Based on a review of research activities within this field, it is evident that the issue of aircraft autonomy is a subject of active investigation. Additionally, advanced propulsion systems are currently the focus of ongoing research efforts. Typically, hybrid propulsion research is oriented towards fixed-wing aircraft, while multirotor aircraft are primarily configured with fully electric propulsion systems. While there are occurrences of multirotor aircraft employing fuel cells and similar energy sources, such instances are relatively infrequent within the broader context of multirotor propulsion technologies.

References [1], [2] establish the foundational framework for modelling, designing control systems, and validating experiments related to the HPU comprising an ICE-EG configuration and are used as the basis for this research.

Reference [3] introduces a comprehensive model designed to assess the performance of a fuel cell hybrid system integrated into a multirotor drone. This model serves as a valuable tool for evaluating the feasibility of employing a hybrid fuel cell system for a specific drone and ascertaining whether it offers superior endurance compared to conventional batteries.

In a practical case study, the utilization of a fuel cell hybrid system is observed to enhance flight duration by a notable 76% when contrasted with the prevalent LiPo batteries. Additionally, this versatile model lends itself to the optimization of system configurations and sensitivity analysis, facilitating further advancements in performance.

It is worth noting, however, that the current cost of implementing a fuel cell hybrid system stands at approximately twelve times that of LiPo batteries. Moreover, there exists a threshold energy system mass of 7.3 kg, beyond which the fuel cell hybrid system demonstrates a performance advantage over batteries in terms of endurance.

Reference [4] investigates the integration of a hybrid power system into a compact UAV. The analysis draws upon data obtained from rigorous bench tests and sophisticated simulations. Notably, the hybrid power system leads to a substantial enhancement in the UAV’s flight performance, extending its endurance from 470 to an impressive 970 minutes. This research study highlights the practicality of hybrid power systems for small UAVs and also establishes the effectiveness of renewable energy sources for mobile applications.

In their review article [13], the authors conducted a systematic review of the literature on hybrid-powered multi-rotor UAVs. They emphasized the importance of internal ICE and highlighted the necessity for further advancements in FCs and batteries. Additionally, they emphasized the significance of high-power powertrains in extending UAV endurance and payload capabilities, suggesting the evaluation of reliable performance parameters across various power ranges. It is found that the pivotal role of hybrid power systems in enhancing UAV capabilities is urged for continued development and optimization. Finally, they proposed future research to effectively integrate multiple power sources, enabling better control and management of generated power while storing excess energy.

Reference [14] introduces a prototype of an advanced hybrid generator employing innovative electronics and a supercapacitor array. This design aims to enhance efficiency, prevent overheating, and extend the operational lifespan of engines within unmanned aerial systems. The system incorporates a throttle control mechanism, and the prototype boasts nearly twice the power output when compared to conventional hybrid generators. Control of the system is managed through a field-programmable gate array (FPGA), which includes dedicated control loops for individual components, along with a comprehensive monitoring and data transmission system for real-time data collection.

The study of fuel cell-based power sources has emerged as a promising path to significantly extend the flight endurance of industrial multirotor drones, surpassing the limitations posed by contemporary lithium-based batteries [15]. While commercially accessible lightweight alternatives exist, embracing this technology presents a set of hurdles, encompassing certification, technical enhancements, and operational intricacies.

The prospect of liquid-cooled fuel cells holds promise in broadening the flight capabilities of UAVs, yet the inherent challenge lies in mitigating the elevated system mass they introduce. Conquering obstacles related to hydrogen storage and substantiating the technology’s operational and financial advantages under real-world conditions stands as a fundamental step in its widespread adoption.

In the domain of multirotor propulsion systems, reference [16] offers an introductory overview, complemented by empirical characterizations. Simultaneously, reference [17] outlines a method for selecting propulsion components based on simplified modelling and introduces an online validation software tool tailored for preliminary calculations during the initial phases of aircraft design.

As shown by reference [18], electrochemical batteries stand out as the predominant power source for multirotor UAVs. This paper conducts a thorough analysis of power consumption and presents an endurance estimation model tailored for aircraft powered by LiPo batteries. Furthermore, a series of experimental flight tests conducted using a commercial multirotor platform confirm the theoretical analysis therein.

In reference [19], the authors propose a conceptual solution for the design of heavy-lift multirotor systems. Their comprehensive analysis encompasses five distinct series of electric propulsion units, each characterized by different multirotor configurations. The study presents results for payloads ranging from 10 kg up to a substantial 100 kg.

Reference [20] shifts the focus to the practical implementation of a hybrid-electric power system, validated through simulations. The results, while indicating the potential for enhanced flight endurance in fixed-wing aircraft, also highlight several details associated with small Internal Combustion Engines (ICEs), including challenges such as intense vibrations and the necessity of active cooling or alternative thermal management solutions.

The reference [21] thoroughly explores the domain of ICE-based propulsion, comprehensively covering the static and dynamic characteristics of these propulsion systems in a valuable manner.

In the study [22] the authors assess challenges in UAV technology, including limited flight duration and payload capacity, focusing on Hybrid Power Systems. The study conducts a systematic literature review for such systems in multi-rotor UAVs and analyzes available commercial models of such systems.

In their study [23], the authors adopted a novel methodology, utilizing fast-response electric motors for stability and integrating a gasoline propulsion system for lift force in their exploration of the impact of a gasoline-electric hybrid multirotor drone on flight duration relative to an electric multirotor drone. While this approach exhibits potential, additional testing is required to validate its effectiveness and feasibility for practical applications.

In summary, the research studies discussed in these references offer valuable insights into the design, modelling, and characterization of multirotor propulsion systems and power sources. The knowledge gleaned from these sources can improve the development of propulsion systems that exhibit greater effectiveness for multirotor UAVs, particularly in the realm of heavy-lift applications.

Currently, the market for HPU is in its early stage of development, however, several notable products have emerged in the hybrid power market. For instance, FoxtechFPV™, a Chinese manufacturer, offers the GAIA™ multirotor, utilizing the NOVA2400™ HPU, depicted in Figure 3a. This system boasts a continuous power capacity of 2400 W, can accommodate a maximum take-off mass of 23 kg, and is priced at approximately 5000 EUR.

Another noteworthy player is Quaternium, a Spanish manufacturer, which manufactures the HYBRIX 2.1™ featuring an advertised power output of 2600 W and a maximum take-off mass of 25 kg, as illustrated in Figure 3b. This product is available in the price range of 5000 EUR to 8000 EUR and has achieved a world record for flight endurance, with over 10 hours and 10 minutes of hovering time.

Additionally, Aerocámaras, a Spanish manufacturer, offers the AEROHYB™ hex copter, powered by the NOVA2400™. It is advertised to support a maximum take-off mass of 19 kg and provides a flight time of up to two hours with a maximum payload, as shown in Figure 3c.

Lastly, Pegasus Aeronautics, a Canadian company, introduces the GE70™ hybrid generator, which utilizes a two-stroke boxer engine from model planes. This generator boasts a maximum power output of 4000 W, incorporates liquid cooling, and fuel injection, and is priced at around 15000 EUR, as depicted in Figure 3d. Additional information regarding these solutions and similar approaches can be found in references [14], [22].

Figure 3.

Commercial hybrid power units: (a) Foxtech NOVA2400 [24]; (b) Quaternium HYBRIX 2.1 [25]; (c) Aerocámaras AEROHYB [26]; (d) Pegasus Aeronautics GE70 [27]

First, it is fundamental to understand the interplay among mass, thrust, and payload capacity to accurately estimate the necessary propulsion power for a multirotor. The formula to calculate the mass of the multirotor is given as follows.

$m_{\text{total}} =m_{\text{UAV}}+m_{\text{PU}} +m_{\text{PL}}$ (2)

In the above equation, m_UAV stands for the mass of the multirotor which includes the combined weight of the frame, motors and speed controllers, propellers, electronics, and any other onboard equipment (excluding the power unit). Meanwhile, m_PU is the total mass of the power unit, encompassing elements such as batteries or a hybrid power unit with fuel. Lastly, m_PL represents the mass of the useful payload, which could be items like a camera, agricultural spraying unit, or other similar devices installed on the multirotor.

Next, it is important to consider the hovering condition, which is reached when the total onboard weight is balanced by the collective thrust produced by all the propellers.

$F_{\text{total}}=m_{\text{total}}g={\displaystyle \sum _{n=0}^i{F}_{\text{T,}i}}$ (3)

F_total represents the combined thrust of all propellers, and F_T,i represents i-th individual thrust contribution of i-th propeller.

The above expression is applicable only under ideal steady-state conditions, where external disturbances such as aerodynamic drag, varying wind conditions, or any transient forces are absent. In real-world scenarios, these factors can significantly influence the multirotor performance, necessitating additional considerations in the design and control algorithms to maintain stability and efficiency.

When evaluating two different power systems for multirotors, we introduce a simplification and assume a consistent mass for the multirotor in all tests. This assumption suggests that while executing the same complex movement, i.e. following a set trajectory, the system would consume the same amount of energy for each case, regarding the power source type – with the condition of the same take-off mass. With this premise, the analysis can be streamlined to primarily focus on the hovering state which, in turn, significantly reduces the complexity of the model.

In evaluating multirotor performance, endurance and flight range are usually most key factors. Endurance is defined as the multirotor flight duration capability, while flight range indicates the distance it can traverse on a single charge or fuel load. These metrics are typically inversely related, with enhancements in one often resulting in compromises in the other. Maximum endurance is usually achieved at lower flight speeds, where most of the energy is allocated to counteracting the multirotor weight, thus leaving minimal energy for propulsion. This, however, limits the flight range due to reduced speed. For analytical convenience, this study focuses on comparing the performance of different power units (battery versus hybrid power units) based on hovering endurance, excluding transient effects. This approach provides a valid assessment of the power unit’s efficiency, encapsulated by the following equation.

$t_{\text{e}}=\frac{E_{\text{a}}}{P_{\text{i}}}$ (4)

E_a is the available energy, P_i is power consumption, and t_e is the endurance.

LiPo (Lithium Polymer) batteries are the preferred power source for multirotor UAVs, valued for their high energy density and rapid discharge capability. Yet, they present challenges including degradation over time, diminished performance in cold conditions, and a discharge rate-dependent capacity. Detailed experimental characterizations of LiPo batteries are available in the literature [1], [2].

Typically, the nominal voltage range for LiPo batteries, from fully charged (100% state of charge) to fully depleted (0% state of charge), spans from 4.2 to 3.3 volts, measured in an open circuit voltage state post chemical stabilization.

It is well-known that electrochemical batteries exhibit non-linear behaviour during charging and discharging, resulting in an exceptionally complex simulation model. For this study, the analysis has been conducted to develop a straightforward discharge model.

For that purpose, the cell voltage, V_ref is assumed to be a constant 3.75 V and the depth of discharge, η_DOD is set at 80%, as a practical value for maintaining battery longevity. The battery charge capacity Q_b is derived from the manufacturer’s specifications. The energy capacity of the LiPo battery is then calculated as follows.

$E_{\text{LiPo}}=Q_{\text{b}} V_{\text{ref}} {\eta }_{\text{DOD}}$ (5)

The hybrid power unit topology considered in this study is based on previous work [1], [2] and depicted in Figure 4. This unit comprises an ICE, an EG with an integrated rectifier and filter (RF), and an auxiliary LiPo battery. These components are connected to a direct current (DC) power bus.

Figure 4.

Topology of considered Hybrid power unit [1], [2], [28]

The ICE serves as the primary mover, mechanically linked to the electricity generator, such as a Permanent Magnet Synchronous Motor (PMSM) or Brushless DC (BLDC) machine. The power generated by the ICE-EG set acts as the main power supply, catering to the quasi-steady-state power requirements, particularly for maintaining hover.

For peak load demands, such as during intense movements that cause a sudden spike in electrical load over a brief period, the battery connection is employed for peak load shaving. This setup allows the hybrid system to smoothly manage power surges until the power output stabilizes. Furthermore, in the event of an ICE-EG system failure, the auxiliary LiPo battery can provide emergency power for several minutes, enabling the emergency landing.

Constraints are introduced to reduce the number of variables in the analysis to keep enough generalities:

• ICE drives the electricity generator (BLDC machine), which provides for a quasi-steady–state load power supply, and mass reduction due to fuel consumption is neglected

• the battery unit is used for peak load shaving and emergency landing; the battery cannot be charged in flight.

The available energy from the Internal Combustion Engine-Electric Generator (ICE-EG) set is contingent upon several factors: the continuous output power, denoted as P_ICE,EG, the onboard volume of the fuel V_tank, and the average fuel consumption rate Q_fuel.

Considering that the typical operational regime for such ICE-EG units is near its maximum torque output, it is a reasonable approximation to assume a constant rate of fuel consumption.

However, it is important to note that fuel consumption is intricately linked to the operational conditions of the unit. A more exhaustive evaluation, particularly when the engine is operated across its full throttle range, would necessitate a detailed analysis of potential variations in fuel consumption rates. To estimate the available energy from the ICE-EG set, the following equation can be utilized as follows.

$E_{\text{ICE},\text{EG}}=P_{\text{ICE},\text{EG}}\frac{Q_{\text{fuel}}}{V_{\text{tank}}}$ (6)

The total energy capacity of the hybrid power unit under review is quantified as the aggregate of the effective energy derived from the Internal Combustion Engine-Electric Generator (ICE-EG) set and the energy stored in the auxiliary battery as follows.

$E_{\text{total}}=E_{\text{ICE},\text{EG}}+E_{\text{LiPo},\text{AUX}}$ (7)

Following the methodology established in the preceding chapter, mass breakdown graphs for three multirotor designs are presented in Figure 9 to Figure 11. Scenarios, where the mass of the battery pack exceeded the specified hovering thrust capacity for each multirotor, were excluded from consideration. The calculated endurance for these designs is depicted in Figure 12.

Figure 9.

Mass breakdown, battery-powered multirotor: case 1, based on Xrotor X6

Figure 10.

Mass breakdown, battery-powered multirotor: case 2, based on Xrotor X8

Figure 11.

Mass breakdown, battery-powered multirotor: case 3, based on Xrotor X9

Figure 12.

Calculated endurances per multirotor take-off mass

The previous section detailed our investigation into HPU, focusing on selecting suitable fuel tanks and calculating the total mass of the ICE-EG and fuel. This was done to ensure compliance with the maximum permissible take-off mass for each propulsion type. Here, we present the results of that analysis.

Following the steps outlined in the case study section, we undertook a tank analysis, calculating both the fuel mass and the overall mass of the full tanks for the selected options. Utilizing fuel consumption data from Table 4 and the capacities of these tanks, we determined the maximum operational duration for each full tank in various HPU and tank scenarios. The results of this analysis are compiled in Table 7.

For a clearer interpretation of these findings, mass breakdown graphs for three multirotor designs are exhibited in Figure 13 to Figure 15. Configurations, where the HPU mass surpassed the designated hovering thrust for each multirotor, were excluded. Furthermore, Figure 16 showcases the calculated endurance for each HPU and tank combination.

These results are essential in assessing the practicality of hybrid power units for boosting multirotor endurance. They offer insights into the most effective tank configurations for each HPU and the upper limits of endurance achievable. When compared with the findings from the pure electric power unit analysis, these results help identify the most appropriate power unit configuration for specific multirotor designs.

Figure 13.

Mass breakdown, hybrid-powered multirotor: case 1, based on Xrotor X6

Figure 14.

Mass breakdown, hybrid-powered multirotor: case 2, based on Xrotor X8

Figure 15.

Mass breakdown, hybrid-powered multirotor: case 3, based on Xrotor X9

Figure 16.

Calculated endurances per multirotor take-off mass

The findings from the preceding section indicate that a multirotors endurance is influenced by the configuration of its power unit and the amount of fuel it carries. In Figure 17a, the correlation between the total available energy and the mass of the power unit is depicted. This graph reveals that the energy available from hybrid power units substantially surpasses that of purely battery-powered units once the mass of the power unit surpasses a certain threshold. These critical mass values for the respective multirotor cases are identified as 4.94 kg, 8.41 kg, and 10.88 kg.

Additionally, Figure 17b illustrates a significant improvement in achieved endurance when the mass of the power unit exceeds these critical values. This trend underscores the superiority of hybrid power units in extending flight durations. The visual data presented in these figures provide a compelling argument for the advantages of hybrid systems in scenarios where extended endurance is a priority.

Figure 17.

Endurance, energy, PU mass analysis: Endurance vs PU mass (a); Energy vs PU mass (b)

Figure 18 elucidates the relationship between the available payload capacity and the endurance achieved using various power unit configurations. The graph shows an increase in endurance as the mass of the power unit grows, up to a pivotal point. Beyond this critical value, the hybrid power unit begins to significantly outperform its battery-powered counterpart. This trend suggests that for multirotors tasked with carrying larger payloads or those with higher power demands, a hybrid power unit becomes a more effective choice for extending flight duration.

Figure 18.

Endurance versus remaining payload mass, first multirotor case (a); Second multirotor case (b); Third multirotor case (c)

To summarize, the findings from this analysis offer valuable perspectives on the balance between the mass of the power unit, the endurance it can provide, and the payload capacity. For multirotors with modest power needs or smaller payloads, battery-powered units emerge as the preferable option. Conversely, in cases where the multirotor must meet higher power demands or carry larger payloads, the benefits of a hybrid power unit become more pronounced. The critical mass values identified for each multirotor scenario serve as a practical benchmark, guiding the selection of the most suitable power unit configuration to achieve the desired level of endurance.

In the final stage of our performance analysis, the goal is to assess how hybrid power units (HPU) stack up against battery power units (BPU) for each type of multirotor. For this purpose, an HPU with a mass equivalent to that of the multirotor is selected, along with a LiPo battery of comparable capacity – specifically, 22 Ah, 44 Ah, and 66 Ah for each respective case.

Data for the HPU is derived through linear interpolations, using the information from Figure 17 and Figure 18. Figure 17a displays the total available energy as a function of the power unit’s mass, while Figure 17b shows the connection between the power unit mass and the endurance achieved.

Conversely, Figure 18 illustrates how the endurance varies with the remaining payload capacity for different power units.

Applying this method revealed that for the three multirotor cases, the HPU offered an increase in endurance by 35, 57, and 118 minutes, respectively, compared to the BPU. These findings are detailed in Table 8.

This comparative analysis sheds light on the distinct performance capabilities of HPU and BPU in various scenarios. The results indicate that when the HPU’s mass surpasses a specific threshold, it surpasses the BPU in endurance. Such insights are crucial for designers in selecting the most appropriate power unit for a multirotor, considering its specific mass and payload requirements.