不可逆损失的限制,PEMFC在将氢能转化为电能的过程中不可避免地会产生大量热量,(PEMFC的典型能量流图如图5所示[39]),如果不能及时将这部分能量排出,电池温度将持续升高,加速膜内水分蒸发,影响膜电极水合,导致膜干,从而使膜电阻率急剧上升、欧姆损耗增大,进而引发电池输出电压下降、功率衰减;严重时还会造成膜局部热点、裂纹甚至穿孔,导致反应气体交叉渗透,造成不可逆的性能恶化与寿命缩短[40]。为此,冷却系统对于燃料电池而言就显得尤为重要。本节从氢燃料电池技术的角度,对热管理进行简要描述,详细内容在热管理章节中详细展开。
总体上,PEMFC可分为液冷型和空冷型[41]2种。其中,与液冷型PEMFC相比,空冷型PEMFC通过空气吹扫为电堆降温,无需复杂的辅助系统,从而使整个系统更加简洁、轻便。根据结构的不同,空冷型PEMFC又可进一步分为3类:面冷型、边缘冷却型[42-43]和开放阴极型[44]。其中,开放阴极型直接将阴极流道暴露在大气中,使得风扇在抽吸空气为电堆降温的同时,也为电池提供了阴极反应所需的氧气。开放阴极PEMFC结构简单、功率密度高、噪声低,是目前3种空冷型PEMFC中应用最广泛、最成熟的类型。典型的开放阴极空冷燃料电池动力系统如图6所示[45]。
然而,也正是因为直接将阴极流道暴露在外界环境中,开放阴极型氢燃料电池的环境适应能力受到限制。而对于工业级、军工级、全天候作业的氢动力无人机而言,常常要面临复杂多变的任务环境,如空气湿度的变化、海岛的盐雾、沙尘天气的固体微粒及工业区大气中的SOx和NOx等,这些都会对电池的性能造成损伤,最终导致电池寿命降低[46-47]。因此,如何提升燃料电池对复杂恶劣环境的适应能力成为亟需解决的难题。近年来,阴极闭合式电堆通过主动供气和可控热管理,为提升系统的环境适应性与寿命提供了新的技术路径。近期,由中国科学院大连化学物理研究所研发的阴极闭合式风冷电堆比功率达1970 W/kg,面功率密度达1.15 W/cm2,具备高功率密度、强环境适应性、长寿命等优势,经鉴定总体技术达到国际领先水平[48]。
同时,氢动力无人机日益拓展的作业环境也使得其不可避免地面临严寒天气或高海拔地区的极低环境温度,而冰点以下生成水会冻结堵塞孔隙与流道,导致电池启动失败或膜电极损伤。因此,低温冷启动技术也成为氢动力无人机燃料电池亟需突破的核心技术之一。下面对目前氢动力无人机上PEMFC的一些冷启动方案进行简要介绍。
首先,使用外部设备辅助加热的方案,典型如空气预热、端板与绝缘板加热。前者利用外部加热设备预热进入PEMFC的空气,从而提升电堆温度。加热空气能快速提高MEA的温度,有利于促发电化学反应[49]。然而,在无人机高海拔地区作业时,由于空气较为稀薄、热传导系数降低,该方法的能量利用效率会受到较大限制。后者则直接对PEMFC电堆的端板和绝缘板进行加热,从而使系统整体温度上升[49]。另外,通过增大启动电流也能实现系统的电化学自加热,但该方案需要对电流进行精准控制以免损坏系统中的元件[50]。相比之下,近年兴起的交流激励(alternating current, AC)阻抗加热技术通过内部焦耳热升温,加热更均匀且不易损伤组件[51]。根据PEMFC电堆内各组件之间的热性能差异,通过分阶段加热控制,优先加热热容较小的组件(如MEA)以促发反应,再逐步加热热容较大的组件(如端板),能够在降低启动能耗的同时实现快速启动[52]。值得注意的是,停机后吹扫对冷启动也非常重要。该方法在系统关机后,利用干燥空气或氢气大流量吹扫电堆内部,将残余水分彻底排出,从根本上消除结冰隐患。
总体而言,面向氢动力无人机轻量化、高功重比以及复杂环境作业的发展需求,氢燃料电池仍存在若干亟待突破的关键技术问题。首先,需要进一步优化双极板材料与结构,在实现轻量化的同时兼顾导电性与耐腐蚀性;其次,需要提升燃料电池的热管理能力,以保证电堆在高功率密度运行条件下维持适宜的工作温度与稳定性能;同时,针对复杂恶劣的工作环境,需进一步增强燃料电池的环境适应能力;此外,面向严寒、高海拔等低温作业场景,快速、可靠的冷启动技术同样需要进一步研究。未来,如何在轻量化、高功率密度、环境适应性与运行可靠性之间实现协同优化,将是推动氢燃料电池进一步满足无人机工程应用需求的重要研究方向。
氢燃料电池动力固然有着众多优点,但当其应用于对瞬时功率要求较高的任务[53]时性能往往受限。这种局限性在不同机型上表现各异:固定翼无人机在起飞爬升阶段需要极大的峰值功率,而进入巡航阶段后需求则显著降低;多旋翼无人机则在垂直起降、紧急规避或频繁的姿态调整中对动力系统提出较大的瞬时功率需求。综上所述,氢燃料电池更加适合长航时巡航这种需要长时间放电的任务,而不适合有瞬时大功率需求的任务场景。由此可见,独立的燃料电池动力系统难以兼顾现代高性能无人机严苛的双重要求。因此,构建多源混合能源系统(hybrid energy system, HES)已经成为解决氢燃料电池[54-55]缺点的有效技术路线。
氢燃料电池无人机的多源混合能源系统通常将氢燃料电池和一个或多个辅助电源相结合,其核心优势在于辅助电源可以提供峰值功率,进而在一定程度上将氢燃料电池与动态负载解耦,使得燃料电池能够在更稳定、更高效的输出范围内持续运行,有利于提高系统整体能量利用率和可靠性。从动力系统架构的角度来看,目前氢燃料电池无人机的主流配置是串联混合动力架构,如图7所示[56]。
在这种架构中,燃料电池系统与辅助电源通过电耦合方式连接到公共高压直流母线上。其中,燃料电池充当机载动力单元,提供主要能量;能量管理系统(energy management system, EMS)作为核心控制器,通过DC/DC转换器调节各能源的功率流向。电子调速器(electronic speed controller, ESC)直接从这一稳定的直流母线获取电能,并调制电流以驱动无刷电机和螺旋桨。这种配置实现了机械推进与电化学发电的解耦,使得燃料电池无论螺旋桨转速如何波动,都能在相对稳定的工况点运行。
混合能源系统的性能直接取决于所选的辅助电源类型。目前,最常见的2种类型是锂电池和超级电容器。近年来,传统液态锂电池在功率与能量密度上已逼近瓶颈。为了突破性能限制,固态锂电池逐渐成为研究热点,其用固态的电解质替代了易燃的液态电解质,避免了挤压/高温时泄漏起火的可能,安全性较优,且能兼容容量更大的锂金属负极,能量密度更高,即便是作为过渡方案的半固态锂电池,能量密度也能够达到350 Wh/kg左右,目前半固态锂电池已开始走向产业化[57-58]。与此同时,传统对称型超级电容器虽具备高功率特性,却因能量密度过低(通常<10 Wh/kg)难以满足系统轻量化要求[59]。因此,兼具超级电容高功率与锂电池高能量特性的锂离子超级电容器,正成为无人机混合能源系统中的研究热点[60]。另外,也有研究在探索太阳能、氢燃料电池、锂电池三能一体的混合动力。
另外,不同构型无人机的混合能源系统配置应根据其任务功率需求进行差异化匹配。以巡航为主的固定翼无人机,可由燃料电池主要承担持续功率需求,辅助电源用于补偿短时峰值负载;多旋翼无人机则需要提高辅助电源的功率配置能力,以满足高功率和快速负载变化需求;对于复合翼无人机,可按照“燃料电池满足巡航持续功率、辅助电源补充垂直起降及过渡阶段峰值功率”的原则进行配置。
对于氢动力无人机而言,高效且具备高动态响应能力的动力系统是其应对复杂任务环境的基础;同时,足量的能源储备则是提升其连续作业能力、拓展工作半径的关键。目前,机载储氢技术主要分为三大类:高压气态储氢、低温液态储氢以及基于固体载体的固态储氢。
高压气态储氢是指将氢气压缩至高压状态并储存于高强度气瓶中,该技术的关键在于高压气瓶的结构强度和耐久性。目前,根据储氢瓶材料可以将储氢瓶分为5种类型,这5种类型氢气瓶的数据如表1所示[61]。其中,Ⅳ型瓶和处于前沿发展阶段的Ⅴ型瓶均属于复合材料储氢瓶,其在轻量化的同时具有更高的质量储氢密度。
氢动力无人机的起飞重量受电机推力的严格限制,而采用轻量化复合材料的储氢瓶则能在保证氢燃料储量不变的情况下,显著降低储氢系统的质量,从而为各无人机搭载的各种传感器或任务载荷留出更多余量。此外,为确保气瓶的耐久性,材料的抗氢脆性[62-63]和耐腐蚀性也是高压气瓶需要重点关注的问题。故而,质量效率高且无氢脆现象的Ⅳ型瓶以及未来的Ⅴ型瓶更适合用于氢能源无人机[59]。除了瓶身材质的选择外,通过提高气瓶储氢压力可在相同储氢量下减小气瓶容积与质量,这也是实现无人机储氢系统轻量化的重要途径。目前,氢动力无人机的储氢系统多采用35~45 MPa的氢气,70 MPa的Ⅳ型瓶技术在航空领域的应用尚处于探索阶段。此外,减压阀门作为高压气态储氢技术的相关部件,也对无人机轻量化做出了一定的贡献。传统工业或车载减压阀多采用不锈钢材质且结构冗余,导致体积与质量偏大,难以满足无人机严格的轻量化需求。近年来,通过引入新型材料,并结合阀体结构集成设计,无人机专用减压阀的质量得到了明显降低。
总体而言,压缩气态储氢凭借系统结构相对简单、技术成熟度较高以及标准体系较为完善等优势,已成为目前工程应用中最为成熟的储氢方式[64]。受无人机起飞重量和机载空间的限制,该技术未来的突破重点主要集中在储氢瓶轻量化和更高压力等级储氢系统的航空应用。一方面,应进一步优化储氢瓶的材料与结构,在保证强度、耐久性和安全性的同时降低气瓶质量;另一方面,还需进一步研究70 MPa级储氢技术在航空领域的适用性,从而进一步提高氢动力无人机的机载储氢能力和续航性能。
低温液态储氢技术的核心思想是:将氢气冷却至−253 ℃以下,使其转变为液氢以储存于特制的超低温容器中。与高压气态储氢技术中使用的氢气相比,液氢密度更大,可达70.8 g/L[65],这使得在相同的质量条件下其所需的储存空间更小。故而,液氢成为突破氢动力无人机续航瓶颈的关键路径。Stroman等的飞行实验表明[66],在同等能源系统质量下,液氢系统提供的飞行航时相比高压气态储氢系统提升了约85%,充分展现了其在长航时飞行任务中的潜力。
尽管该技术相较于高压气态储氢具有更高的能量密度,但在实际使用中也存在一些问题。首先,保存液氢所需的超低温环境对储罐的温度控制能力提出了严苛的要求。当储罐的低温环境出现问题而导致液氢蒸发损耗,就会显著影响无人机的工作效能。为此,在实际应用中,液氢储罐会使用主动温度控制和被动温度控制2种技术。被动温度控制常常借助绝热层实现,常见的设计方案包括喷涂泡沫绝热和多层材料绝热,其中,后者的性能相对更加可靠[61]。同时,为了满足氢动力无人机轻量化的需求,近年来部分新型储罐的设计采用了薄壁承压结构与优化的轻量化支撑结构,此外,石墨烯改性气凝胶和真空绝热板等超轻隔热材料已处于实验室阶段[59]。主动温度控制主要利用低温制冷机来实现。在具体应用中,系统通过传感器实时监测储罐内的压力与温度,据此评估热渗透强度。当热渗透加剧时,控制系统会主动调高制冷机功率进行补偿。这种机制能够确保在作业过程中,储罐内的液氢除燃料电池正常消耗之外,不会因储罐绝热材料性能衰减或环境波动而发生不必要的损耗。
另外,液氢罐的循环使用次数受限于材料老化和结构疲劳。在液氢罐循环充装和排放液氢的过程中,罐体材料受到温度变化引起的热应力影响,疲劳损伤逐渐积累,最终可能引发微裂纹和泄漏[67]。此外,在实际使用中,这类储罐每次充装时,需要进行严格的预冷与吹扫工序,这不仅增加了操作的复杂度,还可能导致部分液氢损耗。为此,最新的研究与工程实践,如中国航天科技集团有限公司第六研究院的移动式液氢加注撬及液氢加氢机,开始采用闭式加注与泵压过冷技术,如图8所示。该技术通过构建闭环加注回路,工艺流程中无需向空排放,极大地降低了加注过程的蒸发损耗,同时通过单路连接降低了操作复杂度,提升了加注效率[68-69]。
综上所述,低温液态储氢技术凭借高能量密度,成为突破氢动力无人机续航瓶颈的关键方案之一。然而,高昂的储罐制造成本与绝热系统带来的额外载荷,使其更适用于载荷能力更强的中大型无人机。此外,尽管加注工艺持续优化,但全球液氢供应链与基础设施建设尚处于起步阶段,这也限制了其大规模的商业化应用。同为液态储运,新兴的液氨路线能够通过机载氨裂解制氢供给燃料电池,并且凭借更高的体积储氢密度、更低的储运要求(常温低压),以及更优的安全性,被研判为超长航时重载无人机的长期最优/终极平衡点技术路线。
固态储氢技术是指通过物理或化学手段使氢气以固态的形式被储存起来。固态储氢依据储氢机理不同,主流方法可以分为2种:一种是氢气分子通过物理吸附作用与储氢材料结合;另一种是氢通过化学键与其他成分发生化学结合形成稳定的氢化物[70],使用时则通过热解或化学反应释放氢气以供能。相比于高压气态和低温液态储氢,固态储氢不仅展现出更高的体积储氢密度,而且在使用上更加安全。该技术的关键在于高效地实现氢气与其他材料的结合与释放。因此,固态储氢相关研究主要聚焦于储氢材料的物理化学性质[71]。
常用的物理吸附型储氢材料主要包括碳基材料、硅基材料、金属有机框架材料[72]以及其他具有高比表面积的多孔材料,氢分子通过范德瓦耳斯力与这些材料进行物理结合。但这种方式受限于材料性能和规模化制备仍处于研发阶段。
化学储氢材料主要包括配位氢化物材料和金属基合金材料。其中,最常用的是硼氢化钠。韩国科研人员开发了一种以硼氢化钠为储氢材料的无人机氢气发生器[73-74],实验数据表明,该氢气发生器的质量比能量和体积比能量分别为739.1 Wh/kg和272.8 Wh/L,且具备稳定的产氢速率。但其在投入实际应用的过程中也出现了诸多问题,一方面,在硼氢化钠体系中所使用的催化剂寿命较短,以至于每次飞行都要重新装填,这增加了使用成本,限制了其商业应用潜力,另一方面,该体系在制氢过程中产生的副产物有可能堵塞燃料电池的燃料进气口,进而影响整个电池系统的性能[75]。
与配位氢化物材料相比,低压金属储氢合金材料通过可逆吸放氢反应实现固态储氢,无需复杂的水解过程。该类材料在安全性与环境适应性方面具有优势,但普遍面临合金密度大、系统质量偏高以及对部分关键金属元素依赖较强等问题,限制了其在对载重与成本敏感的领域的进一步推广。
近年来,镁基储氢材料凭借较高的质量储氢密度与原料来源广泛的优势也受到较多关注,但其放氢温度偏高、动力学缓慢,仍有待进一步优化。除此之外,气-固氢负离子电池等新兴概念尝试将气态氢、固态储氢与电化学储能相耦合,代表了一种具有前瞻性的技术路径,目前尚处于原理验证与原型探索阶段[76]。
总体而言,固态储氢具有体积储氢密度高、安全性较好等优势,在氢动力无人机领域具有较大的应用潜力,但目前整体仍处于研究和探索阶段。该技术未来的突破重点集中在高性能储氢材料开发和储放氢性能优化。一方面,应进一步提高物理吸附材料的储氢能力并改善其规模化制备水平;另一方面,针对化学储氢和金属基储氢材料在催化剂寿命、副产物处理、系统质量、放氢温度等方面的不同限制,还需进一步优化材料组成与反应过程,从而实现氢气的高效、稳定储放,推动固态储氢技术在无人机中的实际应用。
设计的多源混合能源系统通过采用2种或多种互补的动力源,能够使得氢动力无人机更好地面对实际作业中飞行工况复杂多变、功率需求非线性波动的问题。然而,在此过程中,必须通过能量管理策略对燃料电池与辅助电源的功率输出进行实时协调、动态分配与优化控制,才能保障氢动力无人机高效、可靠、长航时运行。氢燃料电池无人机混合能源系统的能量管理逻辑框架如图9所示。
目前,主流的能量管理策略有三大类:基于规则的策略、基于优化的策略以及基于机器学习的策略。下面对这3类方法分别进行介绍。
基于规则的能量管理策略与大量的工程经验息息相关[77]。在多年的工程实践中,面对各种飞行情况的合理应对措施被总结成规则,使得无人机在实景工作环境中,能够通过查询自身烧录的规则库得到对实时情况的合理应对措施。这些经验性的总结往往会呈现为“如果……那么……”的逻辑结构。例如,“如果无人机将保持巡航飞行,那么就增大燃料电池的供电比例,同时限制辅助电源的输出。”总体而言,基于规则的能量管理策略可以分为2类:确定性规则控制和模糊逻辑控制(fuzzy logic control, FLC)。
在工程应用中,确定性规则控制凭借控制结构简单且实时性强等优点成为主要的控制方法。此类方法的核心思想是通过对实时状态变量与固定阈值的比对,实现对系统能量的瞬时分配。确定性规则控制的研究众多,如Yan等[78]利用基于确定性规则的能量管理策略,使得在相同飞行剖面下,飞行器续航时间延长16.5 min,系统总重减少302.8 g,运行成本降低41.58美元,取得了显著的性能提升。Yang等[79]利用基于状态机的能量管理策略来实现确定性规则控制,在不同的电池荷电状态(state of charge, SOC)条件下进行了多次飞行试验,结果证实,该策略优化了功率分配并增强了飞行器的动态性能。
模糊逻辑控制的核心是一套模拟人类经验的“IF-THEN”规则库,其并不直接处理各种传感器传回的精确数字,而是通过模糊化过程将复杂的系统状态(如电压、电量)转化为“高、中、低”等模糊概念,从而实现更灵活的决策。模糊逻辑控制凭借卓越的非线性处理能力和抗干扰特性,在燃料电池能量管理中得到了广泛的应用。Zhang等[80]提出了一种在线模糊逻辑控制策略,相比于被动控制以及状态机策略,设计的系统在降低氢气消耗和提高电池使用效率方面有明显提升。Shen等[81]利用模糊逻辑控制精确地将燃料电池的工作点维持在最有效的区域内,在多种标准工况下进行实验,证明了该方法的优越性。
基于优化的能量管理策略通常涉及代价函数的建立。该类策略将确定燃料电池与辅助电源之间最优功率分配的过程转化为最小化代价函数的过程。通常情况下,该代价函数代表氢气消耗量、系统运行成本或者电池降解程度。此外,为了将系统的实时状态和飞行任务的执行情况也纳入代价函数,还需要引入额外的度量指标,如燃料电池堆内部的温度变化、电力稳定性指标、燃料电池的启停循环次数等。
在实际应用中,能量管理策略常通过动态规划中的加权惩罚项或模型预测控制(model predictive control, MPC)中的实时反馈将上述指标整合到代价函数中。这使得能量管理策略能够预测组件的健康状况,并据此调整无人机飞行任务剖面。相比基于规则的方法,基于优化的策略通常更加高效,因为其利用数学优化算法定义了明确的目标函数,在电池SOC和组件功率限制等约束条件下,能够统筹兼顾系统能耗、燃料电池耐久性、辅助电源降解程度及运行成本等。
总体上,根据优化范围和应用场景的不同,基于优化的策略主要分为2类:全局优化和实时优化[82]。全局优化策略旨在已知的完整任务周期内寻求理论上的最优解,其代表性算法包括动态规划(dynamic programming, DP)和庞特里亚金最小值原理(Pontryagin’s minimum principle, PMP)[83]。这类方法通常需要预先掌握全部运行工况的信息,且计算量巨大。因此,主要用于离线分析,其计算结果往往作为理论基准,用以评估其他在线实时策略的性能及表现。实时优化则要在缺少全局信息的情况下,尽可能地去逼近全局最优解。其中,2种最核心的算法是等效耗能最小策略(equivalent consumption minimization strategy, ECMS)[84]和模型预测控制[85]。
基于优化的能量管理策略也有着广泛的应用。Bradley[86]采用动态规划方法设计了无人机的能量管理策略。戴月领等[87]则采用模型预测能源管理策略,并验证了所提模型的有效性。
近年来,人工智能相关技术飞速进步,推动了智能能量管理策略的发展。这类策略主要包括神经网络(neural network, NN)、强化学习(reinforcement learning, RL)以及深度强化学习(deep reinforcement learning, DRL)等。下面对这3类方法分别展开介绍。
基于神经网络的策略主要采用有监督的学习模型。使用大量飞行数据对模型进行训练,使其能够拟合出一种复杂的映射函数,该函数能够将实时工况特征映射为混合能源系统的功率分配指令。然而,这类能源管理策略不可避免地受到神经网络弊端的影响,即性能高度依赖于训练数据的质量和规模[88]。相比之下,强化学习的核心思想是让智能体在奖励的引导下,通过与“环境”不断地交互、试错来自主学习最优的能量管理策略。这种智能体的训练过程中不需要事先标注好的“高质量”决策数据。而深度强化学习结合了深度神经网络强大的表征能力,显著提升了智能体处理高维状态-动作空间问题的潜力。总体而言,这些智能控制策略都具备自学习与自适应能力,能更好地应对混合动力旋翼无人机等具有高度非线性和动态特性的系统能量管理问题,具有广阔的应用前景。
综上所述,图10从策略类型、代表方法、主要优势及局限性等方面,对氢燃料电池无人机常用能量管理策略进行了归纳和比较。
为客观衡量能量管理策略的优劣,需从能耗、能源利用效率、动态响应特性、算法复杂度、实时性、鲁棒性、适应性等维度建立评价体系。常见的评价指标如表2所示。
面向未来轻量化、高可靠、高效率、大载重氢动力无人机的发展需求,能量管理技术可沿以下方向发展:
1) 大系统的深度耦合。将能量管理与飞行控制、任务规划联动,根据航迹、风速、载荷预调度功率,提升全局性能。
2) 轻量化智能算法。目前的许多管理策略依然需要一定量的数据作为前处理/学习,因此未来可以聚焦以更少数据量实现等效控制精度,降低算法对数据预处理与学习资源的依赖,简化机载计算需求。
3) 多机协同的能量管理策略。面向无人机集群作业,实现机间功率分配、充加氢调度与任务协同。
4) 标准化与集成化。形成面向不同构型、不同功率等级的通用能量管理策略框架,加速工程化与产业化应用。
热管理对PEMFC的安全和工作效率至关重要。PEMFC最佳工作温度通常在80 ℃左右[89]。如果工作温度过高,会导致电池内部的质子交换膜干燥、性能下降并加速极板劣化,而温度过低,则会抑制化学反应动力学。此外,温度分布不均也会直接影响反应物分布、电流密度等,进而干扰PEMFC的整体性能。然而,受制于热力学定律,任何动力装置的能量转换效率都不可能达到100%,必然有相当数额的能量被耗散掉,以热能的形式释放。因此,对于以PEMFC为动力装置的无人机而言,高效的热管理显得尤为关键。本节以PEMFC为例,从散热技术以及温度控制策略2个方面介绍氢能无人机的热管理技术。
PEMFC常用的散热方式包括液冷和空冷2种,二者在换热效率、系统复杂性及飞行器适配性上各有优劣。
液冷系统的优势是极高的换热效率和热容量,使得其非常适用于大功率PEMFC系统。在实际运行时,液冷系统依靠在冷却管道中内循环的冷却液(如高纯度去离子水、乙二醇水混合物、丙二醇水混合物),带走电池电堆产生的热量。根据接触方式的不同,液冷可分为直接接触式(浸入式)与间接接触式。直接接触式液冷系统设计简单、热阻低,且能有效抑制热失控,但对电池模块的密封要求比较严格;间接接触式液冷系统则往往通过额外的结构设计(如冷却板)实现电堆和冷却剂之间的传热,这虽增加了系统的复杂性和热阻,但具有更大的设计空间。尽管液冷散热系统的效果显著,但其所需的泵、管道及冷却液却增加了系统的复杂性和使用成本,同时增加了系统发生泄漏的风险[89]。
与液冷散热系统相反,空冷散热系统的优势是结构简单、设计轻便,无需额外的泵或管道,这使得其更加适用于对体积和载荷敏感的任务载体[90]。空冷系统通过增大阴极空气流量或设计独立的冷却通道,利用空气的自然对流或强制对流同时实现反应供氧与电堆散热。虽然空冷的换热效率低于液冷,但对于一些中小型无人机上搭载的低功率PEMFC系统而言,空冷也能够满足电池系统的散热需求[91]。
值得一提的是,针对不同机型,空冷散热系统的应用形式也存在一些差异。在无人机高速飞行过程中(如固定翼平飞),散热系统可以利用动压将空气吸入机体内部用以冷却电堆[92]。而当无人机停放于地面、低速飞行或者空中悬停(旋翼无人机)时,则要利用额外的装置(如风扇)来吸入冷却空气。旋翼无人机由于常处于悬停或低速飞行状态,故而对强制对流(即额外装置)的依赖更强,相对的固定翼飞机则更多地利用飞行时的来流进行散热。
此外,对于散热系统而言,燃料电池双极板材料的选择和优化也对电池的热管理有很大影响。高导热率材料能够有效传导电堆内部的热量,提高散热效率并减少局部热点的形成[93]。为了满足氢动力无人机轻量化与高导热率的双重需求,具有极薄厚度和高导热率的金属双极板(如表面改性的钛板或不锈钢板)正逐步取代传统石墨双极板。
总体而言,氢燃料电池无人机散热技术需要在散热能力、系统质量及辅助功耗之间进行权衡,同时要根据不同机型和飞行工况合理选择散热方式。未来需要突破的核心技术主要集中在轻量化、高效低功散热系统的设计,要通过优化进排气布局、液冷回路以及双极板材料与结构等手段,提高电堆散热效率。
温度控制技术主要在燃料电池进入常规工作区间后发挥作用,其指的是通过实时监测电堆内部或出口的温度信号,利用特定的控制算法(如比例积分、模型预测控制、模糊逻辑等),动态调节冷却介质(空气或冷却液)的流量与流向,从而使电堆在不同负载需求和环境干扰下,维持在适宜的工作温度范围,以平衡水分管理、电化学反应速率和系统寿命的一套逻辑体系。高效的温度控制策略能够确保系统在稳态和动态负载波动下稳定运行,从而提高反应效率并延长燃料电池系统的使用寿命[94]。由于无人机在飞行过程中面临阵风干扰、爬升等高动态负载波动,且跨高度层飞行时会遭遇气压与温度的骤变,因此对温度控制策略的自适应能力和响应速度提出了极高要求。近年来,国内外学者围绕温度控制策略进行了大量探索。
Yuan等[95]提出了一种基于三维数值分析的多节点控制模型,通过有限状态机与比例积分算法协同调节冷却空气的流向与流速,实验结果显示,该方案成功将电堆内部温差控制在0.5 ℃以内,显著提高了电堆的性能。Wang等[96]提出了一种基于主动温度控制的空冷PEMFC实时功率优化策略,设计了一种改进的温度扰动观察算法,从而能够实时获取最佳参考温度,此外,其还采用基于超螺旋算法的控制器,实现了在多变环境条件下对目标温度的精确跟踪,实验结果显示,在相对较高的负载下,输出功率提升超过4%,验证了该策略的有效性。同时,近年来的温控策略研究正从单一的“温度跟踪”向“热-电-水-气”多物理场协同控制演进[97]。研究人员开始引入动态规划与机器学习算法,将电堆温度与内部膜湿度、风扇/水泵能耗进行全局耦合求解[98]。这类数据驱动的智能控制策略能够降低对精确电堆物理模型的依赖,同时可结合无人机实时飞行数据进行自适应调整。
总体而言,氢燃料电池无人机温度控制策略需要综合考虑控制精度、动态响应能力、自适应能力等。未来的研究主要集中于复杂飞行工况下的快速自适应温度控制与多变量协同控制等方面。
本文系统综述了氢燃料电池混合动力无人机的研究进展与关键技术。首先,介绍了氢能源航空器的发展历程,阐述了氢燃料电池作为无人机动力源的独特优势,以及国内外典型氢动力无人机型号。然后,对氢燃料电池混合动力无人机涉及的关键技术进行了介绍,包括燃料电池混合动力系统、机载储氢技术、能量管理策略以及热管理技术。总体而言,氢燃料电池混合动力无人机技术顺应“绿色”的时代要求、受到国家政策支持,正处于关键技术攻关与早期应用示范并行的关键时期。展望未来,氢燃料电池混合动力无人机将沿着“轻量化、高可靠性、高效率、大载重”的路径继续演进,具体体现在以下方向:
1) 核心电堆组件的迭代与轻量化。散热与载重的权衡是航空工程的永恒命题。燃料电池堆技术将从目前主流的石墨双极板向更薄、功率密度更高的金属双极板过渡,更长远的目标则是实现闭式电堆设计。
2) 混动系统的深度集成与控制联动。未来的混合动力系统将不再是独立的能量源,而是追求极高的可靠性与冗余度。一方面,需开发具备工业级稳定性的氢电混动集成方案;另一方面,必须实现动力系统与飞行控制系统的深度联动。
3) 应用场景向“重载运输”拓展。目前以“天目山一号”为代表的多旋翼巡检类飞机已在电力、管网等领域实现初步应用。下一步的重点将转向载重型飞行器,实现从数十千克到数百千克级的运载能力跨越。随之而来的是对eVTOL及支线客机等更高级别航空器的探索。
4) 控制系统的多模态智能化。未来的氢动力无人机将部署大语言模型与视觉语言模型,实现自然语言交互下达任务以及高精度视觉感知,从而大幅降低用户的操作门槛。
5) 热管理系统的多物理场协同。未来氢动力无人机热管理将融合多算法调控技术,依托多物理场耦合机制,实现工况自适应温控,抑制电池温差,适配复杂飞行环境,全面提升电堆运行稳定性与使用寿命。

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2026年第52卷第10期
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doi: 10.13700/j.bh.1001-5965.2026.0440
  • 接收时间:2026-06-29
  • 首发时间:2026-10-30
  • 出版时间:2026-10-31
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  • 收稿日期:2026-06-29
  • 录用日期:2026-08-21
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    1天目山实验室,杭州 311115
    2北京航空航天大学 航空科学与工程学院,北京 100191
    3西安交通大学 能源与动力工程学院,西安 710049

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2种不同金属材料的力学参数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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