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Rotor Blade Optimization and Flight Testing of a Small UAV Rotorcraft
Journal: Journal of Unmanned Vehicle Systems
Manuscript ID juvs-2017-0005.R2
Manuscript Type: Article
Date Submitted by the Author: 12-Mar-2019
Complete List of Authors: Kotwicz Herniczek, Mark; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace EngineeringJee, Dustin; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace EngineeringSanders, Brian; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace EngineeringFeszty, Daniel; Carleton University Faculty of Engineering and Design, Mechanical and Aerospace Engineering
Keyword: UAV, Rotorcraft, BEMT, Optimization
Is the invited manuscript for consideration in a Special
Issue? :Not applicable (regular submission)
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Rotor Blade Optimization and Flight Testing of a Small UAV Rotorcraft
Mark Kotwicz Herniczek ∗
Research Associate
Dustin Jee
Research Associate
Brian Sanders
Research Associate
Daniel Feszty
Adjunct Professor
Department of Mechanical and Aerospace Engineering, Carleton University
Ottawa, ON, Canada
Abstract
Rotor blade optimization with blade airfoil Reynolds numbers between 100,000 and 500,000 - characteristic of small
single-rotor Unmanned Aerial Vehicles (UAV) - was performed for hover using Blade Element Momentum Theory
(BEMT) and demonstrated via flight tests. BEMT was used to test various airfoil profiles and rotor blade shapes
using airfoil data from 2D computational fluid dynamics simulations with Reynolds numbers representative of the
blade elements. Selected blade designs were manufactured and flight tested on a Blade 600X single main-rotor UAV
(671 mm blade radius) to validate the theoretical results. The parameters considered during the optimization process
were the rotor frequency, radius, taper ratio, twist, chord length, airfoil profile and blade number. The best of the
improved blade designs increased the figure of merit, a measure of rotor efficiency, from 0.31 to 0.68 and reduced power
consumption by 54%. Reducing the rotational frequency accounted for 45% of the improvement in power consumption,
while the taper ratio and blade number accounted for 25% and 17% respectively. The blade twist and airfoil profile only
had a minor effect on the power consumption, contributing 7% and 6% to the improvement. The rotor diameter and
root chord were kept identical to the original rotor and hence had no contribution. The presented results could serve as
useful guidelines to single-rotor UAV manufacturers and operators for increasing endurance and payload capabilities.
Nomenclature
Cd section drag coefficient
Clα section lift-curve slope
CP rotor power coefficient
CT rotor thrust coefficient
F Prandtl’s tip-loss function
FM figure of merit
kx longitudinal linear induced inflow coefficient
ky lateral linear induced inflow coefficient
LD section lift coefficient
P rotor power (Pinduced + Pprofile)
∗Corresponding author (email: [email protected])
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Q rotor torque
r non-dimensional radial distance
R blade radius
Re Reynolds number
T rotor thrust
vi induced velocity
vtip tip velocity
y+ non-dimensional wall distance
Ω rotor rotational frequency
αTPP tip path plane angle of attack
λ total rotor inflow ratio through disk
λh rotor inflow ratio in hover
λi induced rotor inflow ratio
µx advance ratio parallel to tip path plane
µz advance ratio perpendicular to tip path plane
σ rotor solidity
1 Introduction
The use of Vertical Takeoff and Landing (VTOL) vehicles for Unmanned Aerial Vehicle (UAV) missions has grown
exponentially in recent years. Although rotorcraft with fixed pitch rotors - such as quadcopters - have become extremely
popular in the last few years, they are best suited for hover dominated missions with relatively small payloads. For
missions requiring heavier payloads and longer endurance, single-rotor vehicles with controllable blade pitch are more
efficient and thus better suited (Leishman 2006).
The market for single main-rotor UAVs has remained widely divided between the military and commercial sectors,
especially in terms of performance and cost. Military rotorcraft are typically designed for heavier payloads (within the
range of 30 - 200 kg) and are unavailable to the public. On the other hand, commercial single-rotor UAV operators
often utilize smaller, less expensive rotorcraft with lighter payloads (2-10 kg) - many of which are based on off-the-shelf
radio controlled (RC) helicopters with a rotor radius of around 1 m. For these missions the key components of the
UAV - such as the rotor and the drive system - are typically reused in unchanged form. However, commercial RC
helicopter rotors have not been designed for maximizing mission requirements critical for commercial UAV operators,
such as range, endurance or payload. Instead, they have been developed with the primary purpose of conducting short
duration high-performance aerobatic flights. To allow for aerobatic flight a symmetrical airfoil and very high RPM is
necessary, qualities that don’t align with the extended periods of hover typically seen in commercial UAV missions. As
will be demonstrated later in this paper, the endurance of a typical RC helicopter used for UAV missions is only 5-8
minutes long while its hovering efficiency - expressed in terms of the Figure of Merit (FM) - is only around 30%. This
is in sharp contrast to the 80% value observed for manned helicopters (Leishman 2006).
There are a number of differences between typical single-rotor UAVs and manned helicopters that explain these
discrepancies. The rotor blades used in typical unmanned rotary vehicles experience a much smaller Reynolds number
compared to full-scale manned helicopters due to their smaller size. This results in a reduction of the maximum lift-to-
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drag ratio and an early onset of stall (Selig et al. 1995, Anyoji et al. 2014, Kotwicz Herniczek et al. 2016). Additionally,
while full-scale manned helicopters often feature twisted, tapered blades with cambered airfoils, most UAV blades have
no twist, taper nor any airfoil camber. Furthermore, no evidence has been found in the literature that the currently
applied blade number or the rotational frequency of rotors has been optimized for single-rotor UAVs.
Although full scale rotor optimization has been widely studied (Hassan & Charles 1997, Allen & Rendall 2001,
Tatossian & Nadarajah 2011, Leishman & Ananthan 2008, Lee et al. 2010, Leishman 2009, Lee & Kwon 2006) and
low Re airfoils have been developed for aircraft using discrete methods (Selig & Guglielmo 1997, Pfenninger & Vemuru
1988), research regarding small-scale UAV rotor optimization and the manufacturability of those rotors is not evident
in the literature. Some research has been performed at the Micro Air Vehicle (MAV) scale (Bohorquez et al. 2010),
however, the range of Reynolds numbers in this paper are an order of magnitude higher and thus the optimized
rotor blades are likely to be very different. Research has also been published for scaled co-axial rotors, however, the
aerodynamics and optimization involved also differ significantly (Prior & Bell 2011).
The purpose of this paper is therefore to examine whether the efficiency of a 600-class UAV (600 mm nominal rotor
radius), representative of a standard commercial single-rotor UAV, can be improved while maintaining cost-effective
manufacturability of the optimized blades. The paper aims to demonstrate these improvements computationally as
well as through flight tests. UAV developers and operators may be able to use results from this paper to increase the
performance of small (approx. 1 m rotor diameter), single-rotor UAVs.
2 Methodology
The Blade 600X single-rotor UAV (Figure 1), with a rotor radius of 671 mm, was chosen as the test platform due to
the popularity of this category (600–800 class) of aircraft among UAV operators. A 600-class helicopter was selected
instead of the more common 700-800 class helicopters due to its greater ease of use, lower price-point and comparable
the aerodynamics to the 700-800 class rotors.
The main technical parameters of the Blade 600X are shown in Table 1. The stock blades use a NACA 0012 airfoil
and do not feature any twist or taper.
The baseline performance of the UAV was determined through flight testing. A computational method was then
developed by using Computational Fluid Dynamics (CFD) for airfoil section data generation and Blade Element
Momentum Theory (BEMT) for blade optimization. The use of CFD was necessitated by the lack of low Reynolds
number 2D airfoil data needed for the BEMT optimization routine. The CFD method was validated using low Reynolds
number wind tunnel data for the NACA 6409 airfoil from Selig et al. (1995), while the BEMT code was validated using
test cases provided by Leishman (2006) as well as by comparing it to the baseline flight test data. This computational
method was then used to arrive at new rotor geometry and rotor frequency optimized for endurance and range.
Once the new blade geometry had been defined, the design was assessed to ensure the complexity of the geometry did
not surpass the capabilities of the manufacturing process and Finite Element Analysis (FEA) was used to evaluate the
feasibility of the structural design. The vetted design was then manufactured and flight tested using an instrumented
Blade 600X UAV. In the following sections, details of the CFD method, the BEMT code utilized, as well as the UAV
instrumentation and flight test results are described. Blade optimization was also performed for forward flight, however,
these results are presented to a limited extent due to the scope of the paper, which focuses on demonstrating efficiency
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improvements in hovering flight.
3 2D Airfoil Data Development
Since BEMT discretizes the rotor blade into two dimensional elements, 2D airfoil data for blade sections along the rotor
at the corresponding Reynolds and Mach numbers is required to yield accurate results. For a rotor with a 671 mm
radius and 2,000 RPM, the tip speed is only around Mach 0.4 (at standard sea level conditions), while the Reynolds
number along the blade varies between 0 at the root and 500,000 at the tip. Although there have been significant
efforts to produce airfoil data for Reynolds numbers within this range (Selig et al. 1995, 1996, Lyon et al. 1998, Selig
& McGranahan 2004, Williamson et al. 2012), low Reynolds number airfoil data remains very limited relative to data
suited for full-scale helicopter applications, i.e. in a range between 3 million and 9 million. Since an airfoil’s stall
characteristics and flow behaviour can differ significantly at low Reynolds numbers, use of CFD was necessary to
generate the relevant data.
CFD simulations were performed using ANSYS CFX and the airfoil geometry was modeled in ANSYS ICEM. Only
an overview of the key findings regarding verification and validation are provided here; refer to Kotwicz Herniczek et al.
(2016) for further details of the CFD validation.
For the verification and validation of the method, a set of test cases from Selig et al. (1995) consisting of a NACA
6409 airfoil exposed to a freestream with a Mach number of 0.03 (corresponding to a Reynolds number of 200,000)
was chosen. The outcome of this process was the identification of a minimum density mesh for the simulations, which
consisted of 92,014 elements (61,092 nodes) and a first spacing off the wall of 0.001c (y+ ∼ 0.5). It was found that the
best comparison with experiment was obtained when a transitional Shear Stress Transport (SST) turbulence model
was used, suggesting that the flow transitioned from a laminar to turbulent regime near the trailing edge of the airfoil.
These numerical parameters were used for all simulations presented in this paper, and served as an input to the BEMT
optimization routine.
3.1 Low Reynolds Number CFD Data for Selected Airfoils
The Blade 600X UAV uses a symmetric NACA 0012 airfoil. While appropriate for aerobatic flights for which the Blade
600X was designed, this airfoil is not ideal for flight missions typical of commercial UAVs, such as high payload hover or
forward flight. Since the blades operate at low Reynolds number (<500,000) and low Mach number (<0.4) conditions,
airfoils that are used on the blades of full-size helicopters are equally sub-optimal.
The following airfoils, shown in Figure 2, were selected to be tested and used during the blade optimization process:
E387, S7055, NACA 0012, NACA 0009, NACA 2409, NACA 4409, NACA 6409 and NASA RC(4)-10. The first two
airfoils, E387 and S7055, are sailplane airfoils for which experimental airfoil data is available in a study by Selig et al.
(1995) at the University of Illinois at Urbana-Champaign. The four NACA series airfoils with 9% thickness and camber
varying from 0 to 6% (similar thickness and camber to low Reynolds number airfoils) were selected to explore the
potential of using standard NACA airfoils for low Reynolds number applications. Thicknesses below 9% were not
considered owing to blade manufacturing, balancing, and stiffness concerns. The last airfoil, NASA RC(4)-10, is used
on full-size helicopters and was chosen for comparison purposes.
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Low Reynolds number lift and drag data produced by CFD for the five NACA series airfoils considered are included
in Figures 3a and 3b. As expected, a thinner airfoil will have a lower drag coefficient but will experience stall earlier.
Camber increases the maximum lift-to-drag ratio from 40 for the NACA 0012 and NACA 0009 to 47, 51 and 52 for the
NACA 2409, NACA 4409 and NACA 6409 respectively. These are are achieved at angles of attack of 8.3, 6.9, 6.3,
5.7 and 4.7 for the NACA 0012, NACA 0009, NACA 2409, NACA 4409 and NACA 6409.
4 Blade Element Theory
The concept of Blade Element Theory (BET) allows for an estimation of the performance of a rotor for both hover and
forward flight. The greatest challenge for implementing this method is to express the inflow velocity along the blade.
In hover, this can be done by combining BET with Momentum Theory, while in forward flight, semi-empirical methods
need to be involved due to the complexity of aerodynamics and blade dynamics.
4.1 Hover
Blade Element Theory discretizes the rotor blade such that each finite element can be considered as a two-dimensional
airfoil for which aerodynamic forces and moments can be determined. These sectional loads can then be integrated
over the blade span and averaged over one rotor revolution to estimate overall rotor performance (Leishman 2006).
Momentum Theory (necessary to calculate the inflow velocity, vi) models the rotor of the UAV as an infinitely thin,
one-dimensional disk and applies conservation of mass, momentum and energy to the control volume surrounding the
rotor and its wake.
Combining both methods, the non-uniform inflow (in hover) along a rotor blade can be estimated using BEMT as:
λh(r) =vi(r)
vtip=
√σClr
8F(1)
Once the inflow ratio is known, Eqs. (2) and (3), describing the discretized thrust and power of the rotor can be
integrated and used to assess rotor efficiency considering rotor twist, airfoil shape and sectional orientation.
dCT =1
2σClr
2dr (2)
dCP = dCTλh +1
2σCdr
3dr (3)
The sectional lift and drag coefficients (Cl and Cd) in the above equations are obtained from the CFD simulations
described previously.
Figure of Merit, the ratio of ideal to actual power consumption and a measure of the aerodynamic efficiency of a
helicopter can then be calculated using Eq. (4). The induced power is associated with the lift required to hover while
the profile power corresponds to the power required to overcome rotor drag. Ideal power is entirely induced in nature
but ignores losses due to non-uniform inflow, es, wake swirl and non-ideal wake contraction (Leishman 2006).
FM =Pideal
Pinduced + Pprofile=
C3/2T /√
2∑dCTλh + 1
2
∑σCdr3dr
(4)
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To improve the stability of the BEMT implementation, a relaxation scheme was applied to the iteration process
used to find the local Angle of Attack (AOA). Additionally, an initial value for the AOA was estimated by using a Clα
of 2π and equations based on the lift curve slope were used for the first iteration rather than those based on Cl. A
detailed description of the theory, assumptions and equations used in BEMT can be found in Leishman (2006).
4.2 Forward Flight
Blade motion becomes considerably more complex in forward flight with factors such as blade flapping, compressibility
effects and blade stall having a significant effect on results. Additionally, the flow can no longer be assumed to be
axisymmetric and therefore cannot be estimated using BEMT and requires discretization along the azimuthal direction.
As a result, Blade Element Theory coupled with some simplifying assumptions (including an estimation of the inflow)
need to be applied in order to obtain the performance parameters of a rotor in forward flight. Drees’ linear inflow
model, given in Eq. (5), was used to approximate the inflow in forward flight, where kx and ky are model coefficients.
The blade dynamics of a fully articulated rotor were used to approximate the dynamics of the rigid (hingeless) Blade
600X helicopter.
λi(r, ψ) = λiavg (1 + kxr cosψ + kyr sinψ) (5)
The induced inflow in forward flight can be calculated following momentum theory for forward flight developed by
Glauert (Johnson 1994):
λiavg =CT
2√µ2x + λ2
(6)
where the total inflow, λ is given by:
λ = µz + λiavg (7)
The advance ratios µx and µz quantify the incoming flow parallel and perpendicular to the rotor plane and are
defined as:
µx = V∞cosαTPP
ΩR(8)
µz = V∞sinαTPP
ΩR(9)
A detailed description of the theory, assumptions and equations used in the development of the Blade Element
Theory code used to produce the forward flight results presented in this manuscript can be found in Wiebe (2015)
5 Rotor Optimization
In the following sections, the effects of key parameters (UAV mass, rotor frequency, blade geometry, etc.) on UAV
performance are presented. All results in this section were obtained using BEMT.
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5.1 Helicopter Mass Selection
From Table 1, the baseline UAV mass is 3.84 kg. However, for the purposes of this paper, the UAV mass was fixed
to 5.0 kg, allowing for a 1.16 kg mass for instrumentation and a simulated payload representative of a high resolution
camera. At the end of the optimization process and during flight testing, the mass was varied to estimate the maximum
payload. Since the Blade 600X UAV is limited by the motor characteristics (more specifically the motor’s maximum
power) rather than blade stall, it is possible to design a rotor which increases range, endurance and FM while also
increasing maximum payload. This is attainable by reducing the power requirement of the rotor configuration through
RPM control and blade design. Since a 1.16 kg payload is typically sufficient, the blade design was optimized for
increased endurance and range with this payload in mind.
5.2 Rotor Rotational Frequency Selection
Lowering the rotational frequency of the main rotor considerably decreases the power required to hover and increases
FM. Figure 4a illustrates this relationship for the baseline rotor configuration (NACA 0012 airfoil, zero twist and
taper). One should note the baseline rotational frequency of main rotor of the UAV is recommended to be 2,000 RPM,
however, this rotational frequency is only necessary for aerobatic maneuvers and a lower rotor frequency is suitable for
regular operation.
An additional benefit of decreasing the rotor frequency is that it brings the blade AOA closer to the optimal lift-to-
drag ratio when flown with a UAV mass of 5.0 kg. This relationship is demonstrated in Figure 4b for the baseline rotor
configuration which theoretically has a maximum L/D ratio that occurs at a rotational frequency below 1,000 RPM
at an AOA of 8.3. Although minimizing the RPM to the optimal lift-to-drag ratio is desirable, a rotor frequency of
1,500 RPM was selected due to instability observed during low RPM flight testing. Loss of stability was characterized
by a slight wobble of the UAV in the pitch and roll axis for both hover and forward flight. Since flight testing was
performed indoors to avoid the time commitment of obtaining a Special Flight Operations Certificate (SFOC), further
lowering the RPM risked crashing the UAV due to the confined, low altitude nature of the flights. Reducing the rotor
frequency from 2,000 RPM to 1,500 RPM increased FM by 55% and reduced the power required to hover by 36%.
The instabilities observed at 1,500 RPM were unexpected given that RC helicopters of similar scale have been known
to attain head speeds as low as 1000 RPM. Reasons for this behavior may include the increased mass of the helicopter
due to the simulated payload, sub-optimal tuning of the flybarless control system, or overly stiff head dampers. If
instability had not occurred, RPM would have been reduced within a margin of safety of stall conditions.
5.3 Rotor Radius Selection
A large rotor radius, coupled with low RPM is generally desirable to lower the power requirement of the vehicle. This
can be observed in Figure 4c which illustrates the effects of rotor radius on FM and required power considering the
baseline rotor configuration. Figure 4d also demonstrates that increasing the rotor radius would not be beneficial at the
given payload of 1.16 kg unless the rotor frequency is decreased below 1,500 RPM. Since increasing the rotor diameter
would require significant alteration to the frame of the UAV and instability was observed at rotor frequencies below
1,500 RPM, the original 671 mm blade length was maintained. A smaller blade radius could theoretically increase the
blade efficiency or FM by bringing the blade AOA closer to the optimal L/D ratio, however, it would also significantly
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increase the power consumption of the UAV.
5.4 Airfoil Chord Length Selection
If blade taper is not considered, a significant performance improvement can be obtained by reducing the chord length due
to the associated decrease in solidity and the shift in the blade AOA which brings it closer to the angle corresponding to
the maximum L/D ratio. However, if a taper ratio is introduced, a much less significant reduction in chord is necessary
to minimize the required power to hover. This relationship is shown in Figure 4e (NACA 0012 airfoil with no twist
operating at 1,500 RPM) where it can be observed that the optimal chord length is significantly affected by the taper
ratio. Ideally a combination of taper ratio and chord reduction would be utilized, however, reducing the chord was not
feasible considering the materials and blade balancing methods utilized for the production of the rotor (i.e. further
reduction in the chord would leave insufficient thickness at the leading edge of the rotor to add balancing ballast and
result in insufficient blade stiffness). As such, the blade root chord length was kept at 55 mm. A decrease in solidity
and a shift in the AOA was instead achieved with either taper, a reduction in the blade number (i.e. single-blade with
counterweight design), or a combination of both.
5.5 Airfoil Selection
A variety of airfoils (shown in Figure 2) were considered in order to understand the effect of thickness, camber and
shape on the lift and drag characteristics of the airfoil. As can be observed from Figures 3a and 3b, increasing the
camber shifted the lift curve slope upwards while also increasing drag. Conversely, reducing the airfoil thickness had
negligible effect on lift but significantly reduced drag (note that the camber and thickness of NACA 4-series airfoils are
specified by the first and last two digits of the airfoil name, respectively). Airfoils thinner than the NACA 4409 were
not considered to ensure sufficient blade thickness for blade balancing and structural stiffness. From the CFD studies
described earlier, the NACA 4409 and NACA 6409 airfoil were found to have the best lift-to-drag ratios, occurring at
5.7 and 4.7 respectively. Ultimately the NACA 4409 airfoil was selected for its sightly better performance at the
operating AOA of the final blade design, however, both airfoils performed similarly. Implementing the NACA 4409
airfoil into the design resulted in a 5.1% and 4.9% improvement in FM and power consumption relative to the NACA
0012.
The full-scale helicopter-specific airfoil (NASA RC(4)-10) performed poorly as expected since its transonic profile
is not designed for low speed and low RPM flight. This further emphasizes that the low Reynolds number environment
calls for special solutions for small rotorcraft UAVs.
5.6 Taper Selection
While a hyperbolic taper theoretically results in a minimal profile power by maximizing the lift-to-drag ratio (Leishman
2006), blade design was limited to a linear taper to facilitate the manufacturing and blade balancing process. For
simplicity, only a constant taper ratio along the blade was considered. Results for the NACA 4409 airfoil (no twist)
operating at 1,500 RPM for taper ratios between one (constant chord) and four are presented in Figure 4f. It should
be noted that the planform geometry was determined such that the thrust-weighted solidity of the rotor remained
constant. As expected, introducing taper reduced the required power and increased FM as the AOA approaches an
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optimal lift-to-drag ratio. From the presented results, it can be observed that the optimal taper ratio for hover is likely
greater than 4:1. The taper ratio for forward flight is generally restricted to avoid loss of lift on the retreating blade.
In this application, the tip velocity is well below the speed of sound and the forward flight speed is small (∼10 m/s).
Therefore the optimal taper ratio for forward flight is also higher than 4:1. Due to manufacturing constraints and the
limitations of materials such as wood, a taper ratio of 2:1 was chosen to avoid an overly thin tip which could fracture
during the machining process or undergo aeroelastic deformation during flight. At constant thrust-weighted solidity a
taper ratio of 2:1 improves FM and power consumption by 4.9% and 4.7%, respectively. If the weighted solidity is not
kept constant, FM is increased by 21% and power consumption is reduced by 17% (at a taper ratio of 2:1).
5.7 Twist Selection
Minimizing the induced power requires uniform inflow over the rotor disk, which is obtained with a hyperbolic twist
distribution along the blade known as ‘ideal twist’. To avoid divergence of the pitch angle at the root, linear twist is
typically used near the root while ideal twist can be used at the tip (Leishman 2006). A combination of linear and ideal
twist was considered during the optimization process. Both the root pitch angle and the location where linear twist
transitioned to ideal twist were varied. Results for hover and forward flight (presented in Figure 10) were as expected,
with hovering flight having an optimal root pitch around 30 and forward flight (10 m/s forward speed and 5 rotor
tilt) having an optimal root pitch of 10. A lower root pitch angle is desirable in forward flight to avoid loss of lift and
propulsive efficiency on the advancing blade (Leishman 2006). The optimal transition point from linear to ideal twist
for both hover and forward flight was found to be 50% of the blade length from the root. Section 10 represents results
for a rotor with a NACA 4409 airfoil with no taper and with a transition from linear to ideal twist at 50% of the blade
length operating at 1,500 RPM.
Since the majority of the flight time of rotary UAVs is usually dedicated to hovering flight, a root pitch angle of 15
was chosen for the initial blade design, resulting in a 7.6% increase in the FM and 7.1% power reduction for hovering
flight without noticeably affecting forward flight. If an RUAS operator has a mission profile consisting of mostly forward
flight, a smaller root pitch angle should be used.
5.8 Blade Tip Design Selection
Blade tip design is critical on large helicopters due to the tip speeds approaching or even exceeding supersonic speed
on the advancing blades in forward flight. However, for scaled helicopters such as the Blade 600X, which has a nominal
rotational frequency of 2,000 RPM and forward flight speed not exceeding 30 m/s, the maximum resultant tip speed
Mach number will be around Mach 0.5 (i.e. well below the critical Mach number of 0.8). Thus, the blade tip design only
has a minor impact on the aerodynamic performance of the UAV. Nevertheless, blade tip design for single main-rotor
UAVs can affect the acoustic footprint of the rotor and therefore should not be completely neglected. However, since
the BEMT code developed could not accurately predict the aerodynamics or aeroacoustics of the blade tip, a swept
back, rounded tip commonly seen in single-rotor UAVs was chosen for the blade design.
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5.9 Blade Number Selection
From BEMT and flight testing, the AOA of the stock blades (NACA 0012 airfoil, zero twist, zero taper) was observed
to be around 2-3 at 75% of the radius, depending on the RPM. This is far below the 8.3 corresponding to the optimal
lift-to-drag ratio for the NACA 0012. This was also found to be the case for the optimized blades due to manufacturing
limitations which prevented further reducing rotor solidity. A single-bladed design was therefore considered to reach
the desired AOA corresponding to the maximum L/D ratio.
Simulation results from BEMT showed that a single-bladed configuration (using the stock blades) with a UAV mass
of 5.0 kg at 1,500 RPM increased FM by 17% and reduced the power requirement by 14%. Using a single-bladed design
with the a blade that incorporates the twist, taper, and airfoil profile described in the previous sections yields even
better results. A summary of these simulation results is presented in Table 2. While the results tabulated below are
for hover, the same trend was seen for forward flight.
Since the manufactured counterweight was placed near the center of rotation it was required to be significantly
heavier than the opposing blade. To maintain a consistent total UAV weight of 5 kg the payload was reduced by 365 g
in the single-bladed design. If the payload is not reduced, operating at 5.365 kg with the single-bladed design remains
beneficial for the stock configuration but marginally increases power consumption for the optimized design, as shown
in Table 2. Ideally the center of mass of the counterweight would be further from the center of rotation such that a
smaller mass could be used.
Another advantage of a single-bladed design is that the baseline blade could be still used by UAV operators while
delivering a significant performance improvement. Thus, only the counterweight required to match the centripetal
force of the rotating blade would need to be purchased or manufactured. Although using a single blade is not feasible
at low RPM as a result of the unsymmetrical lift produced, due to the high RPM required for flight of this scale
of UAV, the blade frequency is such that stable flight can be achieved. Even at 1,500 RPM, minimal change in
stability and controllability was observed during flight testing when switching from a two-bladed to a single-bladed
rotor configuration. Changes to the vibration and noise amplitude of the UAV were not observed during flight testing
of the single-bladed rotor. This observation, however, was unexpected and is likely a result of the high gear noise and
inexpensive off-the-shelf components used to measure vibration and noise.
5.10 Optimized Blade Design
The optimized blade design, illustrated in Figure 6, features a NACA 4409 airfoil, 2:1 taper ratio, 15 root pitch angle
and a transition to ideal twist at 50% of the blade length. Cost-effectiveness and manufacturability are of utmost
importance for such low cost UAV rotorcraft and, as will be shown later, the blade shown in Figure 6 can be relatively
easily machined from wood or by other more sophisticated techniques.
Although the optimization parameters are presented individually in the sections above, all possible combinations
were considered simultaneously during the optimization routine.
5.11 Summary of Optimization Results
By compiling all the aforementioned results, the performance of each rotor configuration (Figure 7a) and the impact
of each parameter were evaluated (Figure 7b). In Figure 7a, it can be observed that the original rotor configuration
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at 2,000 RPM in a two-bladed configuration (shown as the leftmost bar in the figure) has a significantly higher power
consumption relative to all the tested rotor configurations. Note that the baseline blades refers to the stock blades
suggested by the manufacturer of the Blade 600X UAV and feature zero twist, no taper and use the NACA 0012 airfoil.
Figure 7b reflects the impact of each optimization parameter going from the leftmost (baseline blades at 2,000 RPM
with two blades) to the rightmost (optimized blade at 1,500 RPM with one blade) rotor configuration. As expected
from Figure 7a, the RPM has the largest impact on the power consumption of the UAV. The number of blades and
taper also have a large impact on the UAV performance, while blade twist and airfoil geometry only have a minor
impact on the power consumed by the rotor. Figure of Merit showed a similar trend, with the RPM (58%) and number
of blades (18%) having the largest impact on rotor efficiency, followed by taper (12.5%), twist (6%) and airfoil profile
(5%).
6 Blade Manufacturing
Four different manufacturing methods were considered during the blade fabrication process. Due to the differing
limitations of each manufacturing method, they did not all feature the same design. In particular, the fibreglass blade
featured no twist nor taper. Each method was used to prototype 1-2 sets of blades, which were then tested in a whirl
tower facility. Flight testing was performed on each of the designs with exception of the aluminum edged blade due
to manufacturing defects identified during whirl tower testing. The main features of each manufactured blade were as
follows:
1. CNC - Wooden blade dipped in epoxy with steel leading edge ballast (124.3 g)∗,†
2. CNC - Geometrically optimized non-ballasted wooden blade dipped in epoxy (58.5 g)
3. CNC - Wooden blade with aluminum leading edge (158.0 g)
4. CNC - Steel counterweight (single-blade design; 501.4 g)
5. 3D-printed skeleton wrapped in fiberglass skin (233.5 g)
∗For reference the weight of a stock blades is 136.4g
†Stated blade weights are for a single blade
Computer Numerically Controlled (CNC) routing and 3D printing processes were used to prototype the blades due
to their ability to produce blade geometry of arbitrary complexity. Limitations in blade geometry were therefore mainly
driven by material properties and the accuracy of the machining process. The finished blades from each manufacturing
method are shown in Figures 8a to 8d and 9a. The wooden blades without the aluminum leading edge and the 3D
printed blades required chord-wise balancing to avoid flutter while each of the designs with wood as the load bearing
material needed to be impregnated with epoxy to increase blade stiffness. Yellow birch was used for each of the wooden
blades due to its strength characteristics and availability. The wooden blades in Fig. 8a feature no twist nor taper
and were used to test the feasibility of manufacturing wooden blades. The wooden geometrically optimized blade
depicted in Fig. 8b, on the other hand, proved to be too thin at the leading edge to complete chord-wise balancing
with the manufacturing tolerances of the available equipment without risking the structural integrity of the blade. The
tip-design of the aluminum-edged blade (Fig. 8c) feature a higher taper than the design presented in Fig. 6 due to
smaller amount of taper seen in the remaining blade span. This allows for higher blade strength without a significant
loss in aerodynamic performance.
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A common requirement for each of these designs was for their fabrication cost to remain within a budget compa-
rable to the cost of the baseline UAV itself (i.e. a maximum of 1,000 CAD). This requirement prevented the use of
manufacturing methods involving custom molds or autoclave curing. It should also be noted that the manufacturing
methods presented above are primarily suitable for prototyping and would be uneconomical for large-scale production.
Further details regarding the manufacturing process used for each method can be found in Kotwicz Herniczek et al.
(2016).
Although each blade was manufactured and tested in the whirl-tower, only flight test results for the one-bladed
design (with the stock blade as the lifting surface) are included in this manuscript. This was due to a number of
setbacks during the manufacturing process: The geometrically optimized wooden epoxy-dipped blade survived whirl
tower testing, however, significant blade deformations were observed during takeoff and no flight data was captured.
The wooden aluminum-edged blade showed promising theoretical stiffness and structural strength, however, the blades
were destroyed during whirl tower testing due to incorrect epoxy application along the wood-aluminum interface.
Lastly, the fiberglass wrapped blades were created as a proof-of-concept with the hope of refining the wrapping process
to allow for more precise and complex geometry. The first iteration of these blades were hand-wrapped and given their
similar blade geometry to the stock blades, showed no improvement relative to the stock configuration. Similarly, the
steel-ballasted wooden blades featuring no twist nor taper were flight tested successfully but showed no improvement
in power consumption, as expected.
7 Whirl Tower Testing
Prior to flight testing, each blade design was tested in Carleton University’s Whirl Tower facility at maximum RPM
and maximum pitch angle. This was done to ensure the blades could sustain the highest possible tensile and bending
loads experienced during flight.
The newly designed blades and the counterweight were first subjected to an initial rotational velocity of 500 RPM
(0 collective pitch) for two minutes and then inspected for any loosening of the lead-lag axis blade attachment bolt,
structural distortion, surface cracking or other signs of fatigue. Signs of vibration caused by rotor imbalance were
carefully monitored via remote high-speed video cameras within the chamber. The blades were then subjected to
increasing RPM and pitch such that the final test (held for two minutes) consisted of rotating the blades at 2,000 RPM
at a collective pitch of 10.
8 Flight Testing
Flight testing was conducted to validate the improvements predicted by BEMT as well as to evaluate flight performance
of the manufactured blades. To eliminate variable flight conditions and to facilitate compliance with Transport Canada
regulations, the tests were performed indoors.
8.1 Apparatus
The test platform, as mentioned earlier, was the Blade 600X UAV. While the majority of the necessary components are
included with the purchase of a build kit, it is not possible to measure and record data without additional components;
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namely an electronic speed controller and data logger. The Turnigy ESC-100A Super Brain was used in conjunction
with the Turnigy USB linker to record battery power consumption and shaft RPM. A dedicated Adafruit ADXL335
triple-axis accelerometer was rigidly mounted to the frame of the UAV and connected to an Arduino Uno Microcontroller
to record vibration data, while a telemetry radio enabled real time data streaming and collection. A static pitot tube
was also mounted underneath the rotor along the tail boom to measure inflow through the disk.
8.2 Methodology
Several types of tests were performed. The first test was composed of varying the payload of the UAV and recording
the power drawn from the battery while in hover. During the second test, the RPM was varied via the Electronic Speed
Controller (ESC) while keeping the total UAV mass constant at 5.0 kg. Lastly, FM was measured using a combination
of ground and flight tests. Each test was performed in order to validate the values obtained from BEMT. Free-flight
tests were performed inside an indoor gymnasium 60 m wide by 70 m long by 11 m tall. Any interference effects were
assumed to be negligible given that the UAV was at least 4 m from any boundary surface. It should be noted that
even lower power consumption could be obtained for the flight test data at 1,500 RPM if the gearing had been altered
such that the motor could have remained at full throttle (thus eliminating the reduction in motor efficiency seen by
the motor at low–mid throttle).
8.3 Payload Test Results
During payload testing, the payload was varied from 0 kg to 3.8 kg. Only a fraction of the maximum payload was
added due to the reduced controllability of the UAV at larger payloads and the confined, indoor flight space. Figure 9b
illustrates the relationship between power and total UAV mass. Since the BEMT prediction (shown by the solid line in
Figure 9b) represents the shaft power, while the experimental flight data represents the total power consumption of the
UAV, an offset between the two power values is expected. Although the BEMT prediction is significantly lower, the
offset is consistent and an experimentally determined factor of 2.0 (which accounts for the motor efficiency and the tail
rotor power consumption) can be used to match the two results (shown by the dotted line in Figure 9b). Additional
reasons for the large offset observed are an underestimation of the coefficient of drag by the CFD simulation and the
simplifying assumptions introduced by BEMT for the calculation of the power required to hover. It should be noted,
however, that each of these possible sources of error are not expected to be significant given the successful validation of
the CFD methodology with experimental drag data and the reasonable performance of BEMT that been demonstrated
for hovering flight (Leishman 2006). Minor error is also introduced due to the conversion factor from the avionics power
draw, which does not vary with payload. The consistency of the offset in Figure 9b, however, suggests that the trend
predicted by BEMT is reasonable. The baseline UAV configuration (using two stock blades) and a rotational frequency
of 1,800 RPM was used during payload testing.
8.4 Figure of Merit Results
Figure of Merit (FM) of the baseline and modified UAV rotor was measured via several methods: measuring the shaft
torque through the tail thrust, measuring the inflow using a pitot tube and measuring the power drawn from the
batteries during hover.
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8.4.1 Shaft-torque measurement:
Figure of merit, defined in Eq. (4), is the ratio between the ideal power and the actual power required to hover. The
ideal power in hover can be determined using momentum theory, while the actual power required to hover is equivalent
to the product of shaft torque (Q) and the rotational velocity of the shaft (Ω) as described in Eq. (10).
P = Ω ∗Q (10)
Thus, measurement of the actual power can be obtained by recording the rotational velocity of the main shaft as
well as measuring the torque along that axis. The rotational velocity can be obtained from the rotational frequency
measurement recorded by the ESC, while the torque measurement can be determined by measuring the tail thrust and
multiplying by the tail boom length. To measure the tail thrust, a ground based test stand was built to measure the
force generated by the tail rotor at the pitch and RPM setting required for the UAV to hover during free flight. The
apparatus consisted of a one-degree-of-freedom rotational platform with a force sensor connected to the tail boom. The
main rotor was tested with the main rotor blades on and the tail blades off.
8.4.2 Pitot tube measurement:
The second method used to measure the FM involved placing a pitot tube 10 cm underneath the rotor and recording
the induced velocity at different radial positions along the rotor during hover. The ideal power (required to push air
through the rotor disk if non-ideal effects such as viscous effects, 3D effects, swirl, etc. are neglected) can then be
calculated using Eq. (11).
Pideal = T ∗ vi (11)
The measured inflow velocity showed the expected trend, where the inflow is lowest near the root and increases
towards the blade tip. However, the data recorded from the pitot tube was too poor in resolution and precision to
compare to theoretical results. This was likely a result of significant vibration being transfered through the pitot tube
mount.
8.4.3 Battery power draw measurement:
Lastly, the shaft power of the UAV was estimated from the total power draw of the batteries (recorded by the ESC)
during hover. To obtain the shaft power, the measured power was divided by a factor of 2.0 (experimentally determined
during payload testing) in order to account for the motor efficiency as well as the tail rotor and avionics power
consumption.
Figure 10a shows results for the Figure of Merit calculated from the battery power consumption, the torque mea-
surement and using BEMT, with the three methods showing good agreement. Each measurement was performed under
the same conditions using two stock blades rotating at 1,800 RPM with no payload attached to the UAV.
Results presented in Figure 10b, are similar to Figure 7a introduced earlier in the paper, but include the experimental
results for the power consumption for each rotor configuration. It should be noted that the same experimentally
determined factor of 2.0 was used to match the experimental power to the value predicted by BEMT. Although the
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last two columns in Figure 10b do not have experimental results due to the manufacturing difficulties outlined in
the manuscript, the values for power consumption predicted by BEMT are expected to be reasonable due the close
agreement seen in Figures 9b, 10a and 10b.
9 Conclusions
Rotor blade optimization at Reynolds numbers between 100,000 and 500,000 (indicative of this scale of UAV rotorcraft)
was performed using Blade Element Momentum theory. BEMT was used to test various airfoil profiles and rotor blade
shapes using data provided from CFD. Using BEMT, a blade design utilizing a cambered profile, taper and twist was
developed. Selected blade designs were manufactured and flight tested on the Blade 600X UAV to validate theoretical
results. The following conclusion were made:
1. Rotor efficiency (and therefore range and endurance) can be significantly increased by reducing rotor RPM.
Reducing the RPM from 2,000 to 1,500 on the Blade 600X UAV (equipped with two stock blades) resulted in a
55% increase in the FM and 36% reduction in the power consumption.
2. Following RPM control, reducing solidity had the second largest effect on blade performance and can be achieved
with a taper ratio, smaller chord or a lower blade number. Increasing rotor radius is also generally desirable but
only if the appropriate rotor frequency can be achieved. Blade twist and airfoil selection had the lowest impact
on the performance of the UAV.
3. Using a counterweight to reduce the number of blades is an effective, simple and low-cost method to increase
rotor efficiency. On the Blade 600X UAV, a one-bladed design improved FM and power consumption by 17% and
14% respectively (at 1500 RPM using the stock blades).
4. BEMT is a fast and reasonably accurate tool to investigate blade geometry. For the Blade 600X, a NACA 4409
airfoil, 2:1 taper ratio, 15 root pitch angle and a transition to ideal twist at 50% of the blade length showed optimal
theoretical performance while maintaining manufacturability. This blade design would theoretically improve FM
by 28% and power consumption by 22% (at 1500 RPM for a two-bladed configuration).
5. Published 2D airfoil data at low and transitional Reynolds numbers (100,000 to 500,000) is limited, and CFD or
wind tunnel testing may be required to obtain accurate airfoil data (necessary for BEMT).
6. Rotor blades can be manufactured at low cost with little machinery. However, the process is time consuming,
which restricts the methods to small-scale production. The manufacturing materials and method may also limit
the range of allowable blade geometry during the optimization process.
7. Lightweight, complex and thin blade geometry leads to improved theoretical aerodynamic performance, however,
great care must be taken to ensure sufficient structural stiffness is maintained. Manufacturing tolerances must
also be considered during selection of the minimum blade thickness to ensure chord-wise balancing is feasible.
8. The results presented in this paper suggest that many UAV operators could extend the endurance and range of
their helicopters by reducing rotor RPM and that there is a market for aerodynamically optimized small-scale
UAV rotor blades. Single-bladed designs with a counterweight may also be a viable option for UAV operators
looking to improve the range and endurance characteristics of their helicopters.
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10 Acknowledgments
This work has been a part of Carleton University’s Capstone Rotorcraft initiative, supported by Bell Helicopter Textron
Canada and ING Robotic Aviation, to investigate sub-scale helicopter performance optimization.
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Figure 1: Standard Blade 600X UAV configuration.
Table 1: Standard Blade 600X Specifications.
Specification English MetricEmpty mass (no batteries) 6.26 lb 2.84 kgMinimum takeoff mass (no payload) 8.47 lb 3.84 kgTotal takeoff mass (with payload)∗ 11.02 lb 5.00 kgMain rotor radius† 26.42 in 671 mmMain rotor chord 2.17 in 55 mmMain rotor rotational frequency 2,000 RPMMain rotor tip Reynolds number 500,000Main rotor airfoil NACA 0012
∗The total takeoff mass was defined as 5.0 kg for the purposes of this paper, leaving 1.16 kg for various instrumentation and payload for theflight tests.†The rotor radius is taken from the center of rotation to the blade tip.
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(a) (b)
Figure 3: Lift and drag coefficient data of selected NACA airfoils (Re = 400,000; M = 0.06).
Figure 5: Variation of power consumption with root pitchangle.
Table 2: Single-bladed (with a counterweight)and double-bladed configuration BEMT resultswith a takeoff mass of 5.0 kg at 1,500 RPM.
Blade Type Blades FM Power [W]
Stock NACA 0012 2 0.48 385
Stock NACA 0012 1 0.56 330
Stock NACA 0012* 1 0.57 360
Optimized Design 2 0.62 300
Optimized Design 1 0.68 275
Optimized Design* 1 0.68 304
* Takeoff mass of 5.365 kg (payload of 1.16 kg)
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(c) (d)
(e) (f)
Figure 4: Impact of rotor parameters on performance: (a) power requirement variation with RPM; (b) variation of bladeAOA with RPM; (c) variation of FM with rotor radius at a constant payload; (d) variation of power with rotor radius ata constant payload; (e) variation of power with rotor chord at a different taper ratios; (f) variation of power with taperand RPM in hover.
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Figure 6: Manufacturing drawing of the optimized blade design.
(a) (b)
Figure 7: Results from optimization: (a) power variation with rotor configuration; (b) relative influence of optimizationparameters on power consumption.
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(a) (b)
(c) (d)
Figure 8: Two bladed designs: (a) steel-ballasted wooden blade; (b) non-ballasted, ”optimized” wooden blade; (c) hybridwooden and aluminium blade (6061-T6); (d) 3D-printed, fibreglass-wrapped blade.
(a) (b)
Figure 9: (a) Single-bladed steel counterweight design mounted on the Blade 600X with a close-up view of the counter-weight; (b) comparison of theoretical and experimental power consumption as a function of payload.
(a) (b)
Figure 10: Validation of results from optimization: (a) comparison of FM estimated from battery power draw, tail torquemeasurement and BEMT; (b) theoretical and experimental power variation with rotor configuration.
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