Performance Estimation of Fixed-Wing UAV Propulsion Systems
Abstract
:1. Introduction
2. Overall Process
3. UAV Propulsion System
3.1. Propeller Modeling
3.1.1. The Propeller Geometrical Data
3.1.2. Propeller Aerodynamic Coefficients
3.1.3. Blade Element Momentum Theory (BEMT)
3.2. BLDC Motor Modeling
3.3. Modeling of the Electronic Speed Controller
3.4. Battery Modeling
4. Experimental Setup
4.1. Thrust Measurement
4.2. Propeller Rotation Speed Measurement
4.3. BLCD Electrical Power Measurement
5. Computational Fluid Dynamics Analysis
5.1. Computational Fluid Dynamics Model
5.2. Computational Fluid Dynamics Domain
5.3. Computational Fluid Dynamics Mesh
5.4. Computational Fluid Dynamics Results and Validation
6. Results
6.1. Static Performance Validation
6.2. Dynamic Propeller Performance at Different Advance Ratios
6.3. Propulsion System Efficiency
7. Conclusions
- A comprehensive range of and aerodynamic coefficients in the post-stall zone for the propeller was obtained by integrating XFOIL6.94 software with the flat-plate method. This approach successfully accounted for variations in the Reynolds and Mach numbers, enhancing the accuracy of the aerodynamic predictions.
- The proposed propeller sub-model effectively analyzes static and dynamic performance, as well as airflow properties, under the international standard atmosphere (ISA) model. This provides a reliable framework for predicting propeller behavior in various flight conditions.
- A test rig was established to validate the CFD and the BEMT model regarding the static performance. Additionally, this setup can be employed for more dynamic performance investigations based on wind tunnels.
- CFD was successfully employed to evaluate the dynamic performance of the proposed low-computational-power model, confirming its effectiveness for real-time applications.
- An extensive analysis of BLDC motor performance was conducted across a wide range of RPMs, offering insights into load versus electrical power cases not typically supported by manufacturers. This analysis fills a critical gap in the existing knowledge, aiding in more accurate motor selection.
- The proposed model takes into account both the maximum discharge current of the battery and the maximum current of the electronic speed controller (ESC), considering the practical constraints and requirements.
- The compatibility between the motor and the propeller significantly influences the endurance; in this regard, the proposed model computes the total specific thrust as a means to assess the overall propulsion system efficiency.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Battery Voltage | Propeller | RPM | Current (A) | Elec. Power (W) | Mech. Power (W) | Thrust (N) | Total Specific Thrust (g/w) | Endurance (min) |
---|---|---|---|---|---|---|---|---|
11.1V(3 S) 5200 mAh | 3000 | 2.27 | 25.18 | 18.41 | 2.3 | 9.34 | 116.92 | |
4000 | 5.31 | 58.93 | 42.96 | 4.23 | 7.32 | 49.95 | ||
5000 | 10.5 | 116.6 | 82.92 | 6.71 | 5.87 | 25.25 | ||
6000 | 18.59 | 206.39 | 142.05 | 9.77 | 4.83 | 14.26 | ||
7000 | 30.4 | 337.44 | 224.1 | 13.38 | 4.05 | 8.72 | ||
8000 | 46.83 | 519.82 | 332.8 | 17.57 | 3.45 | 5.66 | ||
9000 | 68.88 | 764.57 | 471.91 | 22.32 | 2.98 | 3.85 | ||
3000 | 2.46 | 27.28 | 19.83 | 2.96 | 11.09 | 107.92 | ||
4000 | 5.84 | 64.83 | 46.64 | 5.46 | 8.59 | 45.41 | ||
5000 | 11.69 | 129.72 | 90.49 | 8.69 | 6.83 | 22.69 | ||
6000 | 20.86 | 231.58 | 155.58 | 12.66 | 5.58 | 12.71 | ||
7000 | 34.35 | 381.27 | 246.08 | 17.37 | 4.65 | 7.72 | ||
8000 | 53.23 | 590.81 | 366.19 | 22.82 | 3.94 | 4.98 | ||
9000 | 78.69 | 873.4 | 520.08 | 29.01 | 3.39 | 3.37 |
Battery Voltage | Propeller | RPM | Current (A) | Elec. Power (W) | Mech. Power (W) | Thrust (N) | Total Specific Thrust (g/w) | Endurance (min) |
---|---|---|---|---|---|---|---|---|
11.1V(3 S) 5200 mAh | 3000 | 2.47 | 27.42 | 18.41 | 2.3 | 8.57 | 107.36 | |
4000 | 5.13 | 56.93 | 42.96 | 4.23 | 7.57 | 51.71 | ||
5000 | 9.38 | 104.12 | 82.92 | 6.71 | 6.58 | 28.27 | ||
6000 | 15.67 | 173.92 | 142.05 | 9.77 | 5.73 | 16.93 | ||
7000 | 24.45 | 271.42 | 224.1 | 13.38 | 5.03 | 10.85 | ||
8000 | 36.22 | 402 | 332.8 | 17.57 | 4.46 | 7.32 | ||
9000 | 51.46 | 571.26 | 471.91 | 22.32 | 3.99 | 5.15 | ||
3000 | 2.62 | 29.06 | 19.83 | 2.96 | 10.41 | 101.32 | ||
4000 | 5.52 | 61.25 | 46.64 | 5.46 | 9.09 | 48.06 | ||
5000 | 10.2 | 113.25 | 90.49 | 8.69 | 7.83 | 25.99 | ||
6000 | 17.17 | 190.62 | 155.58 | 12.66 | 6.77 | 15.44 | ||
7000 | 26.96 | 299.26 | 246.08 | 17.37 | 5.92 | 9.84 | ||
8000 | 40.12 | 445.36 | 366.19 | 22.82 | 5.23 | 6.61 | ||
9000 | 57.24 | 635.4 | 520.08 | 29.01 | 4.66 | 4.63 |
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Etewa, M.; Hassan, A.F.; Safwat, E.; Abozied, M.A.H.; El-Khatib, M.M.; Ramirez-Serrano, A. Performance Estimation of Fixed-Wing UAV Propulsion Systems. Drones 2024, 8, 424. https://doi.org/10.3390/drones8090424
Etewa M, Hassan AF, Safwat E, Abozied MAH, El-Khatib MM, Ramirez-Serrano A. Performance Estimation of Fixed-Wing UAV Propulsion Systems. Drones. 2024; 8(9):424. https://doi.org/10.3390/drones8090424
Chicago/Turabian StyleEtewa, Mohamed, Ahmed F. Hassan, Ehab Safwat, Mohammed A. H. Abozied, Mohamed M. El-Khatib, and Alejandro Ramirez-Serrano. 2024. "Performance Estimation of Fixed-Wing UAV Propulsion Systems" Drones 8, no. 9: 424. https://doi.org/10.3390/drones8090424