2.1 Traditional water sampling methods

Traditional water sampling methods, such as employing divers, boats or ropes for manual data collection, present several health and safety concerns. Personnel are exposed to potential hazards, especially in polluted or challenging environments. For instance, water can harbour numerous disease-producing organisms, posing risks of infection through accidental ingestion or contact with broken skin. To mitigate contamination, the U.S. Geological Survey recommends assuming all water is polluted, wearing personal protective equipment (PPE) like rubber gloves and waders, and practising thorough personal hygiene after sampling activities [23].

Additionally, the Ohio Environmental Protection Agency advises that personal protective equipment, including eye protection and gloves, be used during sampling. They also emphasise the importance of being vigilant for environmental hazards such as insect infestations and ensuring readiness for severe weather conditions, as these factors can further compromise safety during sampling operations [24]. These traditional methods are not only labour-intensive and time-consuming but also require the physical presence of personnel at each sampling location, which can be constrained by site accessibility or weather conditions. Consequently, the associated costs can be significant, encompassing expenses for deploying personnel, boats and equipment. As sampling locations become more complex, these costs continue to rise.

2.2 Drone-based water sampling methods

Drone-based water sampling methods offer a more efficient and extensive approach by enabling remote sample collection, significantly reducing human labour. Drones equipped with water sampling devices can reach difficult-to-access or hazardous locations, providing a more comprehensive assessment of water bodies. This innovation has been widely adopted in remote sensing, relay communication, sample acquisition and close observation in harsh environments [Reference Shelare, Aglawe, Waghmare and Belkhode25–Reference Matamoros29] (Table 1).

Drones can incorporate automated systems such as autonomous navigation to reach designated sampling locations [Reference Deliparaschos, Loizou and Zolotas30, Reference Hadjiloizou, Makridis, Charalambous and Deliparaschos31]. Although the initial setup costs of drones and sampling equipment may be high, operational costs can decrease over time, especially for frequent and large-scale sampling activities. Traditional sampling methods can disturb aquatic environments and introduce contaminants, whereas drone-based water sampling minimises environmental impact by collecting samples without direct human contact with the water, thereby reducing the risk of contamination. Consequently, drone-assisted water sampling has emerged as an innovative and efficient alternative to traditional methods.

Table 1.

Comparison table between drone-based and traditional sampling missions

Table 2. Long description

A table comparing drone-based sampling and traditional sampling methods in terms of health and safety, operational cost, accessibility, and speed and efficiency. The table has four rows and four columns. The columns are labeled Drone-based sampling and Traditional sampling (boats & personnel). The rows are labeled Health & safety, Operational cost, Accessibility, and Speed & efficiency. Row 1: Health & safety, Drone-based sampling, Minimal direct human contact with contaminated water, Reduced risk of infections, Fewer hazards from harsh conditions or wildlife, Traditional sampling (boats & personnel), Direct exposure to potentially polluted water, Requires protective gear (gloves, waders), Heightened risk from environmental hazards (e.g. insects, extreme weather, toxic water sources). Row 2: Operational cost, Drone-based sampling, Higher initial investment in drone and sensor technology, Lower long-term costs (fewer personnel, minimal equipment), Traditional sampling (boats & personnel), Moderate initial investment (boat, basic gear), Higher recurring costs (fuel, boat maintenance, larger crew). Row 3: Accessibility, Drone-based sampling, Can reach remote or hard-to-access areas quickly, Less limited by terrain, Traditional sampling (boats & personnel), Dependent on navigable waterways or safe terrain for personnel, Accessibility is limited by boat size, water depth or hazardous conditions. Row 4: Speed & efficiency, Drone-based sampling, Rapid deployment and data collection, Ability to sample multiple sites in a single flight, Traditional sampling (boats & personnel), Slower process (launching boats, positioning, collecting samples), Time-consuming, especially for multiple or distant sites.

2.3 Field quality control in water sampling

Field quality control is a critical aspect of water sampling. The process of collecting and analysing water samples involves multiple stages that can influence observed results. Field quality control ensures the accuracy, reliability and representativeness of collected samples through rigorous monitoring of factors that may affect sample integrity [Reference Wilde and Radtke22].

A key field quality control practice is field rinsing, which involves rinsing the water sampling device three times to minimise contamination. Spot sampling is the most commonly used method for measuring chemical pollutant levels across all three monitoring modes. Following sample collection, extraction and instrumental analysis are performed to assess water quality [Reference Madrid and Zayas32].

Surface waters are typically sampled by directly filling a sample bottle. However, for depths beyond 0.5 meters, this approach becomes impractical, necessitating the use of specialised water samplers. These samplers are lowered while open on a rope or steel cable and can be remotely triggered to close. Alternatively, pumps may be used for sample collection. Automatic samplers offer a more comprehensive understanding of water quality variations over time and enhance data reliability.

Besides routine quality-control checks, contamination control is a critical field concern for physicochemical sampling from hybrid hydrogen–battery UAVs. Platform-specific contamination pathways include rotor-wash that resuspends sediments and surface films, direct exposure of samplers to any exhaust or lubricant residues, and cross-contamination from reusable sampling hardware. Although hydrogen fuel-cell propulsion substantially reduces combustion-derived emissions relative to hydrocarbon engines, it does not eliminate contamination risks associated with rotor disturbance, hardware contact or field handling. Therefore, contamination control must combine careful platform tactics with procedural safeguards and rigorous quality control sampling.

Two practical examples are: (1) sampler selection and protection, use closed or remotely triggered samplers (or sterile peristaltic tubing) to prevent direct exposure of the collected water to the air column during retrieval, and physically shield sampler inlets from rotor wash and any exhaust plume (for example with a simple shroud or a boom-mounted inlet); and (2) component decontamination and documentation, clean and sterilise all sampling components before fieldwork using validated methods and either replace single-use parts or apply on-site sterilisation between sites, documenting every cleaning step and retaining equipment blanks to detect any procedural contamination [Reference Aurell33, Reference Wilde34].

2.4 Review of existing water sampling devices

The overall design requirements that should be met by the water sampling device include: (i) lightweight, (ii) water sample is visible, (iii) ensure minimal leakage and (iv) can collect up to 500 mL of water.

Samplers represent the most basic act of sampling water. Over the years, various sampling mechanisms have been developed and widely adopted in general sampling applications. Some of the most popular methods have been introduced by companies and researchers, with their designs and functionalities documented in scientific articles and technical papers (Fig. 2). Notable among these are:

Van Dorn sampler: This cylindrical device, typically made from glass or other inert materials, features apertures at both ends secured by tensioned springs. During deployment, the sampler remains open, allowing water to flow through. Upon reaching the desired depth, a weighted messenger is released, triggering the closure of the lids and capturing the water sample. A significant advantage of the Van Dorn sampler is its capability to collect samples both vertically and horizontally, facilitating sampling at various depths [35].

Figure 2.

Van Dorn sampler top left, Niskin sampler top right, Kemmerer sampler bottom left, Ruttner sampler bottom right.

Niskin sampler: Constructed primarily of plastic, the Niskin sampler operates similarly to the Van Dorn. It is available in various sizes, enabling the collection of different water sample volumes. As the sampler descends vertically to the required depth, water passes through it. A weighted messenger then activates a trigger mechanism, closing the lids and securing the water sample at the predetermined depth [36].

Ruttner sampler: Commonly used for collecting water samples from various depths, the Ruttner sampler consists of an acrylic cylinder with openings at both ends, kept open by a rod running through the cylinder. As the sampler is lowered vertically, water flows through it. Upon reaching the desired depth, a variable weight is released, striking the cylinder lid and activating a mechanism that seals the cylinder, capturing the water sample. The sample is then transferred to a container via a hose attached to the sampler’s bottom [37].

Kemmerer sampler: Designed to obtain uncontaminated water samples from specific depths, the Kemmerer sampler is a cylindrical device made of stainless steel or PVC. It features lids at both ends that remain open during descent, allowing water to flow through. Upon reaching the target depth, a weighted messenger travels down the cable, triggering a spring-loaded mechanism that rapidly closes the lids, sealing the water sample [38].

In addition to these traditional samplers, upgrades have been made in integrating water sampling mechanisms with drones, enhancing efficiency and accessibility (Fig. 3). Notable examples include:

DOST-PCIEERD automatic sampling system: This sampler has been developed by the authors’ team from the College of Engineering, Mindanao State University, Iligan Institute of Technology, Philippines, and the Department of Electronics Engineering, Shibaura Institute of Technology, and presented in Ref. [Reference Lariosa39].Footnote ¹ The system features an automatic lock mechanism activated after rigorous field quality control that ensures reliable collection of water samples in various scenarios. Logistics-wise, the system has a mass of 1.318 kg and can collect up to 531.5 ml of water. In fact, this study presents an example that highlights automatic sample collection using drones.

Figure 3.

(a) DOST-PCIEERD automatic sampling system [Reference Lariosa39] (a) Credit: I. M. G. Lariosa; J. C. Pao; C. A. G. Banglos; I. P. Paradela; E. R. M. Aleluya; C. J. O. Salaan, C. N. Premachandra, Drone-Based Automatic Water Sampling System, in IEEE Access, vol. 12, pp. 35109-35124, 2024, doi:10.1109/ACCESS.2024.3372655. (CC BY-NC-ND 4.0), unmodified, (b) SwellPro-UK water sampling kit, (c) NeroSampler Series-Nero Poli, (d) NeroSampler Series-Nero Mia.

SwellPro-UK water sampling kit: Designed for use with the SplashDrone 4, this water sample collector enables quick collection of water samples in areas that may be off-limits or hazardous. The kit includes a water collector weighing 56 g, compatible with standard 350 and 550 ml plastic water bottles. It is made of aluminium and features a bottle cap finish with a diameter of 30 mm and a height of 9 mm [40].

NeroSampler Series:

• • Nero Poli: This sampler allows the collection of up to four separate samples in a single deployment. It includes a built-in thermometer for live temperature sensing and operates at a sampling speed of approximately 1 litre per minute. The device is drone-agnostic with simple modifications and is designed and assembled in Australia [41].

• • Nero Mia: A single-bottle payload capable of sampling up to 2 litres using a peristaltic pump system. The Nero Mia has been upgraded to secure a full 2-litre water sample in a single sortie, with a streamlined design that improves aerial manoeuvrability. It operates at a sampling speed of approximately 2 litres per minute. Like the Nero Poli, it is designed and assembled in Australia [42] (Table 2).

2.5 Physicochemical analysis tools

Integrating physicochemical analysis tools into drones enhances their efficiency in conducting in situ water quality assessments. Equipped with advanced sensors, drones can collect real-time data across vast and hard-to-reach water bodies. Some of the basic parameters usually examined are listed as follows:

Table 2.

Drone sampling mechanisms

Table 1. Long description

A table comparing drone sampling mechanisms by various companies. The table has 8 rows and 5 columns. The columns are labeled A/A, Company, Product, Sample, Sampling type, and Mass (kg). Row 1: A/A, 1; Company, SwellPro-UK; Product, Water Sampling Kit; Sample, 350 ml & 550 ml; Sampling type, Static; Mass (kg), 0.5. Row 2: A/A, 2; Company, NeroSampler; Product, Nero Poli; Sample, Flow rate: 1 L/min; Sampling type, Continuous flow; Mass (kg), 2.7. Row 3: A/A, 3; Company, NeroSampler; Product, Nero Mia; Sample, Flow rate: 2 L/min; Sampling type, Continuous flow; Mass (kg), 3.5. Row 4: A/A, 4; Company, DOST-PCIEERD; Product, Automatic Sampling System; Sample, 531.5 ml; Sampling type, Static; Mass (kg), 1.318. Row 5: A/A, 5; Company, KC Denmark; Product, Van Dorn; Sample, 2-5 L; Sampling type, Static; Mass (kg), 7.2. Row 6: A/A, 6; Company, Aquatic BioTechnology S.L.; Product, Niskin bottle NK; Sample, 1.7-10 L; Sampling type, Static; Mass (kg), 2.6-5.7. Row 7: A/A, 7; Company, KC Denmark; Product, Ruttner; Sample, 1-5 L; Sampling type, Static; Mass (kg), 1.35-7.5. Row 8: A/A, 8; Company, Cole-Parmer; Product, Kemmerer; Sample, 0.4-2.2 L; Sampling type, Static; Mass (kg), 1-7.

Dissolved oxygen (DO) sensors: These sensors measure the concentration of oxygen dissolved in water, a critical parameter for assessing aquatic ecosystem health. Optical DO sensors, known for their accuracy and low maintenance, are suitable for drone integration due to their compact size and rapid response time [Reference Qadir, Mumtaz, Manzoor, Saleem, Khan and Charlesworth43].

Conductivity sensors: Conductivity sensors assess the water’s ability to conduct electrical current, which correlates with ion concentration and salinity levels. These sensors are essential for detecting salinity changes and pollution levels. Their relatively small size and durability make them ideal for drone applications [Reference Qadir, Mumtaz, Manzoor, Saleem, Khan and Charlesworth43].

pH sensors: pH sensors determine the acidity or alkalinity of water, an important factor influencing chemical solubility and biological processes. Miniaturised pH sensors can be integrated into drones to provide immediate readings, facilitating rapid assessment of environmental conditions. Studies have demonstrated the use of drones equipped with pH sensors for in-situ water quality measurements [44].

Turbidity sensors: Turbidity sensors measure water clarity by detecting the scattering of light caused by suspended particles. High turbidity can indicate pollution or erosion issues. Compact turbidity sensors can be mounted on drones to monitor sediment levels and overall water quality. Recent advancements have enabled drones to carry turbidity sensors for environmental monitoring [Reference Hamzah, Aqlan and Baidya45].

Ammonia nitrogen sensors: Ammonia nitrogen sensors detect ammonia levels, which are crucial for assessing nutrient pollution and its impact on aquatic life. While traditionally larger, recent developments have led to more compact and efficient ammonia sensors suitable for drone integration. These sensors are vital for monitoring agricultural runoff and wastewater discharge. Innovations in sensor technology have made it feasible to equip drones with ammonia nitrogen sensors for water quality assessments [Reference de Camargo, Spanhol, Slongo, da Silva, Pazinato, de Lima Lobo, Coutinho, Pfrimer, Lindino, Oyamada and Martins46].

Table 3.

Physicochemical sensor types

Table 3. Long description

A table comparing different physicochemical sensor types, their measurement parameters, advantages, and limitations. The table has 6 rows and 4 columns. The columns are labeled Sensor type, Measurement parameter, Advantages, and Limitations. Row 1: Sensor type, Solid particles (TSS); Measurement parameter, Suspended solids (mg/L); Advantages, Real-time data, useful for pollution detection; Limitations, Affected by water clarity variations. Row 2: Sensor type, Dissolved Oxygen (DO); Measurement parameter, Oxygen levels in water; Advantages, Essential for aquatic life monitoring; Limitations, Sensitive to temperature changes. Row 3: Sensor type, Conductivity; Measurement parameter, Salinity & ion concentration; Advantages, Detects chemical contamination; Limitations, Does not identify specific contaminants. Row 4: Sensor type, pH; Measurement parameter, Acidity/Alkalinity; Advantages, Key to chemical solubility and biological health; Limitations, Requires frequent calibration. Row 5: Sensor type, Turbidity; Measurement parameter, Water clarity (NTU); Advantages, Indicates pollution and sediment levels; Limitations, May not distinguish between different pollutants. Row 6: Sensor type, Ammonia Nitrogen; Measurement parameter, Nutrient pollution levels; Advantages, Detects wastewater contamination; Limitations, Sensors can be expensive.

Solid particles sensor: Also known as a total suspended solids (TSS) sensor, this measures the concentration of suspended particles in water. These particles include silt, algae, organic debris and industrial waste. High levels of suspended solids can indicate pollution, erosion or wastewater contamination, making this sensor critical for environmental monitoring [Reference Shannyn, Tsitsi, Mbulisi, Seifu, Alistair and Tafadzwanashe47] (Table 3).

By integrating these sensors into drones, real-time, automated water quality analysis can be performed with minimal environmental impact. This allows for early detection of pollution sources, assessment of water body health and long-term environmental monitoring.

The combination of solid particle sensors with other physicochemical analysis tools enhances data accuracy and provides a preliminary understanding of water conditions, making drone-based water sampling a powerful solution for modern environmental monitoring.

By integrating an advanced drone sampling mechanism and in-flight physicochemical analysis tools sourced from the information and references in this section, this innovative approach will enable long-distance water sampling and analysis missions. The system will be capable of covering significant distances, from coastal regions to remote and inaccessible areas, even under extreme environmental conditions such as floods. The seamless integration of these technologies will lead to the development of a cutting-edge drone platform with diverse applications across multiple fields.

3.1 Main fuel cell types for UAVs

There are three primary categories of fuel cells used in UAVs Fig. 4:

• • Proton exchange membrane fuel cells (PEMFCs) [Reference Hatti, Meharrar and Tioursi67, Reference Barroso, Renau, Lozano, Miralles, Martín and Sánchez68]

• • Solid oxide fuel cells (SOFCs) [Reference Fernandes, Andrade, Bistritzki, Fonseca, Zacarias and Gonçalves69, Reference Baroutaji, Wilberforce, Ramadan and Olabi70]

• • Direct methanol fuel cells (DMFCs) [Reference González-Espasandín, Leo, Raso and Navarro63, Reference González-Espasandín, Leo and Navarro-Arevalo71]

PEMFCs: A PEMFC involves three parts: the anode, the cathode and the proton exchange membrane (PEM). The PEM is made of Nafion, which can effectively transfer protons [Reference Pan, An and Wen72]. The anode and cathode are located on the two sides of the PEM, respectively. With the diffusion layer and a catalyst layer of the electrode, triple-phase boundaries for electrochemical reactions, including hydrogen oxidation and oxygen reduction reactions, can be achieved.

SOFCs: The SOFC is composed of three solid parts: porous ceramics cathode, porous ceramics anode and a solid oxide electrolyte [Reference Fernandes, Andrade, Bistritzki, Fonseca, Zacarias and Gonçalves69, Reference Abdalla, Hossain, Azad, Petra, Begum and Eriksson76]. The function of the solid oxide electrolyte is similar to that of the PEM, but it transfers negative oxygen ions from the cathode to the anode [Reference Abdalla, Hossain, Azad, Petra, Begum and Eriksson76]. Therefore, electrochemical reactions based on different triple-phase boundaries can be realised in the SOFC.

DMFCs: To achieve long-range and long-duration applications, the DMFC has been proposed as a possible power source for UAVs due to the high energy density of water methanol under conventional conditions [Reference Gong and Verstraete77]. Indeed, the internal configuration of the DMFC is similar to that of the PEMFC, i.e. it consists of an anode, a cathode and a water-saturated PEM [Reference Zago, Bisello, Baricci, Rabissi, Brightman and Hinds78]. In this respect, the DMFC can be considered as a type of PEMFC.

PEMFCs and SOFCs typically achieve higher operating efficiencies than DMFCs) [Reference Seo and Lee79]. However, DMFCs offer an advantage by utilising water-phase fuel, allowing greater energy storage within the same volume compared to PEMFCs and SOFCs [Reference Barthelemy, Weber and Barbier80]. These distinct characteristics arise from differences in electrochemical reactions, making each fuel cell type suitable for specific UAV flight requirements [Reference Boukoberine, Zhou and Benbouzid65, Reference Gong and Verstraete77, Reference Dudek, Tomczyk, Wygonik, Korkosz, Bogusz and Lis81].

Despite their benefits, fuel cells face challenges, such as relatively low power density, reduced efficiency under low or high-power outputs, and slow response times to load changes [Reference Gong and Verstraete77, Reference Dudek, Tomczyk, Wygonik, Korkosz, Bogusz and Lis81, Reference Thounthong and Davat82]. UAVs that rely solely on fuel cells may experience limited manoeuvrability and flight endurance [Reference Donateo, Ficarella, Spedicato, Arista and Ferraro83].

3.2 Hybrid propulsion systems

To address these limitations, hybrid propulsion systems combine fuel cells with complementary power sources, batteries, supercapacitors and solar cells, enhancing performance, responsiveness and energy storage capacity [Reference Gong and Verstraete77, Reference Bataller-Planes, Lapena-Rey, Mosquera, Orti, Oliver, Garcia, Moreno, Portilla, Torroja, Vasić, Huerta, Trocki, Zumel and Cobos84–Reference Yang, Moon and Kim86]. The roles of these complementary power sources vary:

• • Batteries: Commonly used for small, short-range commercial UAVs, batteries provide a stable output voltage and serve as auxiliary power sources. However, for long-endurance UAVs with high and irregular power demands, relying solely on battery-fuel cell integration could reduce battery lifespan [Reference Donateo, Ficarella, Spedicato, Arista and Ferraro83, Reference Verstraete, Gong, Lu and Palmer87, Reference Rezk, Nassef, Abdelkareem, Alami and Fathy88].

• • Supercapacitors: With higher power density than batteries, supercapacitors can smooth out power demand spikes in systems, improving dynamic load response and protecting batteries [Reference Rezk, Nassef, Abdelkareem, Alami and Fathy88, Reference Gong, MacNeill, Verstraete and Palmer89].

• • Solar cells: By harnessing solar energy, solar cells generate electricity without fuel consumption. Mounted on UAV wings, they reduce the space required for power systems and can act as either a primary or supplemental power source, significantly extending flight endurance [Reference Gang, Kim and Kwon90–Reference Gao, Hou, Guo, Fan and Chen93].

Each of these power sources contributes unique strengths to fuel cell hybrid systems. Batteries ensure voltage stability, supercapacitors enhance power density and solar cells provide renewable energy. Together, these components enable UAVs to achieve the desired balance of manoeuvrability, reliability and endurance for various mission profiles. Hybrid propulsion systems represent a promising path forward for improving UAV performance and broadening their operational capabilities.

3.2.3 Hybrid with supercapacitor

Supercapacitors or ultracapacitors, as an emerging energy storage technology, have garnered significant attention in recent years [Reference Rezk, Nassef, Abdelkareem, Alami and Fathy88, Reference Ren, Ma and Cong101]. Compared to lithium-based batteries, supercapacitors deliver significantly higher instantaneous power output, making them ideal for certain applications. However, their primary drawback is their extremely low energy density. Thanks to their rapid charging and discharging capabilities, supercapacitors hold distinct advantages as emergency power supplies in UAVs. Their unique double-layer structure results in very low internal resistance, enabling extremely high charging and discharging efficiencies [Reference Sharma and Bhatti102, Reference Xu, Zhang, Wang and Ma103].

By utilising supercapacitors for short impulses of energy, it offloads the power requirements from the hydrogen fuel cell and battery, which can help extend the battery life and prevent it from heating [Reference Gong, MacNeill, Verstraete and Palmer89, Reference Ren, Ma and Cong101, Reference Sharma and Bhatti102]. This feature makes them especially useful in high-altitude or cold-weather environments, where adding a supercapacitor pack can significantly enhance the performance of propulsion systems. One notable application is the PEMFC/battery/supercapacitor hybrid emergency power system used in more-electric aircraft [Reference Motapon, Dessaint and Al-Haddad85, Reference Sarlioglu and Morris104]. This system leverages the uninterrupted power supply provided by supercapacitors, enhancing the lifetime of both fuel cells (FC) and batteries [Reference Motapon, Dessaint and Al-Haddad85, Reference Motapon, Dessaint and Al-Haddad105].

Gong et al. [Reference Rezk, Nassef, Abdelkareem, Alami and Fathy88] utilised a hardware-in-the-loop (HITL) simulator to investigate an FC/battery/supercapacitor hybrid propulsion system for UAVs. In this setup, the supercapacitor smoothed the FC power output, improving its durability. Compared to FC/battery hybrid systems, studies [Reference Rezk, Nassef, Abdelkareem, Alami and Fathy88, Reference Gong, MacNeill, Verstraete and Palmer89] demonstrated that FC/battery/supercapacitor hybrid propulsion systems deliver faster responses to dynamic electrical loads. Additionally, Gong et al. [Reference Rezk, Nassef, Abdelkareem, Alami and Fathy88, Reference Gong, Palmer and Verstraete106] conducted experimental flight tests in order to avoid collision, using a fixed-wing UAV (Fig. 5). Results showed that the supercapacitor effectively supplied peak power and mitigated power fluctuations, protecting the FC from abrupt shocks under varying flight conditions.

Figure 5.

FC/battery/supercapacitor hybrid power source in a fixed-wing UAV (FC/Battery/Supercapacitor UAV, Credit: https://createdigital.org.au/world-first-drone-fuel-triple-threat/).

Despite these advantages, challenges remain for FC/battery/supercapacitor hybrid systems. One significant issue is the supercapacitor’s output voltage, which fluctuates based on its residual energy [Reference Xu, Zhang, Wang and Ma103]. This makes it difficult to ensure a stable output voltage for the propulsion motor when relying solely on a supercapacitor [Reference Chen, Gao, Dougal and Quan107]. Therefore, relying solely on a supercapacitor as the auxiliary power source in FC hybrid propulsion systems for UAVs is not ideal due to its limited lifespan.

In practical UAV applications, it is generally not recommended to directly connect the supercapacitor to the DC bus or load. Instead, engineers often integrate supercapacitors with batteries to compensate for FC power output limitations [Reference Rezk, Nassef, Abdelkareem, Alami and Fathy88, Reference Gong, MacNeill, Verstraete and Palmer89, Reference Gong, Palmer and Verstraete106]. While the supercapacitor alone may lack sufficient energy storage capacity, its combination with batteries creates a more robust hybrid system capable of addressing both steady and peak power demands effectively.

3.3 Hybrid construction types

The design of hybrid propulsion systems significantly impacts the overall performance of FC-based hybrid propulsion systems. According to the literature [Reference Howroyd and Chen94], three primary objectives must be considered when designing hybrid propulsion systems: regulation, protection and balancing.

• • Regulation: This involves actively controlling the DC-bus voltage as well as the output voltage and current from each power source through regulators.

• • Protection: The output power from the power sources must be decoupled to prevent interference, ensuring the safety of each power source. Specifically, fuel cells must be protected from reverse currents and surge power to ensure safe operation and extend their lifespan [Reference Pratt, Klebanoff, Munoz-Ramos, Akhil, Curgus and Schenkman62, Reference Lee, Park, Kim, Yang and Ahn116].

• • Balancing: The hybrid construction must match the output voltages of the different power sources, effectively distributing power to optimise the performance of the system.

The simplest configuration is the direct hybrid construction, which is often used in FC/battery hybrid propulsion systems [Reference Yang, Moon and Kim86, Reference Nishizawa, Kallo, Garrot and Weiss-Ungethüm99]. However, this design can present challenges. For example, the output voltage of the two power sources may not match, as the FC’s output voltage decreases with increasing output power. To prevent reverse current from damaging the FC, a power diode is typically employed (Fig. 6a). Similarly, when solar cells are added to the system, the direct hybrid construction can also be applied to FC/battery/solar hybrid systems (Fig. 6b) [Reference Lee, Park and Kim111, Reference Lee, Park, Kim, Yang and Ahn116]. The main drawback of these direct hybrid systems is that the output power from the power sources cannot be actively regulated. In the FC/battery/solar hybrid system, for instance, the solar cells and FC can only generate available power when their voltage is equal to or greater than the battery’s output voltage.

Figure 6.

(a) Direct FC/battery hybrid construction (same configuration but without the solar cell) and (b) direct FC/battery/solar cell hybrid construction.

To actively regulate the power sources, the indirect hybrid construction was proposed [Reference Jiaqiang, Liu, Zhang, Han, Chen and Wei54]. In this system, DC-DC converters serve as regulators to transfer energy from one power source to the load bus or to other power sources. Previous studies [Reference Verstraete, Gong, Lu and Palmer87, Reference Das, Tan and Yatim98, Reference Nishizawa, Kallo, Garrot and Weiss-Ungethüm99, Reference Lee, Park and Kim111, Reference Gao, Jiang and Dougal117] have proposed three types of indirect hybrid constructions for FC/battery systems:

Semi-active FC/battery hybrid construction: In this setup, the FC is indirectly connected to a unidirectional DC-DC converter (Fig. 7) [Reference Nishizawa, Kallo, Garrot and Weiss-Ungethüm99, Reference Gao, Jiang and Dougal117]. This allows the output power of the FC to be actively regulated while the battery, connected to the DC bus, absorbs or supplies additional power. The advantage of this system is that the DC-bus voltage matches the battery voltage, providing stability. Moreover, since the FC is isolated from the fluctuating load, its safety and lifespan are better protected.

Figure 7.

Semi-active FC/battery hybrid construction (the converter DC-DC is unidirectional).

Semi-active battery/FC hybrid construction: In this design, the positions of the FC and battery are swapped [Reference Verstraete, Gong, Lu and Palmer87, Reference Arat and Sürer118]. The battery, capable of both charging and discharging, is connected to a bidirectional DC-DC converter (Fig. 8). This allows the FC to provide power to the DC bus directly, minimising energy loss during DC-DC conversion. However, the bidirectional converter requires frequent switching between forward and reverse modes, which introduces energy losses. Additionally, the FC’s output may be affected by load fluctuations due to its direct connection to the DC bus, which could reduce its lifespan.

Figure 8.

Semi-active battery/FC hybrid construction (the converter DC-DC is bidirectional).

Fully active FC/battery hybrid construction: In this configuration, two DC-DC converters are used to control each power source independently (Fig. 9). This decouples the power sources entirely, preventing interference between them and allowing for precise regulation of the DC bus, output voltages, and power from each source [Reference Lei, Yang, Lin and Zhang49, Reference Das, Tan and Yatim98, Reference Ren, Ma and Cong101]. This is the most flexible and efficient hybrid construction, as both the FC and battery are isolated from the DC bus, ensuring their safety. However, the use of two DC-DC converters requires additional space and adds weight to the system, which can compromise the compact, lightweight design of UAVs. The increased weight can also negatively impact the UAV’s payload capacity and flight endurance.

Figure 9.

Full-active FC/battery hybrid construction.

To summarise, this section provides a comprehensive review of current FC hybrid propulsion technologies for UAV applications. Three fuel cell types commonly employed in UAV systems are compared: (1) PEMFCs, (2)SOFCs, and (3) DMFCs. Among these, PEMFCs are identified as the most suitable propulsion candidate for small commercial UAVs due to their favourable operating characteristics, including relatively low operating temperature, high power density and system maturity, as supported by the cited studies [Reference Boukoberine, Zhou and Benbouzid65–Reference Dudek, Tomczyk, Wygonik, Korkosz, Bogusz and Lis81].

Despite these advantages, several limitations constrain the overall effectiveness of FC-based propulsion systems in UAV applications, including limited dynamic power response, reduced efficiency under low- and high-load conditions and comparatively low peak power capability.

To overcome these challenges, hybrid propulsion strategies that integrate fuel cells with complementary electric energy sources are examined. The findings indicate that batteries play a critical role in stabilising power output and supporting transient load demands, while supercapacitors provide rapid power delivery for emergency or high-power burst scenarios. Furthermore, integrating FC systems with solar cells can further extend flight endurance under suitable environmental conditions.

Based on the comparative analysis of hybrid architectures, the semi-active FC/battery configuration, where the battery is directly connected to the DC bus and the fuel cell is interfaced via a DC-DC converter, is identified as the most appropriate solution for the proposed UAV platform, selected by the authors for the proposed application, design choice made by the authors following a comprehensive comparative assessment of hybrid architectures. This decision is based on the synthesis of the reviewed studies, combined with the specific requirements of the proposed UAV platform (e.g. balance between energy efficiency, system simplicity, weight constraints and dynamic performance) [Reference Wang119]. This architecture effectively combines the high energy density of the fuel cell with the fast dynamic response of the battery, enabling efficient load sharing while maintaining a lightweight and simplified system structure. Consequently, the semi-active FC/battery configuration is recommended as the preferred hybrid propulsion architecture for this project due to its advantages in performance, energy efficiency and system reliability.

4.1 Notional fuel cell UAVs

The first documented fuel cell UAV flight was conducted by AeroVironment’s Hornet UAV in 2003 [136]. With a compact wingspan of just 38 cm, this platform demonstrated the feasibility of fuel-cell-powered flight on a small scale. In the same year, NASA tested its Helios aircraft at the opposite end of the size spectrum. This experimental platform, featuring a massive 75 m wingspan, was designed to test an 18.5 kW regenerative hydrogen fuel cell system [137, 138]. These two groundbreaking projects showcased the viability of fuel cell technology for UAVs across vastly different size classes.

Following these initial successes, extensive research efforts emerged, leading to the design, construction, and testing of numerous small fuel-cell-powered UAVs. Universities [Reference Roessler, Schoemann, Baier and Stolten121, Reference Kim, Kim, Lee and Kwon122, Reference Kim and Kwon125, Reference Rhoads, Wagner, Taylor, Keen and Bradley126, Reference Bradley, Moffitt, Parekh and Mavris139–Reference Chaney, Adam, Leachman and Matveev149], defence agencies, independent research organisations [Reference Baldic, Osenar, Lauder and Launie150–156] and corporations such as AeroVironment, Bluebird, Elbit, IAI, Lockheed Martin, ST Aerospace and UconSystem [Reference Gundlach and Foch151, 157–Reference Mills, Buchholtz and Olsen171] all contributed to advancing the technology.

The following is a summary of some of the most noteworthy aircraft from the past two decades, showcasing the progress in technology over the years. Figure 11 illustrates the evolution of fuel cell-powered drones, from their initial use to modern developments, demonstrating how improvements in weight, endurance and flight efficiency have shaped their progression.

Figure 11.

Historical evolution of fuel-cell-powered UAVs.

U.S. Naval Research Laboratory (Spider Lion): The U.S. Naval Research Laboratory (NRL) focused on enhancing the endurance of electric UAVs, leading to the development of the Spider Lion UAV [Reference Stroman, Kellogg and Swider-Lyons172]. This small UAV incorporated a 95 W PEMFC from Protonex and powered a 2.5 kg airframe, achieving a successful flight duration of 3 hours and 19 minutes in November 2005 [Reference Gundlach and Foch151]. This success laid the groundwork for subsequent programmes, including the XFC and Ion Tiger.

eXperimental Fuel Cell (XFC): Building on the achievements of the Spider Lion programme, the eXperimental Fuel Cell (XFC) UAV was conceived in 2006. Designed as a tube-launched unmanned platform, the XFC was developed to serve as a small tactical UAV, leveraging the potential of fuel cell propulsion [Reference Gundlach and Foch151]. Its unconventional design featured pivoting wings that allowed the UAV to fit within the constraints of a tube-type container [173]. The platform had a take-off weight of 9.1 kg and an unfolded wingspan of 3.0 m, powered by a 1 kg 300 W PEMFC [Reference Baldic, Osenar, Lauder and Launie150]. Unlike many other prototypes, the XFC was designed with operational military use in mind. Notably, it was successfully launched from a submerged submarine in 2013, demonstrating its tactical versatility [Reference Gundlach and Foch151].

The fuel cell power system used for the XFC UAV was derived from the Ion Tiger programme, which ran concurrently at the U.S. NRL. This system was a 36-cell Protonex PEMFC, capable of delivering 550 W of power in a lightweight 1 kg package [174]. The externally humidified fuel cell system included essential components such as a blower, humidifier, coolant pump and control electronics. It was highly adaptable, operating continuously between 50 W and 500 W, with a peak efficiency of 42% [Reference Swider-Lyons, Mackrell, Rodgers, Page, Schuette and Stroman175]. This advanced propulsion system enabled the XFC to achieve an endurance of 7 hours.

Ion Tiger: The Ion Tiger programme, which operated alongside the XFC project, was focused on validating cutting-edge fuel cell propulsion systems for UAVs [Reference Gundlach and Foch151, Reference Swider-Lyons, Stroman, Page, Mackrell, Rodgers and Schuette153]. The Ion Tiger featured a conventional airframe design, with a take-off weight of 15.9 kg and a wingspan of 5.2 m. By 2009, it had achieved a 26-hour flight while carrying a 2.3 kg payload, setting an unofficial endurance record [Reference Swider-Lyons, Stroman, Page, Mackrell, Rodgers and Schuette153, Reference Swider-Lyons, Mackrell, Rodgers, Page, Schuette and Stroman175]. In 2013, a modified version of the Ion Tiger, equipped with a water-hydrogen tank, surpassed this achievement with a flight duration of over 48 hours [Reference Tang, Yuan, Pan and Wan132–Reference Verstraete, Lehmkuehler, Gong, Harvey, Brian and Palmer134, Reference Gundlach and Foch151].

Georgia Institute of Technology and Colorado State University: Early work on fuel-cell-powered UAVs was conducted at the Georgia Institute of Technology, where Bradley and Moffitt spearheaded research from 2006 onward. Their efforts resulted in the successful design, construction and flight of one of the first fuel-cell-powered UAVs with publicly available data [Reference Bradley, Moffitt, Thomas, Mavris and Parekh176–Reference Moffitt, Bradley, Mavris and Parekh183]. The UAV had a take-off weight of 16.4 kg and a wingspan of 6.58 m. It was powered by a 500 W, 32-cell PEMFC stack from BCS Technology, with a custom water-cooling system to regulate fuel cell temperature [Reference Bradley, Moffitt, Mavris and Parekh178].

Continuing this work at Colorado State University in 2009, Bradley developed an extended-endurance UAV powered by a proprietary lightweight 600 W fuel cell from UTRC. This UAV, weighing 13.4 kg with a wingspan of 5.54 m, was designed for endurance beyond 24 hours. While this capability was demonstrated in hardware-in-the-loop simulations, it has yet to be confirmed through flight testing [Reference Rhoads, Wagner, Taylor, Keen and Bradley126, Reference Bradley, Moffitt, Fuller, Mavris and Parekh184].

California State University and Oklahoma State University (Pterosaur): In 2004, California State University (CSU) began research into fuel-cell-powered UAVs for remote sensing applications [Reference Ofoma and Wu185, Reference Herwerth, Ofoma, Wu, Matsuyama and Clark186]. Their studies highlighted challenges such as the need for fuel cells with a high power-to-weight ratio and low cost. Despite these hurdles, CSU’s Multidisciplinary Flight Dynamics and Control Laboratory (MFDC) persisted in developing fuel cell UAVs. In 2006, the team procured a 650 W fuel cell from Horizon Fuel Cell Technologies and successfully demonstrated a flight using a hydrogen storage system based on metal hydride tanks [187]. These efforts collectively represent significant milestones in the development and application of fuel-cell-powered UAVs, showcasing progress in endurance, power efficiency and airframe integration.

After its initial successes, CSU continued advancing fuel-cell-powered UAVs, aiming to break range and endurance records in the radio-controlled aircraft category. One notable platform was the Pterosaur UAV, developed in collaboration with Oklahoma State University. The Pterosaur utilised a 150 W PEMFC and a 4-cell 2100-mAh LiPo battery for boost power. Weighing just 5 kg, the aircraft set a range record of 128 km (76 miles) [Reference Chiang, Herwerth, Mirmirani, Ko, Matsuyama, Choi, Nomnawee, Gamble, Arena, Gu, Wankewycz, Koschany and Jin143, Reference Herwerth, Chiang, Ko, Matsuyama, Choi and Mirmirani188].

University of Michigan (Endurance): In 2008, the University of Michigan, in partnership with Adaptive Materials Inc., achieved a new world record for the longest flight by a fuel-cell-powered aircraft. Their Endurance UAV flew for 10 hours and 15 minutes, setting a benchmark at the time [Reference Roessler, Schoemann, Baier and Stolten121, 189]. This milestone also marked the first successful flight of a small propane-powered SOFC UAV.

Korea Aerospace Research Institute (KARI): EAV-1 and EAV-2: KARI has made significant advances in integrating fuel cell systems into UAV platforms. In 2010, KARI equipped the EAV-1 UAV with Horizon Fuel Cell Technologies’ AeroPak hybrid system. This aircraft, with a wingspan of 2.4 m and a weight of 6.5 kg, achieved a flight duration of 4.5 hours [Reference Lee, Park, Kim, Valavanis and Vachtsevanos190]. Building on this success, KARI developed the EAV-2 UAV, an 18 kg sailplane with a 6.9 m wingspan. It retained the 200 W fuel cell from the EAV-1 but incorporated a 240 W solar-cell array and a 1.3 kW battery for smoothing power fluctuations and storing excess energy [Reference Lee, Park, Kim, Valavanis and Vachtsevanos190]. The EAV-2 was the first small UAV to combine solar and fuel cell technologies.

Korea Advanced Institute of Science and Technology (KAIST): In 2007, KAIST developed a blended-wing-body micro air vehicle (MAV) powered by a 50 W fuel cell. Hydrogen was generated onboard using sodium borohydride, with take-off supported by battery power and the fuel cell used for cruising. This UAV demonstrated a 5-hour flight time [Reference Barbosa, Escobar, Sanchez, Hernandez, Acosta and Verde109].

Table 4.

Notional fuel cell UAVs summary table

Table 4. Long description

Panel A: Table with columns for year, take-off weight, propulsion platform, payload, and endurance. Rows list different UAVs: Spider Lion (2005), Experimental fuel cell (2006), Ion Tiger (2009), Georgia tech fuel-cell UAV (2006-2008), Colorado state (2009), Pterosaur (2006), University of Michigan Endurance (2008), KARI EAV-1/EAV-2 (2010), KAIST (2007/2011/2013). Each row details the specific fuel cell type, weight, payload, and endurance. Panel B: No additional panels.

KAIST continued its work in fuel-cell-powered UAVs, creating a larger, conventionally configured aircraft in 2011. This platform, with a 2 m wingspan and a take-off weight of 2.5 kg, achieved a flight duration of 2.5 hours [Reference Kim, Kim, Lee and Kwon122]. In 2013, KAIST collaborated with other Korean research organisations to develop an even larger UAV, featuring a 2.9 m wingspan and a take-off weight of 7.5 kg. Powered by an ammonia borane hydrogen generator, this aircraft successfully completed a 57-minute flight [Reference Seo, Kim, Kim, Kim, Lee and Lee191].

4.2 Modern UAVs with hybrid propulsion systems

Since 2014, the integration of fuel cell and battery technologies in UAVs has led to significant advancements in endurance and performance. Several notable UAVs have emerged during this period (Table 4):

BlueBird Aero Systems’ WanderB: In 2014, BlueBird Aero Systems unveiled the WanderB, a fuel cell-powered mini-UAV capable of flying for more than 10 hours. Designed for intelligence, surveillance and reconnaissance missions, it can carry payloads up to 1.5 kg, including BlueBird’s electro-optical/infrared and laser sensor suite [192].

ST Aerospace’s fuel-cell-powered mini-UAV: In 2016, ST Aerospace developed a mini-UAV equipped with a new solid storage fuel cell, achieving a flight endurance of 6 hours. This advancement demonstrated the potential of solid storage fuel cells in enhancing UAV endurance [193].

Delft University’s project: In 2020, researchers from Delft University introduced the ‘Neder Drone’, a hydrogen-powered UAV designed to showcase the feasibility of hydrogen fuel cells in aviation. The project highlighted the potential for sustainable energy sources in UAV applications [Reference De Wagter, Remes, Smeur, van Tienen, Ruijsink, van Hecke and van der Horst194].

Hy-Fly’s H510 VTOL drone: In 2022, Hy-Fly unveiled the H510, a VTOL drone powered by a hybrid hydrogen-electric system. The H510 demonstrated improved flight times and operational flexibility, marking a significant step in hybrid UAV development [195].

JOUAV-Doosan’s CW-25H: In 2023, JOUAV, in collaboration with Doosan Mobility Innovation, launched the CW-25H, a hydrogen-electric hybrid VTOL fixed-wing UAV. The CW-25H boasts a maximum flight time of 330 minutes, a cruising speed of 80 km/h and a service ceiling of 6000 meters. It can carry a maximum payload of 4 kg, making it suitable for long-distance inspections and large-area surveying and mapping. The integration of Doosan’s DM15 lightweight fuel cell system ensures high stability and reliability [196].

Over the past two decades, hybrid propulsion technology has advanced significantly, with numerous verified projects demonstrating its effectiveness. These developments provide a solid foundation for our research, allowing us to build upon established fuel cell and battery configurations. Initially implemented in multirotor and fixed-wing UAVs, hybrid propulsion systems are now being integrated into VTOL platforms to maximise efficiency and operational advantages.

And the technology continues to advance. From 2024 to 2026, numerous concepts have emerged, not only focusing on VTOL drones but also leveraging the benefits of hydrogen. Companies are exploring their implementation in supersonic drone applications as well as public transportation through eVTOL aircraft. Notable examples include: Destinus, which is developing hydrogen-powered supersonic drones, and Vertiia, a hydrogen-fuelled eVTOL designed for long-range, zero-emission travel.

AMSL Aero’s Vertiia e-VTOL: In November 2024, AMSL Aero’s Vertiia, an emission-free, long-range eVTOL aircraft, successfully completed its first untethered flight in New South Wales, Australia. Designed to carry up to four passengers and a pilot, Vertiia aims to achieve a range of 1,000 km using hydrogen fuel, cruising at speeds of 300 km/h. [197].

Destinus high-speed drone: A Swiss startup is developing hydrogen-powered supersonic and hypersonic drones and planes. In 2026, they plan to test the Destinus G, a 5.5-ton maximum take-off weight UAV capable of exceeding Mach 2 speeds, designed for intercepting various airborne targets. Looking ahead, Destinus aims to build a hypersonic passenger plane by 2030, capable of travelling at speeds five times faster than sound, potentially transporting passengers from Paris to New York in just 1.5 hours [198] (Table 5).

Table 5.

Modern UAVs with hybrid propulsion systems summary table

Table 5. Long description

The table compares various modern UAVs with hybrid propulsion systems, detailing their first documented flight, take-off weight, propulsion system, payload, and endurance. The table has 7 rows and 5 columns. The columns are labeled Platform, First documented flight, Take-off weight, Propulsion system, Payload, and Endurance. Row 1: WanderB, 2014, 14 kg, PEM fuel-cell, 1.5 kg, >10 h. Row 2: ST Aerospace mini-UAV, 2016, 9 kg, Solid-storage fuel cell, 2.5 kg, 6 h. Row 3: Neder drone, 2020, 10 kg, fuel-electric/hydrogen fuel-cell + battery, Experimental sensors, 3 h 38 min. Row 4: H510 VTOL, 2021, 75 kg, fuel-electric/hydrogen fuel-cell + battery, 10 kg, 72 min. Row 5: CW-25H, 2023, 31 kg, Hydrogen-electric with Doosan DM15 fuel cell, 4 kg, 330 min. Row 6: Vertiia (eVTOL), 2025, 4 passengers + pilot, Hydrogen-to-electric via fuel cells, 4 passengers + pilot, 3.3 h. Row 7: Destinus, 2026, 5.5-ton, Hydrogen propulsion concepts, jet/ramjet/combined cycle, Large (tonne-scale), Planned (2026), Mach > 2.