Corresponding author’s email address: 790 ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY & ENVIRONMENT ORIGINAL RESEARCH ARTICLE DESIGN AND ANALYSIS OF FLIGHT PERFORMANCE OF A HYBRID ENERGY SOURCE FOR UNMANNED AERIAL VEHICLE D. N.O. Eleazer1, U. E. Uche2*, M. Tajudeen3 and I. M. B. Omiogbemi2 1Department of Aerospace Engineering, Faculty of Air Engineering Air Force Institute of Technology, Kaduna, Nigeria, 2Department of Mechanical Engineering, Air Force Institute of Technology, Kaduna, Nigeria, 3Department of Material and Metallurgical Engineering, Air Force Institute of Technology, Kaduna, Nigeria. *Corresponding author’s email address: eaumie@gmail.com ARTICLE INFORMATION ABSTRACT This study presents a hybrid energy harvesting system for Unmanned Aerial Vehicle (UAV), that integrates solar power and hydrogen fuel cells to enhance flight performance. The study commenced with the analysis of the case study UAV flight power design specifications using analytical methods. the estimation of number of solar cells and the hybridization of the solar and hydrogen fuel cells. A Computer Aided Design (CAD) model of the solar cell arrangement is created using industrial software which enables the visualization of the arrangement on the wing in a virtual environment. The mission performance analysis was carried out using Excel tool and Matrix Laboratory (MATLAB). The redesigned system increased available power to 580 Watts with a weight penalty of 1.5 Kg thereby reducing the payload mass from 4.627 kg to 3.085 kg. To assess the structural implications of this result, a stress analysis was performed using Computer- Aided Three-dimensional Interactive Application (CATIA) and Abaqus software which revealed a negligible failure index of 0.000757. The hybrid system achieved a 120% increase in power that extended the endurance from 4.2 hours to 16.3 hours and the range from 6 km to 230 km. The design offers a promising solution for enhanced UAV performance. Submitted: 30 May, 2024 Revised: 29 June, 2024 Accepted: 08 July, 2024 Keywords: Hydrogen Fuel Cell Solar Hybridization Endurance Range © 2024 Faculty of Engineering, University of Maiduguri, Nigeria. All rights reserved. 1.0 Introduction The hybrid energy harvesting UAV designed by the 2021/2022 MSc research students at Air Force Institute of Technology was used as the test bed for this paper. The case study UAV has an endurance of about four hours using a combination of a 7S 4000 mAh Li-Po battery and hydrogen fuel cell system as its power source (AFIT- ALTA, 2022). The design goal was to integrate the fuel cell to increase the endurance and range parameters of the UAV, as well as power the onboard electronic or avionics components. The increase in the endurance is significant. However, at instances where there is strong turbulence resisting the motion of the UAV, the endurance calculated for the mission falls short and the liquid hydrogen fuel is not sufficient to accomplish the mission. Therefore, with an appreciable wing geometry, solar cell is selected based on its environmental friendliness and energy conversion efficiency compared to other energy sources to counter this limitation. The solar cells will be sized and arranged in series on the upper surface of the plan form area of the wing to provide an operating voltage higher than the battery voltage to be able to charge the battery and onboard avionic equipment. The solar cells will be arranged to flush with the wing surface in order not to increase drag. Collaterally, integration of the solar cells on to the wing of the UAV is accompanied with some mass complexities which will either increase or decrease the operational empty weight of the UAV. (Saravanakumar et al., 2023; Wang et al., 2022; Matlock et al., 2019). Unmanned Aerial Vehicle (UAV), commonly known as drone is an aircraft without any human pilot or crew onboard. They are controlled remotely with the aid of sensors that transmits and receive radio signals for communication (Mohammadnia et al.,2020). The UAV under study, was designed to have an all-up mass of 10 Kg and a wingspan of about 4.2 m. The image of the aircraft is shown in Figure 1. It serves as the case study hybrid energy UAV for flight power performance analysis. AZOJETE December 2024. Vol.20(4):790-812 Published by the Faculty of Engineering, University of Maiduguri, Maiduguri, Nigeria. Print ISSN: 1596-2490, Electronic ISSN: 2545-5818 www.azojete.com.ng mailto:eaumie@gmail.com http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 791 Figure 1: Hydrogen fuel cell UAV (AFIT-ALTA, 2022) In recent times, UAVs play a major role in global society due to their ability to carry payloads, operate and monitor complex scenarios where the presence of onboard human pilots are needless. UAVs are however constrained by power, which invariably affects their performance during most flight missions. Typically, therefore, the mission profiles of these UAV’s are limited by insufficient range and endurance. Its main source of power is either engine or batteries. A hybrid energy harvesting system offers increased flexibility into the UAV design by allowing choice of specific instrument regardless of the electrical bus and to expand the system as system requirement changes. Some of the energy harvesting technologies used to generate electricity for air vehicles include Piezoelectric process, Thermoelectric process, Electromagnetic process and Photovoltaic techniques. The basic components of a conventional energy harvesting system is depicted in Figure1. It includes the energy input source, detection and storage and the loads to which the scavenged energy will be supplied to. Components required to achieve the process include transducers to convert ambient energy to electrical energy, power management circuit to adjust the harvested energy based on the needs of the loads embedded in the UAV and lastly, an energy storage buffer to deliver the high power to the load. Figure 2: Conventional Energy Harvesting System (Prauzek et al., 2018) Various concepts are employed in the utilization of solar energy, but one of the ways proposed to tap maximum amount of electrical energy efficiently and effectively from the solar is a hybrid combination of solar panels and thermoelectric generators (Mohammadnia et al., 2020) Thermoelectric generator (TEG) is a solid-state device that converts heat energy to electrical power by means of semiconductor charge carriers serving as a working fluid. They function like heat engines but are less massive with no moving parts (Rezania and Rosendahl, 2012). Their advantages are that they do not require any fluid for fuel or cooling, making them non-orientation dependent and allowing for use in zero-gravity or deep-sea applications. In this system the solar produces heat in addition to the photons that are focused onto the panels. The heat energy is tapped and converted into electrical energy to boost the energy produced by the solar panels. Ozbek et al., (2021) used a Polymer Electrolyte Membrane (PEM) fuel cell – Li-Po batteries as a hybrid energy harvester to produce more wattage power for the fixed wing UAVs to achieve large endurance. In his experiment, he observed that, approximately 160 – 170W power was met by the fuel cell when no preconditions were applied. The fuel cells converted the chemical energy of the fuel into direct current electricity through electrochemical process without any moving parts (Barbir, 2012). Also made studies into providing some regenerative power from some avionics or electronic components installed in UAVs by equipping it with energy harvesters which can scavenge energy from radio frequency (RF) using relays have been carried out. However, the energy generated is not enough to power large loads. Citroni et al. (2019) AMBIENT SOURCE DETECTOR (SENSORS) ENERGY CONVERTER ENERGY STORAGE MODULE ENERGY CONSUMPTIO N MODULE http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 792 therefore proposed a hybrid energy harvesting system that can recover energy from solar and RF energy sources at the same time to significantly improve the energy required for long flights. The RF energy from the surroundings serves as an alternative power source for powering the UAV when there is insufficient or no radiation to generate electrical power from the solar panels. Furthermore, there is the need to consider better aerodynamics properties irrespective of design modifications to increase the overall UAV performance during its flight missions (Wang et al., 2019). The focus of the study therefore includes the analysis and design of takeoff, landing, climb and cruise power supply system and its performance evaluation in terms of the UAV endurance, range and other flight performance indicators. 2. Materials and Methods 2.1 Materials The aircraft understudied has design specifications as shown in the Table 1. Table 1: Design specification of case study UAV Parameters Values Design Gross weight 10 kg Maximum ceiling altitude 10,000 ft. Maximum range 6 km Design cruise speed 14.3 m/s Maximum balanced field length <100 m Engine AXI 4130/20 Electric Motor Wing area 1.009835 m2 Wingspan 4.28 m The main battery power source was augmented with a hydrogen fuel cell stack on a 7S 4000 mAh Li-Po battery. 2.2 Methods 2.2.1 UAV Power Requirement 2.2.1.1 Determination of Take-Off Power Requirement Power (P) required for the UAV to successfully achieve a complete take-off is estimated using the formula (Malik, 2020). 𝑃 = 𝑇ℎ𝑟𝑢𝑠𝑡 × 𝑇𝑎𝑘𝑒 − 𝑜𝑓𝑓 𝑣𝑒𝑙𝑜𝑐𝑖𝑡𝑦 . (1) Where the thrust (T) is estimated as; 𝑇 = 𝐷 +𝑊𝑠𝑖𝑛𝛾 (2) Where the climb angle of the aircraft is represented as 𝛾, D is the drag of the UAV and W is the weight of the UAV. 𝐷 = 1 2 𝜌𝑉𝑠 2𝑆[𝐶𝐷0 + 𝑘𝐶𝐿𝑚𝑎𝑥 2 ] (3) Also, the free stream velocity is expressed as; http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 793 𝑉𝑠 = √ 2𝑊 𝜌𝑆𝐶𝐿𝑚𝑎𝑥 (4) Therefore, assuming sea level conditions, the density is assumed to be 1.225 𝑘𝑔𝑚−3, and the UAV specification,𝐶𝐿𝑚𝑎𝑥 = 1.38, 𝜌 = 1.225 𝑘𝑔𝑚 −3,𝑊 = 10 𝑘𝑔, 𝑆 = 1.009835 𝑚2the free stream velocity is estimated using Equation 4 (Clark, 2018). Power required for the UAV to successfully achieve a complete take-off is therefore estimated using Equation 1, 2,3 and 4, assuming sea level conditions of density 1.225 𝑘𝑔𝑚−3, and taking the 𝐶𝐿 ,𝑊 𝑎𝑛𝑑 𝑆 from the case study UAV specification to first obtain the free stream velocity as follows: 𝐶𝐿𝑚𝑎𝑥 = 1.38, 𝜌 = 1.225 𝑘𝑔𝑚 −3,𝑊 = 10 𝑘𝑔, 𝑆 = 1.009835 𝑚2 𝑉𝑠 = √ 2(10 × 9.81) 1.225 × 1.009835 × 1.38 = 10.7205 𝑚𝑠−1 Therefore, the minimum speed at which the UAV can be maintained to generate lift for a successful take-off is estimated to be 10.7205 𝑚𝑠−1. To ensure a safety margin during take-off, a liftoff velocity is also estimated which is about 20% greater than the stall velocity is obtain using Equation 5. 𝑉𝐿𝑂 = 1.2𝑉𝑠 (5) 𝑉𝐿𝑂 = 1.2(10.7205) = 12.8646 𝑚𝑠 −𝑠 The drag the UAV will be subjected to during take-off is also estimated using Equation 3 to obtain 𝐷 = 1 2 (1.225) × (10.7205)2 × (1.009835) × [0.0109 + 0.0446(1.38)2 = 6.7464 𝑁 Considering a climb angle of 5 degrees, the Take-off thrust (T) is projected from Equation 2 𝑇 = 6.7464 + 10(9.81) sin(5) 𝑇 = 15.2963 𝑁 Therefore, having estimated the value for the take-off thrust and Lift-off velocity, the power required by the UAV for take-off is estimated from Equation 1. 𝑃 = 15.2963 × 12.8646 = 196.7820 𝑊𝑎𝑡𝑡𝑠 Therefore, the power required to achieve a complete take-off by clearing the 50 feet obstacle height is 197 watts. 2.2.1.2 Determination Climb Power Requirement For climb performance evaluation (Figure 3), parameters considered are the rate of climb (ROC), and the climb angle (𝛾). With these parameters well estimated, the UAV will be able to climb at a good rate over vertical obstacles. It is worth noting that, the maximum ROC is experienced at sea level and decreases as the altitude increases. ROC which is defined as the rate of change of altitude per unit time is mathematically expressed as in Equation 6 (Anderson, 2020) http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 794 𝑅𝑂𝐶 = 𝑑ℎ 𝑑𝑡 = ℎ̇ (6) Where h = the altitude and t = time. Figure 3: Forces acting on an aircraft in Climb. (Malik, 2020) The propeller of the UAV is mounted at an angle known as the climb angle (𝛾) of 5°. Since the UAV will be climbing at a constant acceleration ‘a’, from Newton’s second law, the equilibrium of the forces in the direction of flight can be expressed as in Equation 7; 𝑇𝑐𝑜𝑠(𝑖𝑇 + 𝛼) − 𝐷 −𝑊𝑠𝑖𝑛(𝛾) = 𝑚𝑎 = 𝑚( 𝑑𝑣 𝑑𝑡 ) (7) Where ‘𝑖𝑇’ is the angle of incidence, 𝛼 is the UAV angle of attack. If all forces are assumed to pass through the center of gravity, 𝑖𝑇 and 𝛼 are also assumed to be zero, then Equation (6) becomes Equation 8 (Anderson, 2020) 𝑇 − 𝐷 −𝑚𝑔𝑠𝑖𝑛𝛾 = 𝑚( 𝑑𝑣 𝑑𝑡 ) (8) The airspeed vector ‘V’ is then resolved into its vertical and horizontal component. By definition, the vertical component ℎ̇ is the ROC of the UAV. From Figure 4, the relationship between the forward speed and ROC is expressed as in Equation 9. 𝑉𝑠𝑖𝑛(𝛾) = 𝑑ℎ 𝑑𝑡 = ℎ̇ (9) Figure 4: Horizontal and Vertical Airspeed component for ROC Multiplying Equation (8) by 𝑉 and substituting it into Equation 9 yields, (𝑇 − 𝐷)𝑉 = 𝑑(𝑚𝑔ℎ+ 1 2 𝑚𝑉2) 𝑑𝑡 (10) Where (𝑇 − 𝐷)𝑉 = 𝑒𝑥𝑐𝑒𝑠𝑠 𝑝𝑜𝑤𝑒𝑟 𝑎𝑛𝑑 𝑚𝑔ℎ + 1 2 𝑚𝑉2 = 𝑡ℎ𝑒 𝑈𝐴𝑉 𝑡𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 795 Therefore, the UAV ROC is estimated using the Equation 11, 𝑅𝑂𝐶 = (𝑇−𝐷)𝑉 𝑊 (11) 𝑅𝑂𝐶, the power required for the climb phase is calculated using the Equation 12, 𝑃𝑐𝑙𝑖𝑚𝑏 𝑟𝑒𝑞 = (𝑇 − 𝐷)𝑉𝑙𝑜 (12) From Equation (11), 𝑅𝑂𝐶 = [(15.2963 − 6.7464) × 12.8646] 10 × 9.81 = 1.1212 𝑚𝑠−1 The UAV will be climbing at a speed of 1.1212 𝑚𝑠−1 to cruise altitude where climbing will stop. This indicates that, ROC generally decreases with altitude to the cruise altitude where it becomes zero. Using the Equation 12, , the power required for the climb phase is 𝑃𝑐𝑙𝑖𝑚𝑏 𝑟𝑒𝑞 = (15.2963 − 6.7464) × 12.8646 = 109.99 𝑊𝑎𝑡𝑡𝑠 2.2.1.3 Determination of Cruise Power Requirement The governing principle in straight and level flight is the Newton’s second law of motion which explains how an object’s motion changes when a force is applied. The external forces of interest in this flight phase are the UAV weight (W), thrust (T) from the battery, drag (D) and lift (L) as shown in Figure 5. Figure 5: Equilibrium of forces in a straight level flight (Malik, 2020) In an un-accelerated straight and level flight, the governing Equations 13 of motion are. ∑𝐹𝑥 = 0 𝑎𝑛𝑑 ∑ 𝐹𝑧 = 0 (13) This is an implication that, the UAV is in a trim or equilibrium state. From figure 5, the trim equations along 𝑧 and 𝑦 axes are Equation 14 and Equation 15. 𝐷 = 𝑇𝑐𝑜𝑠(𝛼 + 𝑖𝑖) (14) 𝑊 = 𝐿 + 𝑇𝑠𝑖𝑛(𝛼 + 𝑖𝑖) (15) where, 𝛼 = the angle of attack and 𝑖𝑖 = the engine setting angle. However, for ease of estimation, the following assumptions are made. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 796 (i) For straight and level flight, UAV angle of attack is assumed to be zero. (ii) Also, since the UAV has no engine mounted on it, the engine setting angle is also assumed to be zero. Hence, Equations 14 and 15 becomes. 𝐷 = 𝑇 (16) 𝑊 = 𝐿 (17) Indicating that, for un-accelerated straight and level flight, the conditions in Equations (16). and (17)are true. Therefore, in a steady level flight, when the available power is more than the required power, the UAV will accelerate and vice versa. The required power is a function of airspeed. To have a steady level flight, the lowest amount of energy is required from the power system and this is achieved at the minimum power speed. However, there will be no steady level flight when the power generated produces a velocity that is less than the minimum required power speed 𝑉𝑚𝑖𝑛𝑝which is generally about 30% of the maximum available power (Clark, 2018). The minimum power speed is estimated using the Equation 18, 𝑉𝑚𝑖𝑛𝑃 = √ 2𝑚𝑔 𝜌𝑆√ 3𝐶𝐷0 𝑘 (18) where 𝜌 = density of the air at the cruise altitude which per the case study specification is 10,000 feet. The air density at 10,000 feet from International Standard Atmosphere (ISA) Table is 0.413 0.413 kg/m3. Since for this condition, the thrust produced is equal to the drag generated as a result of forward motion, the minimum power required can be estimated using Equation 19,20, 21 and 21. 𝑃𝑚𝑖𝑛 = 𝑇𝑚𝑖𝑛𝑃 × 𝑉𝑚𝑖𝑛𝑃 = 𝐷𝑚𝑖𝑛𝑃 × 𝑉𝑚𝑖𝑛𝑃 (19) 𝑤ℎ𝑒𝑟𝑒 𝐷𝑚𝑖𝑛𝑃 = 1 2 𝜌10,000𝑉𝑚𝑖𝑛𝑃 2 𝑆(𝐶𝐷𝑂 + 𝑘𝐶𝐿 𝑚𝑖𝑛𝑃 2 ) (20) 𝐴𝑙𝑠𝑜, 𝐶𝐿(𝑚𝑖𝑛𝑃) = √ 3𝐶𝐷𝑂 𝐾 (21) Therefore, substituting equation 21 into Equation 20 yields Equation 22, 𝐷𝑚𝑖𝑛𝑃 = 2𝜌𝑉𝑚𝑖𝑛𝑃 2 𝑆𝐶𝐷𝑂 (22) Using Equation 18, 𝑉𝑚𝑖𝑛𝑃 = √ 2 × 10 × 9.81 [0.413(1.009835)√ 3(0.0109) 0.0446 ] = 10.7716 𝑚𝑠−1 Hence, since the minimum required power velocity for cruise is greater than the stall velocity, it can be concluded confidently that, during steady level flight, the UAV will be able to cruise at the minimum power velocity of 10.7716 𝑚𝑠−1 without stalling. With this condition, the thrust produced is equal to the drag generated because of the forward motion, the minimum power required can be estimated using Equation 19,20, 21 and 22 to obtain http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 797 𝐷𝑚𝑖𝑛𝑃 = 2(0.413)(10.7716) 2(1.009835)(0.0109) = 1.0549 𝑁 Therefore, the minimum power required to sustain the UAV in a steady level flight is calculated from Equation 19 as, 𝑃min = (1.0549) × 10.7716 = 11.3631 𝑊𝑎𝑡𝑡𝑠 2.2.1.4 Determination of Descent Power requirement Here, the velocity will be reducing from the cruise velocity to a new velocity known as the approach velocity until the UAV touches down. The descent procedure is as depicted in Figure 6. Figure 6: Descent process from Cruise phase of flight (Clark 2018) Just like the climb phase which the UAV uses a climb angle to climb, the descent also occurs at a constant angle known as the angle of descent (𝛾). The descent is controlled by varying the power to thrust ratio which is estimated according to (Clark, 2018) to be 10% to 30% of the total power to thrust ratio. However, since the case study UAV is designed to have gliding characteristics due to its wing design, in the absence of power, the UAV will be capable of gliding by taking advantage of the air gradient in a process known as dynamic soaring. In a descending flight, the drag is greater than the thrust and the lift is smaller than the weight. Therefore, if the approach speed is kept constant, the kinetic energy possessed by the UAV will remain constant while the potential energy will decrease due to loss of altitude. Assuming the descent angle is the same as the climb angle, the rate of descent (ROD) can be estimated using equation 23, 𝑅𝑂𝐷 = 𝑉𝑑𝑒𝑠 sin(𝛾) (23) Where, 𝑉𝑑𝑒𝑠 is the UAV approach speed and 𝛾 is the descent angle. Descent velocity for UAVs in the weight category of the case study UAV are estimated in the range of 1m/s to 3 m/s. Therefore, assuming a descent velocity of 3 m/s and a descent angle of 5° degrees. The ROD is estimated to be, 𝑅𝑂𝐷 = 3 sin(5°) = 0.2615 𝑚𝑠−1 http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 798 Therefore, the UAV will have a controlled descent rate of 0.2615 m/s until it touches ground and the power gradually reduced to zero for the UAV to go into a complete rest. Also, assuming a descent thrust of 20% thrust from the cruise thrust at steady level flight, the descent thrust can be estimated as, 𝑇𝑑𝑒𝑠 = 20% 𝑜𝑓 𝑇𝑚𝑖𝑛 (24) Hence for that of the case study UAV, the descent thrust is calculated from equation 24 to be, 𝑇𝑑𝑒𝑠 = 20 100 × 1.0549 = 0.211 𝑁 The power required for descent flight is therefore estimated using the expression (equation 25), 𝑃𝑑𝑒𝑠 = 𝑇𝑑𝑒𝑠 × 𝑉𝑑𝑒𝑠 (25) 𝑃𝑑𝑒𝑠 = 0.211 × 3 = 0.6329 𝑊𝑎𝑡𝑡𝑠 The power required for the UAV to descend and subsequently land is 0.6329 Watts. 2.2.1.5 Landing Landing is the final phase of flight. This phase encompasses the ability of the UAV to safely land on the ground and gradually come to a complete stop prior to a controlled descent. It is the opposite to the take-off performance. Unlike the take-off where the required power is large, landing requires minimum or no power to execute this phase. However, it must be controlled in order not to cause destruction to the structural or avionics components. During descent and landing, the power consumed is generally less compared to take-off and climb phase. MATLAB codes were generated for the performance estimations. 2.2.2 Power Supply To provide the needed power as determined, harnessing of renewable energy from the surrounding environment - solar energy in combination with the installed hydrogen fuel cell is proposed. The UAV will therefore harvest additional energy from the photovoltaic cells spread on its wingspan as well as from the hydrogen fuel cell which converts liquid hydrogen into electrical power via an electrochemical process. The proposed hybrid combination model of the solar cell system and the hydrogen fuel cell system is shown in Figure 7. Figure 7: Proposed Hybrid Energy Harvesting System 2.2.2.1 Solar Energy The photovoltaic cell selected is the monocrystalline solar cell made from a single silicon crystal. Though they are more expensive, they have a higher conversion efficiency rating ranging between 15% to 25%. In other words, they have the ability of converting about 25% of the sunlight absorbed into usable energy (electricity). A monocrystalline solar cell has greater longevity of about 40 years and also characterized by lower http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 799 temperature coefficient which makes it more efficient under heat (Yadav et al., 2019). Figure 8 represents a pictorial view of the monocrystalline solar cells panel. Figure 8: Monocrystalline solar cell. Table 3: Photo voltaic cell specification (Monocrystalline) Parameter Specification Mass of solar cell 4 gm Length and width 78 mm by 77 mm Efficiency of solar cell 18.6% Rated voltage 0.5 V or 0.6 V Rated current 2.1 A The number of solar cells and its arrangement on the Wing are therefore estimated according to the power need of the UAV with respect to the specification given in Table 1. 2.2.2.1.1 Determination solar charge capacity The determination of charge capacity as per the specification of the selected PV cell (Table 3) of which 0.5 V is produced from, requires a combination of cells in series to be able to generate the required voltage that can continuously charge the Li-Po battery with a constant voltage of 22.2 V. Therefore, to obtain the 22.2 V, the number of cells required is estimated to be: 22.2 0.5 = 44.4 𝑐𝑒𝑙𝑙𝑠 𝑎𝑝𝑝𝑟𝑜𝑥𝑖𝑚𝑎𝑡𝑒𝑙𝑦 45 𝑃𝑉 𝑐𝑒𝑙𝑙𝑠. However, due to different type of losses that will be encountered in the course of conversion there is the need to add about 35% more cells to get a voltage above the constant voltage charge of the battery, and since the wing planform area and the span are fixed as per the case study UAV, the cells will be arranged on the planform in a way that will not disrupt the boundary flow. Hence, the estimated number of cells to be used for the generation is, 45 × 0.35 ≅ 15 more cells. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 800 Hence, total number of PV cells are, 45 + 15 = 60 PV cells. Therefore, the ideal total voltage acquired from the solar cells will be, 60 × 0.5𝑉 = 30𝑉 Ideal watt power for the solar cells is expressed as 𝑃𝑠𝑜𝑙𝑎𝑟 = 𝑉𝑠𝑜𝑙𝑎𝑟 × 𝐼 (26) Where 𝐼 is the rated current capacity of the PV cell and 𝑉𝑠𝑜𝑙𝑎𝑟 is the total voltage acquired from the combination of the PV cells. Hence, estimating the solar power from Equation 26 gives. 𝑃𝑠𝑜𝑙𝑎𝑟 = 30 𝑉 × 2.1 𝐴 = 63 𝑊𝑎𝑡𝑡𝑠 Ideally, the solar cells should produce whatever watts of electricity under perfect conditions. But practically, the peak sunshine hours depending on the climatic condition in the region to which the UAV will be operating is factored in the estimation. This makes the output power vary. Hence, solar output power per day is estimated as 75% of the total output capacity. Other losses are considered to be 25%. Assuming a 7-hour sunshine in the northern part of Nigeria, the solar output power will be calculated as; 𝑠𝑜𝑙𝑎𝑟 𝑝𝑜𝑤𝑒𝑟 𝑜𝑢𝑡𝑝𝑢𝑡 = 𝑠𝑜𝑙𝑎𝑟 𝑝𝑜𝑤𝑒𝑟 𝑟𝑎𝑡𝑖𝑛𝑔 × 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑒𝑎𝑘 𝑠𝑜𝑙𝑎𝑟 ℎ𝑜𝑢𝑟𝑠 × 75% 𝑃𝑠𝑜𝑙𝑎𝑟 𝑜𝑢𝑡𝑝𝑢𝑡 = 𝑃𝑠𝑜𝑙𝑎𝑟 × 𝑃𝑒𝑎𝑘 𝑠𝑜𝑙𝑎𝑟 ℎ𝑜𝑢𝑟𝑠 × 75% (27) Therefore, from Equation 27, the solar power is computed as; 𝑆𝑜𝑙𝑎𝑟 𝑝𝑜𝑤𝑒𝑟 𝑜𝑢𝑡𝑝𝑢𝑡 = 63𝑊 × 7ℎ𝑟 × 0.75 = 330.75 𝑊𝑎𝑡𝑡 − ℎ𝑜𝑢𝑟 (𝑊ℎ) Hence, converting the watt-hour to Ampere-hour using Equation 28 yields. 𝑆𝑜𝑙𝑎𝑟 𝐴𝑚𝑝 − 𝐻𝑟 = 𝑊𝑎𝑡𝑡−ℎ𝑜𝑢𝑟 𝑡𝑜𝑡𝑎𝑙 𝑠𝑜𝑙𝑎𝑟 𝑣𝑜𝑙𝑡𝑎𝑔𝑒 (28) 𝑆𝑜𝑙𝑎𝑟 𝐴𝑚𝑝 − 𝐻𝑟 = 330.75 30 = 11.25 𝐴ℎ𝑟 2.2.2.1.2 Determination cells arrangement on wing plan form Examining the size and shape of the wing of the UAV under consideration, the solar cells is divided into two and arranged on the plan form of the wing taking into consideration the dimension of each cell. The plan form area and span of the wing are 0.9724𝑚2 and 4.2𝑚 respectively. Wing is tapered from root to tip. Figure 9. represents the wing under consideration. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 801 Figure 9: Wing geometry of case study UAV Table 4: Wing specifications (AFIT- ALTA 2022) Parameter Specification Span 4.42 m Aspect ratio (AR) 18.14 MAC 0.2418 m Max coefficient of lift 1.38 The solar cells are rectangular in shape due to their dimension which is 78 𝑚𝑚 × 77 𝑚𝑚 in terms of length and width to give: 78 𝑚𝑚 × 77 𝑚𝑚 = 0.078 𝑚 × 0.077 𝑚 𝐴𝑟𝑒𝑎 𝑜𝑓 𝑃𝑉 𝑐𝑒𝑙𝑙 𝑖𝑠 6.006 × 10−3𝑚2 Therefore, as per the estimation, a total of 60 solar cells will be housed on the wing surface of the UAV, covering about 0.3604 square meter which is about 36% of the wing area. Figure 10 shows how the cells are arranged and wired in series to obtain the desired voltage output of 30 volts. The solar cells will be augmented with a Maximum Power Point Tracking solar charger (MPPT) to ensure that, the loads receive maximum current to be used by quickly charging the Li-Po battery and also powering the onboard avionic equipment. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 802 Figure 10: Arrangement and wiring of solar cells on wing surface The CAD model of the solar cell arrangement is created using industrial software which enables the visualization of the arrangement in a virtual environment. The arrangement is made up of multiple solar cells that are connected in series for the desired voltage and current output. Additionally, a robust support structure is designed to hold the solar cells firmly on the wing. This support is transparent enough to allow the cells capture maximum sunlight from the surrounding environment. Figure 11 shows the CAD model of the arrangement of solar cells on the wing planform area of the case study UAV Figure 11: Arrangement and wiring of solar cells on wing surface 2.2.2.2 Hydrogen Fuel Cell System This system is capable of generating electricity through an electrochemical reaction between hydrogen and oxygen which gives off heat and water as by-products. They are clean form of energy with no carbon dioxide emissions or air pollutants that may lead to health issues in humans. They consist of anode, cathode and electrolyte membrane for its operation. When hydrogen passes through the anode, a catalyst splits the hydrogen molecule into protons and electrons. The protons pass through the electrolyte membrane whereas the electrons are forced through a circuit, generating an electric current and excess heat. The hydrogen fuel cell specification for the case study UAV, has the specification shown in Table 5 while Figure 12 is the pictorial view of the hydrogen fuel cell used in the design of the case study UAV. ((AFIT- ALTA 2022). http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 803 Table 5: Hydrogen fuel cell specification H3 Dynamics AEROSTACK A-250 Rated Power (FC) 250 W Voltage 24.5-35.2 V Specific Power 347 W/Kg Start Up time < 20 s Figure 12: Hydrogen fuel cell 2.2.2.3 Hybridization of Solar and Hydrogen Fuel Cells The hybrid combination model of the solar cell system and the hydrogen fuel cell system is shown in Figure 13. Figure 13: Proposed Hybrid Energy Harvesting System Total number of solar cells to be employed in the design is 60. Therefore, combining the two generative systems, the total power that is generated from the hybrid energy system of solar, hydrogen fuel cell and the LiPo battery is obtained using equation 29; http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 804 𝑇𝑜𝑡𝑎𝑙 𝑣𝑜𝑙𝑡𝑎𝑔𝑒 = 𝑉𝑜𝑙𝑡𝑎𝑔𝑒𝑠𝑜𝑙𝑎𝑟 + 𝑉𝑜𝑙𝑡𝑎𝑔𝑒ℎ𝑦𝑑𝑟𝑜𝑔𝑒𝑛 𝑓𝑢𝑒𝑙 𝑐𝑒𝑙𝑙 + 𝑉𝑜𝑙𝑡𝑎𝑔𝑒𝐿𝑖𝑃𝑜 𝑏𝑎𝑡𝑡𝑒𝑟𝑦 (29) 𝑇𝑜𝑡𝑎𝑙 𝑣𝑜𝑙𝑡𝑎𝑔𝑒 = 30𝑉 + 30𝑉 + 22.2𝑉 = 82.2 𝑉𝑜𝑙𝑡𝑠 Considering the weight of each photovoltaic (PV) cell to be 4g, the total weight of the PV cells on the wing surface is therefore estimated to be 240g. In addition, the weight of the maximum power point tracking system (MPPT) to be installed on the fuselage is 1.3 Kg. The above modifications will add to the power requirement of the UAV and therefore forms part of the flight power performance analysis. 2.2.4 Stress Analysis of Wing To confirm that the wing will not fail when the solar cells are placed on its planform, stress analysis was performed on the wing in order to establish the failure index using CATIA and Abaqus software. The CAD model of the wing was developed in CATIA and imported into Abaqus. Material properties were defined, boundary conditions set and load was carefully applied at the selected area. The model was then meshed and analysis ran to see the visual effect. The Tsai-Hill failure criteria was considered for the failure analysis. The criterion considers the interaction between different stress components and its failure mode. When the failure index of the material is 1, it implies the material has reached its maximum strength and can no longer withstand additional stress. 2.2.5 Flight Performance Analysis The aim of the study is to enhance flight performance of the AFIT Post Graduate UAV both in endurance and range by designing an enhanced hybrid energy source that meet its mission profile within the constraints of extraneous factors such as environmental conditions and flight altitude. Performance of an aircraft denotes its characteristics and capabilities at various phases of flight. It encompasses a range of factors such as speed, range, climb rate, maneuverability, take-off and landing distances, payload and fuel efficiency. Therefore, understanding and optimizing aircraft performance is critical for guaranteeing a safe and efficient flight operations, as well as achieving specific mission objectives for different types of aircrafts (Anderson, 2010). MATLAB codes were generated for the performance estimations. 2.2.5.1 Endurance According to (Traub, 2011), for electric powered UAVs, the maximum endurance is estimated using the relation for minimum power and thrust. The condition for maximum endurance is given by Equation 30, 𝐶𝐷0 = 1 3 𝑘𝐶𝐿 𝑚𝑖𝑛𝑃 2 (30) Hence, the maximum endurance is estimated using the Equation 31, 𝐸𝑚𝑎𝑥 = 𝑅𝑡 1−𝑛 ( 𝜂𝑡𝑜𝑡𝑉×𝐶 ( 2 √𝜌𝑆 )𝐶𝐷0 1 4 (2𝑊√ 𝑘 3 ) 3 2 ) 𝑛 𝐻𝑜𝑢𝑟𝑠 (31) 𝐶𝐷0 𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛 𝑓𝑜𝑟 𝑡ℎ𝑒 𝑐𝑎𝑠𝑒 𝑠𝑡𝑢𝑑𝑦 𝑖𝑠, 𝐶𝐷0 = 1 3 (0.0446)(0.8563)2 = 0.0109 where 𝑹𝒕 = the power system hour rating in hours which is assumed to be 1 hour since the discharge time over which small rechargeable battery packs are rated is typically per hour, V = the power system total voltage, C= the energy source capacity in ampere hours, 𝜼𝒕𝒐𝒕 = the total efficiency due to losses in the propulsion system which consist of propeller efficiency, servo motors etc. It is assumed to be 0.8 and n = a discharge parameter which is dependent on the battery type and temperature. Traub (2011) investigated the impact of discharge rate on effective battery capacity by simulating an ideal battery: no Peuket effect using n=1 and n=1.3 (typical for Lithium polymer batteries). http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 805 2.2.5.2 Range Range is an essential performance that determines how far the UAV can fly with its available battery power. This is the maximum distance an aircraft can travel with a full load of fuel tank. However, in the case of UAVs, it is the distance the UAV can travel with its available electric power. Flight range of UAVs in the weight class of 10 Kg can vary significantly depending on the design and purpose of the UAV. Generally, UAVs within this weight class might have flight ranges of around 10 to 50 kilometers on a single battery charge. The range is easily estimated (equation 32) after obtaining the endurance by, R=E×UR (32) Where R = range E = endurance UR= required flight velocity for maximum range of the UAV – equation 33. 𝑈𝑅 = √ 2𝑊 𝜌𝑆 √ 𝑘 𝐶𝐷0 (33) However, since the design cruise velocity was given as part of the specification as 14.3 𝑚𝑠−1, it is used to compute the range to meet the mission profile of the UAV. 3. Results and Discussion 3.1 Power Requirement Power required for the UAV to successfully achieve a complete take-off is estimated using equation 1, 2, 3 and 4 as given in section 2, assuming sea level conditions of density 1.225 kgm−3, and taking the CL,W and S from the case study UAV specification to first obtain the free stream velocity. Therefore, the power required to achieve a complete take-off by clearing the 50 feet obstacle height is 197 watts. The power required for the climb phase is calculated using the equation 13, to obtain 109.99 Watts. For the Cruise Power Requirementthe minimum power required is estimated using equations 18,19, 20 and 21 to obtain DminP = 1.0549 N. Hence, the minimum power required to sustain the UAV in a steady level flight is calculated from equation 18 to obtain Pmin = 11.3631 Watts. Descent power requirement using the descent velocity for UAVs in the weight category of the case study UAV are estimated in the range of 1m/s to 3 m/s. Therefore, assuming a descent velocity of 3 m/s and a descent angle of 5° degrees the ROD is estimated from Equation 22 to be 0.2615 ms−1. Therefore, the power required for the UAV to descend and subsequently land is 0.6329 Watts. The power required for various flight phases are presented in Table 6 and depicted in Figure 14. Table 6: Power requirement Flight Phases Power Required (Watts) Take-Off 197 Cruise 11.3631 Descent 0.6329 Landing is the final phase of flight. This phase encompasses the ability of the UAV to safely land on the ground and gradually come to a complete stop prior to a controlled descent. It is the opposite to the take-off performance. Unlike the take-off where the required power is large, landing requires minimum or no power to execute this phase. However, it must be controlled in order not to cause destruction to the structural or avionics components. During descent and landing, the power consumed is generally less compared to take-off and climb phase. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 806 3.2 Battery Capacity The energy consumed at the various stages of flight varies significantly depending on the size of the UAV, design, payload, the mission requirement, and environmental factors. Considering the critical phases under study which includes take-off, climb and cruise, the individual power consumed at these phases for the case study UAV, are indicated on the mission profile in Figure 14. Figure 14: Mission profile of power required at various phases of flight. From Figure 14, take-off requires a significant amount of power- 17 Watt since the UAV needs to reach a sufficient altitude and velocity to maintain a stable flight. The climb phase is the second largest power (109 Watt) consuming phase of the profile since the UAV continues to use a significant amount of power to reach its desired cruising altitude. Next energy consuming phase is the Cruise phase. The power consumption- 11.363 Watt at this phase is stable as the UAV maintains a constant speed and altitude throughout this phase. During descent (0.6329 Watt) and landing, the power consumed is generally less compared to take-off and climb phase. It is therefore obvious from Figure 14 that the battery must deliver a minimum power of 197 Watts attributable to the takeoff phase to achieve the mission profile of the UAV. 3.2 Flight Performance Analysis The flight power performance of an aircraft encompasses a range of factors such as speed, range, endurance, climb rate, maneuverability, take-off and landing distances, payload, and fuel efficiency- greater speed using less fuel (thrust specific fuel consumption- TSFC), weight and balance. 3.2.1 Endurance Traub, (2011) investigated the impact of discharge rate on effective battery capacity by simulating an ideal battery: no Peuket effect using n=1 and n=1.3 (typical for Lithium polymer batteries) 𝐸𝑚𝑎𝑥 = 1 −0.3 ( 0.8 × 82.2 × 15.23 ( 2 √(0.413)(1.009835) ) (0.0109) 1 4 (2 × 98.1(√ 0.0446 3 )) 3 2 ) 1.3 𝐸𝑚𝑎𝑥 = 16.286 ℎ𝑜𝑢𝑟𝑠 http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 807 Therefore, the maximum endurance that the UAV can go within the permissible assumption made for the solar cells receiving solar energy for seven hours continuous is 16.286 hours for the design weight without payload onboard and 9.025 hours with the design maximum mass. However, since it is also on solar power, the UAV will constantly receive power until the solar radiance reduces in energy when the cells can no longer produce enough energy for continuous power supply. When it happens this way, the hydrogen cell system takes over the power supply chain. This is achieved via a power management system. Hence, for this system it can be concluded that, the UAV will have unlimited endurance provided there is sufficient sunlight available for the PV cells to convert into electrical energy. In the absence of sufficient sunshine, the hydrogen fuel system will power the UAV especially during night operations for about 4 hours to its destination before landing. 3.2.2 Range The range is estimated to be (Equation 32), 𝑅 = 16.286 × 14.3 = 232.891 𝑘𝑚 The range of the UAV will be more than the estimated range provided there is more than 7 hours’ sunlight on the PV cells. However, in the absence of solar power, the UAV will fly for a maximum range of 7.4687 km at a cruise speed of 14.3 meters per second according to initial specification (Table 1). 3.3 Flight Power Analysis The total power capacity that will be generated from both the battery and the solar cells is 11.25 Ah. This will have tremendous boost in the power efficiency of the UAV and also improves it flight endurance and operational capabilities. Despite the challenges of other factors such as environmental conditions and flight altitude, there will be enough power to compensate to overcome such conditions. Power from the solar cells, however, will not be readily available until approximately 7:30 am due to the assumptions made in the estimation (section 2). The battery and the hydrogen fuel cell will provide power within this early hour. Therefore, their power need is distributed between the generating systems during the flight periods with the aid of a power management system. Figure 15 illustrates a graph of power available against power required at various flight phases of the mission profile of the UAV. Figure 15: Power available Versus Power required. After a successful take-off and climb to the maximum altitude, the total available power from the hybrid harvesting system drops from 580 Watts to about 350 Watts. After that big drop, there is a gradual decrease of power within the cruise phase from 350 to 300 Watts. The drop is not as large compared to the drop during the take-off and climb phase. This is because, minimum power is required at the cruise phase of the mission. All things being equal, the power drop remains constant till the end of the flight mission. This is because of the regenerative process of the harvesting system. Figure 16 also shows how the available power generated from the hybrid combination is depleted over the total flight endurance. The power reduces gradually in the mission over time from take-off to landing. 0 100 200 300 400 500 600 700 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 P O W ER A V A IL A B LE ( W ) TIME (HR) POWER AVAILABLE MISSION PROFILE http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 808 Figure 16: Graph of power against time 3.4 Stress Analysis of Wing To confirm that the wing will not fail when the solar cells are placed on its planform, stress analysis was performed on the wing in order to establish the failure index using CATIA and Abaqus software. The CAD model of the wing was developed in CATIA and imported into Abaqus. Material properties were defined, boundary conditions set and load was carefully applied at the selected area. The model was then meshed and analysis ran to see the visual effect. The Tsai-Hill failure criteria was considered for the failure analysis. The criterion considers the interaction between different stress components and its failure mode. When the failure index of the material is 1, it implies the material has reached its maximum strength and can no longer withstand additional stress. 3.4.1 Weight Analysis Under the design constraints on payload due to size, weight and power (SWaP) of both small and micro-UAVs the change in the energy system of the proposed concept led to an increase in the design weight from 5.373 Kg to 6.915 Kg. thereby reducing the maximum payload of the original design by 1.542 Kg. Table 7 shows the various weights of the case study UAV design and the new design. Table 7: Weight comparison of old and new model of UAV Parameters Old design New design Design weight 5.373 Ks 6.915 Kg Payload 4.625 Kg 3.085 Kg Power to weight ratio 2.497 W/N 5.912 W/N Furthermore, the power to weight ratio is estimated (equation 34) for both designs and compared, to ensure that the new design with the new hybrid energy method meet the requirements for the intended use of the UAV. 𝑃𝑜𝑤𝑒𝑟 𝑡𝑜 𝑊𝑒𝑖𝑔ℎ𝑡 𝑟𝑎𝑖𝑜 = 𝑃𝑜𝑤𝑒𝑟 𝑜𝑢𝑡𝑝𝑢𝑡 𝑓𝑟𝑜𝑚 𝑒𝑛𝑒𝑟𝑔𝑦 𝑠𝑦𝑠𝑡𝑒𝑚 𝑊𝑒𝑖𝑔ℎ𝑡 𝑜𝑓 𝑈𝐴𝑉 (34) The power to weight ratio of both designs is far greater than 1 with the proposed hybrid solar system at 5.9 as against 2.5 of the case UAV. This is an indication that, the UAV will have more power available per unit of weight which can result in better performance capabilities. The P/W ratio of the new design is therefore over 100% greater than the P/W ratio of the original design. This gives room for an increase in the payload mass of the UAV. However, this must be done cautiously without compromising other performance parameters. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 809 3.4.2 Wing Stress Analysis The maximum stress that can cause the wing to fail at the root was recorded as 0.39 MPa with a wing failure index of 0.000757. The failure index for a material to fail according to Tsia-Hill criteria is 1. Therefore, having a failure index of 0.000757 indicates that, the pressure loads imposed by the solar cells on wing planform will not cause failure of the wing during it operations. Deflection is very small and has little or no significant impact on the wing. Figures 17 to 19 illustrate the CAD drawings of the wing stress analysis. Figure 17: Stress analysis of the wing of case study UAV Figure 18 shows the stress analysis of the UAV wing. A boundary condition was set at the root section of the wing and pressure loads applied to portions of the wing (Figure 18). A maximum stress of 0.173 MPa was experienced at the root end. This is less than the allowable stress of the composite material used for the wing design, which is 42.27 MPa. Figure 181: Application of pressure loads of solar cells on planform area. http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 810 Figure 19: Stress analysis of wing mounted with solar cells. Figure 19 represents the stress analysis on the wing with the solar cells installed on its planform. From the analysis it was observed that, the maximum stress of 0.39 MPa occurs at the root end of the wing. The area where the cells are concentrated recorded a stress of 0.032 MPa. 3.5 CAD model of the converted UAV with Solar Panel Figure 20 represents a CAD conversion model with the hybrid solar, hydrogen fuel cells energy system mounted. Performance analysis was carried out based on the mission profile of the UAV and compared to other UAVs in the same class including the case study UAV. Some of the findings made with regards to the case study UAV were that, with the amount of power generated, by the harvesting system, the endurance and range of the UAV increased to 16.3 hours and 232.9 Km respectively. Figure 202: CAD model of the converted UAV with Solar Panel 4. Conclusion The Unmanned Aerial Vehicle (UAV) was initially designed with a specified endurance of 4.2 hours and a range of 6 kilometres, powered by a 245-Watt output system. However, the integration of the proposed harvesting model significantly enhanced the performance, generating an output power of 580 Watts based on 7 hours of sunshine. Subsequent performance analysis, tailored to the UAV's mission profile, revealed substantial improvements: 1. Endurance increased by 287% to 16.3 hours 2. Range extended by 3765% to 232.9 kilometres While these enhancements came with a 1.5-kilogram weight penalty, reducing the payload mass from 4.627 kilograms to 3.085 kilograms, stress analysis conducted on the wing using CATIA and Abaqus software ensured the structural integrity of the design. The resulting failure index of 0.000757 confirms the wing's ability to http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4):790-812. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: 811 withstand the added load of the solar cells without compromising its performance. However, considering the evolving landscape of UAV design, with increasing demands for larger payloads and higher altitudes, it is essential to explore additional aerodynamic optimizations beyond power system modifications to further enhance overall UAV performance during flight missions (Wang et al., 2020). Despite the success recorded based on the results presented and discussed, some limitations were observed that needs to be considered in future works on the study. Future work can consider embedding the PV cells into the wing during the wing design phase so that it will flush smoothly with the wing in order to reduce the zero lift drag that will be generated due to the UAV movement. • Experimental validation of the CAD models can be pursued to validate its accuracy. • Computational Fluid Dynamics (CFD) analysis can be conducted to ascertain the flow around the wing of the UAV. References AFIT- ALTA 2022. AFIT Light Trainer Aircraft Project in ALTA Specification Document. 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