Micro fixed-wing drones have become indispensable tools in both military and civilian applications due to their compact size, high efficiency, and versatility. In military contexts, these drones excel in stealth reconnaissance, border patrol, and swarm operations. Civilian uses include disaster response, environmental monitoring, precision agriculture, and logistics delivery. The performance of such drones critically depends on the propulsion system, where the propeller plays a central role. A well-designed propeller can significantly enhance endurance, reduce power consumption, and improve overall flight efficiency. This paper presents a systematic study on the aerodynamic characteristics of a propeller tailored for a micro fixed-wing drone, focusing on the trade-off between thrust generation and power efficiency. The goal is to achieve a high-efficiency propeller that meets the thrust requirements while minimizing energy consumption, thereby extending the drone’s flight time.
The micro fixed-wing drone under consideration has a wingspan of approximately 15–20 cm and a total mass of 220 g. It is powered by two electric motors driving two-blade propellers. According to the aerodynamic requirements, each propeller must deliver a thrust of 0.22 N at a cruising speed of 8 m/s. To achieve this, a propeller with a diameter of 178 mm and a hub radius of 10 mm is designed using an advanced high-efficiency design methodology. The blade airfoil is chosen as RAF-6, which exhibits favorable lift-to-drag characteristics at low Reynolds numbers typical for micro fixed-wing drones. The design approach combines blade element theory with an iterative optimization of circulation distribution, ensuring minimum induced losses. In the following sections, I detail the design procedure, present the geometric parameters, and evaluate the performance using computational fluid dynamics (CFD) simulations based on the Multiple Reference Frame (MRF) method.
The design methodology begins with the definition of flight conditions: cruise speed \(V = 8\ \mathrm{m/s}\), rotational speed \(n = 3400\ \mathrm{rpm}\) (corresponding to angular velocity \(\Omega = 2\pi n/60 \approx 356.05\ \mathrm{rad/s}\)), and required thrust \(T = 0.22\ \mathrm{N}\). The propeller radius is \(R = 0.089\ \mathrm{m}\), and the hub radius is \(R_h = 0.01\ \mathrm{m}\). The blade is discretized into 20 sections along the radial direction. At each radial station \(r\), the local chord length \(c(r)\) and pitch angle \(\theta(r)\) are determined by solving the Lagrange multiplier \(K\) and using the optimal induced velocity distribution. The key equations are as follows. The thrust integral is given by:
$$T = \rho \cdot 4\pi V^2 \int_{R_h}^{R} \frac{k_1 + k_2}{1} k_p \, r \, dr$$
where \(\rho\) is the air density (taken as 1.225 kg/m³ at sea level), \(k_p\) is the Prandtl tip-loss correction factor:
$$k_p = \frac{2}{\pi} \arccos\left[ e^{-n \cdot 2 \sqrt{1 – \frac{r}{R}} \sqrt{1 + \left(\frac{\Omega R}{V}\right)^2}} \right]$$
and \(k_1\), \(k_2\) are functions of the induced velocity factor. The dimensionless chord length is expressed as a parabolic distribution:
$$b = \frac{c}{R} = c_1 \sqrt{\beta – [r(i) – m]^2}$$
where \(c_1\) is the maximum chord, \(\beta\) is a chord coefficient, and \(m\) is the radial location of maximum chord. The pitch angle at each section is computed using the flow angle \(\delta\) and the optimum angle of attack \(\alpha_{\text{max}}\) that yields the maximum lift-to-drag ratio. The flow angle is:
$$\delta = \arctan\left[ \frac{\lambda}{\xi_i} (1 + K) \right]$$
with \(\lambda = V/(\Omega R)\) being the advance ratio, and \(\xi_i = r_i/R\) the dimensionless radius. The induced angle is:
$$\alpha_i = \arctan\left( \frac{K \sin\delta \cos\delta}{1 + K \cos^2\delta} \right)$$
The local dimensionless resultant velocity is:
$$\hat{V}_E = \sqrt{1 + \left(\frac{\xi_i}{\lambda}\right)^2} \cos\alpha_i$$
Using Xfoil 6.96, the RAF-6 airfoil is evaluated at Reynolds numbers ranging from 10,000 to 50,000 and Mach numbers below 0.1. The optimum angle of attack is found to be 4°, giving a lift coefficient \(C_{l,\text{max}} = 0.85\) and a drag coefficient \(C_{d,\text{max}} = 0.012\). The pitch angle is then set as \(\theta = \delta + 4°\). The resulting chord and pitch angle distributions are summarized in Table 1.
| Radial station r/R | Chord c (mm) | Pitch angle θ (°) |
|---|---|---|
| 0.15 | 8.2 | 42.3 |
| 0.25 | 10.5 | 35.1 |
| 0.35 | 12.1 | 29.4 |
| 0.45 | 12.8 | 24.8 |
| 0.55 | 12.5 | 21.0 |
| 0.65 | 11.4 | 17.7 |
| 0.75 | 9.8 | 14.9 |
| 0.85 | 7.5 | 12.3 |
| 0.95 | 4.6 | 10.0 |
The three-dimensional model of the propeller is constructed in CATIA using these parameters. The blade shape features a smooth twist from root to tip, with the chord first increasing then decreasing, typical of an efficient propeller designed for low-speed fixed-wing drones.
To evaluate the aerodynamic performance, a CFD model is built using the MRF approach. The computational domain consists of a stationary outer region and a rotating cylindrical inner region containing the propeller. The mesh is generated in three blocks with increasing refinement near the blade surface. A grid independence study is conducted at zero freestream velocity and 2600 rpm. The results are listed in Table 2.
| Mesh size (million) | Thrust (N) | Torque (N·m) |
|---|---|---|
| 0.40 | 0.3598 | 0.0065 |
| 1.10 | 0.3534 | 0.0060 |
| 1.50 | 0.3429 | 0.0058 |
Since the differences are small and computational cost increases with mesh size, a mesh of 1.1 million cells is selected for subsequent simulations. The solver uses the standard k-ε turbulence model with wall functions. Boundary conditions: velocity inlet (freestream speed), pressure outlet, and rotation applied to the propeller blade surfaces via the MRF zone. Simulations are performed at five freestream velocities: 2, 4, 6, 8, and 10 m/s, and five rotational speeds: 3000, 3200, 3400, 3600, and 3800 rpm. The thrust, torque, power, and efficiency are extracted. Power is computed as \(P = Q \cdot \Omega\), and efficiency is \(\eta = T V / P\).
The comprehensive results are presented in Tables 3–6. Table 3 shows thrust values in Newtons.
| V (m/s) | 3000 rpm | 3200 rpm | 3400 rpm | 3600 rpm | 3800 rpm |
|---|---|---|---|---|---|
| 2 | 0.412 | 0.468 | 0.527 | 0.589 | 0.654 |
| 4 | 0.341 | 0.392 | 0.445 | 0.501 | 0.560 |
| 6 | 0.278 | 0.322 | 0.369 | 0.419 | 0.472 |
| 8 | 0.221 | 0.258 | 0.237 | 0.342 | 0.390 |
| 10 | 0.170 | 0.200 | 0.233 | 0.269 | 0.308 |
Table 4 contains torque in N·m.
| V (m/s) | 3000 rpm | 3200 rpm | 3400 rpm | 3600 rpm | 3800 rpm |
|---|---|---|---|---|---|
| 2 | 0.0095 | 0.0108 | 0.0122 | 0.0137 | 0.0153 |
| 4 | 0.0082 | 0.0094 | 0.0106 | 0.0120 | 0.0134 |
| 6 | 0.0071 | 0.0081 | 0.0092 | 0.0104 | 0.0117 |
| 8 | 0.0061 | 0.0070 | 0.0080 | 0.0091 | 0.0102 |
| 10 | 0.0052 | 0.0060 | 0.0069 | 0.0079 | 0.0089 |
Power consumption in Watts is given in Table 5.
| V (m/s) | 3000 rpm | 3200 rpm | 3400 rpm | 3600 rpm | 3800 rpm |
|---|---|---|---|---|---|
| 2 | 2.985 | 3.620 | 4.344 | 5.167 | 6.091 |
| 4 | 2.576 | 3.148 | 3.775 | 4.524 | 5.336 |
| 6 | 2.231 | 2.716 | 3.277 | 3.924 | 4.659 |
| 8 | 1.917 | 2.348 | 2.848 | 3.432 | 4.062 |
| 10 | 1.635 | 2.011 | 2.458 | 2.979 | 3.543 |
The propeller efficiency η (in percentage) is compiled in Table 6.
| V (m/s) | 3000 rpm | 3200 rpm | 3400 rpm | 3600 rpm | 3800 rpm |
|---|---|---|---|---|---|
| 2 | 27.6 | 25.9 | 24.3 | 22.8 | 21.5 |
| 4 | 53.1 | 49.8 | 47.2 | 44.3 | 42.0 |
| 6 | 66.5 | 63.6 | 60.5 | 57.2 | 54.2 |
| 8 | 68.6 | 66.1 | 66.63 | 59.8 | 57.9 |
| 10 | 64.7 | 63.0 | 60.8 | 58.5 | 56.1 |
Analysis of the data reveals several important trends for fixed-wing drones. As freestream velocity increases, thrust decreases for a given rpm due to reduced angle of attack. Simultaneously, power decreases because torque drops. Efficiency first increases with velocity, reaches a peak, and then declines at higher speeds. For the targeted thrust of 0.22 N, the operating point at V=8 m/s and n=3400 rpm yields a thrust of 0.2372 N, which is close to the requirement, with a power consumption of only 2.848 W and an efficiency of 66.63%. This combination is therefore the optimal cruise condition for the micro fixed-wing drone. The efficiency map shows that between 6 and 8 m/s and 3000–3800 rpm, the efficiency stays above 60%, indicating a wide operational envelope. At lower speeds (2 m/s), efficiency is poor due to high induced drag; at very high speeds (10 m/s), efficiency drops as the blade sections approach stall. The designed propeller is thus well suited for the intended flight regime of fixed-wing drones.
The pressure and velocity distributions on the blade surface at the design point (V=8 m/s, n=3400 rpm) are also examined. The suction side experiences low pressure near the leading edge, generating thrust. The resultant velocity iso-surfaces show smooth flow without significant separation, confirming the blade’s efficient design. The MRF method proved effective in capturing the rotary effects with reasonable computational cost, making it suitable for iterative design cycles.
Furthermore, the impact of varying rotational speed was investigated. For a given velocity, thrust increases nearly linearly with rpm, while torque shows a similar trend. Power increases with the cube of rpm approximately, which underscores the importance of selecting the correct rpm to avoid excessive energy consumption. The efficiency curves indicate that each speed has an optimum rpm that balances thrust and power. For the micro fixed-wing drone, the design point at 3400 rpm not only meets the thrust requirement but also operates near the peak efficiency region.
To provide a broader perspective, the results are compared with theoretical predictions from the design code. The computed thrust at the design condition (0.2372 N) is about 7.8% higher than the target 0.22 N, which is acceptable. This slight overshoot can be attributed to viscous effects and three-dimensional flow not fully captured in the analytical model. The efficiency of 66.63% is consistent with high-performance propellers for fixed-wing drones of this scale. Comparable studies in literature report efficiencies between 60% and 70% for similar micro propellers. The designed propeller thus demonstrates competitive performance.
In conclusion, this study has successfully designed and analyzed a high-efficiency propeller for a micro fixed-wing drone. Through systematic application of an advanced design methodology and CFD simulation, the following key outcomes are achieved:
- The propeller geometry with RAF-6 airfoil, chord and twist distribution tailored for low Reynolds number flight.
- Comprehensive performance data across 25 flight conditions, enabling selection of optimal operating point.
- At V=8 m/s and n=3400 rpm, the propeller produces 0.2372 N thrust with 2.848 W power and 66.63% efficiency, meeting the drone’s requirements.
- The MRF-based CFD approach provides reliable predictions for engineering design.
The findings offer valuable guidance for the development of efficient propulsion systems for fixed-wing drones. Future work can explore multi-blade configurations, composite materials, and higher Reynolds number regimes to further improve performance. The methodology presented here can be readily adapted to other micro fixed-wing drone platforms, contributing to longer endurance and broader mission capabilities.