27th AIAA Applied Aerodynamics Conference
22 - 25 June 2009, San Antonio, Texas
AIAA 2009-3962
∗
†
‡
§
Massachusetts Institute of Technology, Cambridge, 02139, U.S.A.
A propulsion system for a Nano-Air Vehicle (NAV), defined as an air vehicle smaller than
7.5 cm and weighing about 10 grams, has been designed, fabricated, and tested. The design features a novel gearless torque-canceling propeller mechanism, with a tightly-integrated counter-rotating electric drive motor. A design procedure that strongly couples the design tradeoff for the electrical motor and the propellers was developed and used to obtain an optimum design minimizing the power consumption at hover thrust. From the test results, the prototype: demonstrated maximum thrust of 17.28 g; provided hover thrust at a power consumption of 1.26 Watts and input voltage of 3.3 Volts, which translates to 20 minutes of hovering endurance; and provided a torque-canceling mechanism capable of canceling up to 99% of torque generated in the motor. Using a combination of 5-bladed and 3-bladed propellers with an operating motor speed of 9,000 rpm, this propulsion system had a noise footprint of 42.55 dBA 1m away from the vehicle, quieter than typical indoor background noise during the day. It is concluded that the propulsion system developed was capable of meeting all the requirements imposed by DARPA.
Γ
T
R
B
Propeller radius, m
Propeller blade count
Blade circulation
Thrust, N
P
C
T
C
P c
` c d
Re c
ρ
Ω
Power, W
Coefficient of thrust
Coefficient of power
Blade local lift coefficient
Blade local drag coefficient
Blade average chord Reynolds number
Density of air, kg / m
3
Angular velocity, rad/sec
η h
η tc
Propeller efficiency factor
Torque-canceling efficiency
τ
M
τ res
Motor torque, N-m
Residual torque, N-m
OASP L Overall sound pressure level, dBA
∗
Graduate Student, Department of Aeronautics and Astronautics, 77 Mass Ave 31-255, chauds11@mit.edu, AIAA Member.
†
Professor, Department of Aeronautics and Astronautics, 77 Mass Ave 37-475, drela@mit.edu, AIAA Member.
‡
Professor, Department of Electrical Engineering & Computer Science, 77 Mass Ave 10-176, lang@mit.edu
§
Principal Research Engineer, Department of Electrical Engineering & Computer Science, 77 Mass Ave 10-027 otten@mit.edu
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A.
DARPA NAV Project
O n
October 4, 2005, the Defense Advanced Research Project Agency (DARPA) requested proposals under a Nano-Air Vehicle (NAV) program, 1 aiming to develop a small air vehicle that could operate in small spaces where MAVs have not been able to navigate. The requirements for this NAV specified by DARPA are the following:
• dimension small enough to fit inside a sphere 7.5 cm in diameter;
• gross take off weight (GTOW) smaller than 10 g, including 2 g of payload;
• ability to hover for more than 60 seconds;
• ability to loiter at 5 to 10 m/s;
• operating range greater than 1000 m;
• ability to navigate within 0.5 m mean-square residual error (MSRE);
• small noise footprint to reduce risk of detection.
These requirements cover multiple fields: propulsion, controls and navigation. Among these requirements, this research focuses on meeting the performance requirement in the field of propulsion.
B.
Research Objectives & Design Approach
The objectives of this research are to design and build a NAV propulsion system, and assess whether this prototype has the potential of meeting the requirements set by DARPA, such as thrust, weight and power consumption, while keeping the noise generated by the propulsion system as low as possible. Specifically, the prototype is designed to achieve the following specifications: smaller than 7.5cm in rotor diameter; powerful enough to provide hovering thrust of the vehicle (approx. 8 grams excluding the propulsion system) with an additional 20% safety margin; low enough power consumption to provide hovering thrust for this vehicle during its mission ( ≈ 20 min); low input voltage ( ≤ 3 .
7 Volts) so it can be powered by a 145 mAh lithium polymer battery; and a noise footprint of < 45 dBA at a distance 1 m away from the vehicle. The propulsion system is designed around a hovering condition, assuming that the vehicle will be hovering during most of its mission. Figure
1
shows the NAV configuration, which has the following features:
• simple passive torque-canceling mechanism, with its only mechanical loss at the bearings and slip rings,
• and gearless 2:1 speed-up of motor speed, for improved motor efficiency.
Figure 1. Schematics of NAV propulsion system: propeller attached to stator (red) and one attached to rotor
(blue) counter rotates to passively cancel motor torque; power provided to rotating motor through slip rings
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Figure 2. Main Component of HNAV Propulsion System
Figure
2
shows the propulsion system components, which are tightly integrated and optimized. The following design tradeoffs were considered:
• Weight of the propulsion system: governs the thrust required, hence its power consumption.
• Aerodynamic efficiency of propellers: tend to have higher efficiency at low operating rpm due to
Reynolds number effect. Details shown in section
III .
• Electrical efficiency of motor: tends to have higher efficiency at higher operating rpm; opposite trend from propeller efficiency
• Input voltage of motor: needs to be lower than 3.7 Volts, provided by a lithium polymer battery.
• Noise: need to be studied parametrically to determine lowest noise design.
Figure
3
illustrates the main design optimization procedure of the propulsion system. Its primary goal is to generate an optimal motor and propeller design combination which minimizes the electrical power input to the system, while satisfying all the constraints and requirements. The core of this optimization process consists of two main components:
1. the motor model, which synthesizes the geometry of the motor and evaluates its performance characteristics given the required output shaft power and its operating rpm;
2. the propeller model, which computes the geometry of the propellers and their shaft power input required, given the amount of thrust they must provide at a certain operating speed.
A simple weight model was also added to update the amount of thrust required. The general optimization process is the following:
1. make initial weight estimate of the vehicle;
2. compute the thrust required to hover the vehicle;
3. compute the geometry of the propeller and its required shaft power input, given the thrust required;
4. based on shaft power required, generate a motor geometry that minimizes the electrical power input to the motor;
5. using the geometry of the propeller and the motor, update the weight of the vehicle.
Iterate between step 2-5 until the optimal design converges.
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Requirements:
• Thrust, weight, size, input voltage
Motor geometry
• Motor geometry
• Loss mechanism
Propeller geometry
Power RPM
Thrust
• Power usage
• Propeller geometry
Motor + propeller design combination
Minimum electrical power input
Figure 3. Propulsion System Design Optimization Procedure
The propulsion system must be designed for a wide range of operating rpms so that a parametric study of the noise footprint versus rpm can be conducted later on. For that reason, the optimization process was repeated over a range of operating speeds; the final design was selected based on the overall performance of the motor within the design range of speeds, between 8,000 and 12,000 rpm.
In this paper, we will mainly focus on the aerodynamics, as well as the overall performance of the propulsion system such as thrust, power consumption, and noise footprint.
A.
Analysis on low Reynolds number propeller performance
2
The propeller thrust and power are characterized by:
C
C
T
P
=
=
T
1
2
ρ (Ω R ) 2 πR 2
P
1
2
ρ (Ω R ) 3 πR 2
(1)
(2) where Ω is the angular velocity, R the tip radius, T the thrust generated and P the mechanical power input.
The power can be separated into viscous and inviscid components.
C
P
= C
P i
+ C
P v
(3)
From actuator disk theory, the relationship between C
T and C
P i can be expressed as:
η h
C
P i
=
1
2
3 / 2
C
T
(4) where C
P i is the inviscid coefficient of power, and η h is an efficiency factor which includes the losses due to unrecoverable kinetic energy from residual swirl in the flow, and losses due to blade intermittency, which are not accounted for in the actuator disk theory. Assuming a certain local blade lift and profile drag coefficient and integrating these coefficients along the radius, we obtain:
C
C
T
P v
=
= c
`
B c ave
3 π c
`
B
R c ave c d
4 π R c
`
=
3
4
C
T c d c
`
(5)
(6)
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where C
P v is the viscous power, B the power components we obtain: the number of total blades, and c ave the average chord length. Summing
C
P
= C
P i
+ C
P v
=
C
3 / 2
T
2 η h
+
3
4
C
T c d c
`
(7)
One important figure of merit of a hovering propeller is the power-to-thrust ratio, which directly affects the hovering endurance of the vehicle.
P
T
=
1
Rη h
T
2 πρ
1
2
+
3
4 c d
Ω R c
`
(8)
Although we do not have much freedom to modify the first actuator disk power term, in equation ( 8 ), the
viscous profile power term can be reduced by lowering the rotational speed. Reducing the rotational speed also has an additional noise benefit.
By definition,
C
T
= c
`
B c ave
3 π R
=
T
1
2
ρ (Ω R ) 2 πR 2
(9) solving for the average chord length, c ave
, we obtain: c ave
=
3 πRT
1
2
πR 2 c
`
(Ω R ) 2
(10) and
Re c
=
3 πRT
1
2
πR 2 νc
`
(Ω R )
(11)
Equation
11
shows that at a fixed thrust, the Reynolds number of the blade increases as the rotational speed is lowered. The profile drag coefficient estimate c d
= c
3
`
π
Re c
10 , 000
− 1 / 2
(12) also shows that lowering the operating speed has an additional benefit of reducing the drag-to-lift ratio, c d
/c
`
, which further reduces the viscous power loss. However, because the efficiency of the motor is higher at high operating speed, this essentially gives a design trade off between the propeller’s aerodynamic efficiency and motor efficiency. In addition, because a low rpm propeller has a higher solidity, for the same thrust output, low-speed design propeller tends to be heavier than those designed for high operating speed. This increases the thrust and hence power required.
B.
Propeller Design Model
The purpose of the propeller model is to supply the mechanical power input and the geometry of the propeller at various operating speeds for the overall optimization procedure described in Section
II . It also
computes an accurate three dimensional loading on the blade in order to predict possible problematic regions.
Two different propeller models were used to achieve these goals: 1) XROTOR, 3 for quick design iterations and performance predictions, and 2) RVL 4 coupled with RAXAN 5 for a detailed three dimensional flow prediction.
XROTOR was first used in order to generate preliminary propeller designs and performance predictions.
A database of propeller weight and input mechanical power was constructed using this code, and the data was fed into the propulsion system design optimization model. The preliminary propeller geometry obtained using XROTOR was then fed into the RVL/RAXAN combination, where further performance analysis and design modifications were conducted.
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1
2
B Γ
Γ
Figure 4. Lifting line model used in XROTOR
3 a y p p p
Figure 5. Iterative procedure used to design
1.
Preliminary design iteration using XROTOR
XROTOR models the propeller blade as a lifting line, trailing semi-infinite helical vortices. Given an input parameter such as propeller radius, free-stream velocity, operating speed and output thrust, XROTOR computes the circulation distribution of the propeller which maximizes the efficiency η h of the propeller by enforcing radially constant local induced efficiency along the blade. Once the circulation distribution of the blade is calculated, the detailed geometry of the propeller (chord and blade angle along radial stations) is obtained using a specified local lift coefficient distribution.
In order to model viscous losses, XROTOR uses a simplified viscous model involving the profile drag of an airfoil section suited for low-Reynolds number operating condition (TA series) obtained from XFOIL, 6 another computer program written by Prof. Drela which predicts the performance of a two dimensional airfoil section. This model gives fairly accurate viscous power predictions around design conditions.
To capture the aerodynamic interaction between the top and bottom propellers, an iterative procedure depicted in Figure
5
was used to match the induced velocity fields of the two propellers.
Normalized Thrust vs. Normalized Speed
2
of Prototype Propeller
1.4
Experimetal data
1.3
XROTOR prediction
1.2
1.1
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.2
0.3
0.4
0.5
1 1.1
1.2
1.3
1.4
0.6
0.7
0.8
0.9
RPM
2
/RPM
2 des
Normalized Thrust vs. Normalized Power of Prototype Propeller
1.4
Experimetal data
1.3
XROTOR prediction
1.2
1.1
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0 0.2
0.4
1.4
1.6
1.8
0.6
0.8
1
Power/Power des
1.2
Figure 6. Normalized thrust vs. normalized speed
2 Figure 7. Normalized thrust vs. normalized power
To quantify the accuracy of this model, a prototype propeller was fabricated and tested, and the result compared against the prediction from XROTOR. Figure
6
shows the predicted and measured thrust normalized by its design thrust as a function of speed squared normalized by the design speed squared, and
Figure
7
shows the comparison of predicted and measured power. Although XROTOR captures the overall performance trends of the propellers, it tends to overestimate the performance. The error in the estimation of the power consumption is especially large, with more than 20% error at the design condition. This large discrepancy is mainly due to the three dimensional effects of the flow around the propellers, such as radial inflow and stream tube contraction that cannot be modeled using a two dimensional lifting line theory.
Further blade design refinement was therefore conducted using higher fidelity codes RVL and RAXAN.
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2.
Three-dimensional modeling using RVL and RAXAN
To capture the three-dimensional effects, the preliminary geometry obtained by XROTOR were analyzed further using a combination of two programs:
RVL and RAXAN, both of which written by Prof.
Drela.
RVL works in a very similar way as XROTOR; the main difference being that RVL uses vortex panels to model the propeller blades (shown in figure
8 )
instead of using lifting lines. By doing this, RVL can resolve local blade loading along the chordwise direction that XROTOR was not able to capture. In addition, this extra degree of freedom allows RVL to take into account the radial inflow into the propeller that XROTOR did not account for.
RAXAN is an axisymmetric stream function solver which is capable of solving for the mutual interaction of the propellers simultaneously from a prescribed propeller blade circulation obtained from
RVL. By solving for the interaction simultaneously, control
point
ring strength airmass moti on relative to blade r i
V camber surface pane l ring vortex trailing edge horseshoe vortex wake vortex
Γ i
T E
T E
Figure 8. Vortex lattice modeling used in RVL
4
RAXAN is able to compute and incorporate the contraction of the wake stream tube into the results; an important effect that XROTOR was not able to take into account.
Figure
9
shows the general iteration procedure to analyze the flow field around the propeller. SimRVL / RAXAN coupling ilar to the XROTOR iteration, two RVL cases are run simultaneously. The blade circulations of both propellers are first computed from the freestream
RVL 1
• Top Prop Model
• Compute blade circulation from external flow field
RVL 2
• Bottom Prop Model
• Compute blade circulation from external flow field boundary condition from the two RVL run cases.
The blade circulations are then fed into RAXAN, where the mutual interaction of the propellers is computed simultaneously. The obtained flow field is then fed back into the two RVL cases, where the circulation of each propeller will be adjusted based
Blade
Circulation
Induced
Flow Field
Blade
Circulation
RAXAN
• Compute mutual propeller interaction
• Outputs velocity profile seen by each propeller
Induced
Flow Field on the new flow field computed using RAXAN. This procedure is repeated until the circulation of each of the blades converges.
The designed blades were further fine tuned to
Figure 9. Coupling between RVL and RAXAN eliminate problematic regions such as high blade loading and oversized hub blade sections.
After the system optimization, a 3.5-gram propulsion system prototype was successfully fabricated. The performance of different propeller designs, the design thrust was fixed at 13.2 grams. This value was chosen based on the weight of the motor and the propeller, combined with the notional goal of the weight of the propulsion system set by DARPA. Table 1 lists all the propeller combinations tested.
Table 1. Propeller combinations tested during experiment
Combination Motor rpm Blade #, top Blade #, bottom
9,000-3 9,000 rpm 3 blades 3 blades
9,000-4
9,000-5
9,000 rpm
9,000 rpm
4 blades
5 blades
3 blades
3 blades
10,000-3
11,000-3
10,000 rpm
11,000 rpm
3 blades
3 blades
3 blades
3 blades
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A.
Test Results
As shown in Figure
10 , the HNAV propulsion system worked as antic-
ipated, and met all requirements set by DARPA, with a capability of generating up to 17.28 grams of thrust, a power consumption of 1.26W
at hover thrust with an input voltage of 3.3 Volts. The passive torquecanceling mechanism was demonstrated to give a residual friction torque of only about 1% of the internal motor torque.
The thrust of the propulsion system was measured using simple force scale.
The power consumption was recorded by direct electrical measurement, and the rpm of the propeller from the strobe scope.
The experiment was conducted multiple times to ensure repeatability of the results; the data was taken with increasing and decreasing power inputs 6 times, and the variation of the results were within ± 5%.
Figure
11
shows the relation between thrust generated and electrical power input for various propeller combinations.
The thrust has been non-dimensionalized by the hover thrust of the vehicle (11 g), and the power has been normalized by the target input power (1.23W, required for 20 minutes of hovering endurance). Data points were taken between
2.0 Volts and 4.5 Volts, in 0.25 Volt steps. As we can see from the plot, this propulsion system was able to produce the design thrust at roughly the design power with all of the propellers tested.
One interesting point to note is the relatively small variation in performance between the different propellers. This shows that the system (propeller and motor) performance has been properly optimized; at the optimum, the propeller versus motor tradeoffs should balance to first order. To illustrate this tradeoff more precisely, two important parameters have been investigated: 1) the propeller efficiency and 2) the motor efficiency. From the data obtained in the experiment, the efficiency of the propeller was calculated by dividing the ideal actuator disk power by the measured shaft power of the propeller. The ideal actuator disk power can be expressed as
1.6
1.4
1.2
1
0.8
0.6
0.4
9,000−3
9,000−4
9,000−5
10,000−3
11,000−3
Figure 10.
Operating HNAV prototype
Normalized Thrust vs. Normalized Input Electric Power
P ideal
1
=
R
T
3
2 πρ
1 / 2
(13)
0.2
0.2
0.4
0.6
0.8
1 1.2
1.4
P elec
/P elec des
1.6
1.8
2 2.2
therefore, the propeller efficiency was defined as
η prop
=
1 /R p
T 3 / 2 πρ
P shaf t
(14)
Figure 11. Normalized thrust vs. Normalized electrical power input (Thrust des
= 11 gf. P elecdes
= 1 .
23 W)
To compute the motor efficiency, the output shaft power was simply divided by the input electric power:
η
M
=
P shaf t
P elec
(15)
Figures
12
and
13
show respectively the relation between the propeller and motor efficiencies vs. normalized thrust. As expected, the opposite trend can be observed from the plots. A lower operating rpm leads to lower viscous power loss, while the motor is expected to have higher efficiency at higher rpm.
Figure
14
shows the correlation between the normalized thrust and the voltage normalized by the target operating voltage (3.4V). There is a small variation in the thrust output of the propulsion system at a fixed voltage. This is also expected from the predicted characteristics of the motor, which state that the motor will run at higher voltage and lower current when operated at a higher operating speed. For this reason,
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Propeller efficiency vs. Normalized Thrust
0.62
0.6
0.58
0.56
0.54
0.52
0.5
0.48
0.46
0.44
0.42
0.4
0.38
9,000−3
9,000−4
9,000−5
10,000−3
11,000−3
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 1.1
1.2
1.3
1.4
1.5
1.6
Thrust/Thrust des
Figure 12.
propeller efficiency vs. normalized thrust
(Thrust des
= 11 gf )
0.6
0.58
0.56
0.54
0.52
0.5
0.48
0.46
0.44
0.42
Motor efficiency vs. Normalized Thrust
9,000−3
9,000−4
9,000−5
10,000−3
11,000−3
0.4
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 1.1
1.2
1.3
1.4
1.5
1.6
Thrust/Thrust des
Figure 13.
motor efficiency vs.
normalized thrust
(Thrust des
= 11 gf ) at the target voltage level, while the low rpm propeller (9,000 rpm) was able to generate up to 105% of the hover thrust, the high rpm propeller (11,000 rpm) was only able to produce 90% of the hover thrust required for this vehicle.
Based on these results, it was concluded that for this particular motor, the 9,000 rpm propeller was best suited to meet the system requirement set by DARPA, with a capability of generating 120% hover thrust at a voltage of 3.75 V, sustaining hover thrust at an input voltage of 3.3 V, with a power consumption of
1.26W to provide a hovering endurance close to 20 minutes.
To measure the torque-canceling effectiveness of the passive torque-canceling mechanism used in this propulsion system, the residual torque from the slip ring and bearing friction was measured using a torque meter. It was found that the residual torque applied to the body of the propulsion system was nearly independent of speed, and equal to τ res
= 1.07
× 10
− 5
N-m.
A useful related parameter is the torque-canceling efficiency:
η tc
= 1 −
τ res
τ
M
(16) which quantifies the residual torque magnitude, relative to the torque generated inside the motor. Figure
15
shows η tc versus thrust. A maximum torque cancellation close to 99% was provided by the counter-rotating motor at maximum thrust.
B.
Summary
Based on the experiments conducted on the propulsion system, it was found that the designed propulsion system was able to meet all the performance requirements set by DARPA. Specifically, the propulsion system using the propeller with design speed of 9,000 rpm was found to be most suitable, and was able to achieve the following:
• produce more than 120% of hover thrust required by the vehicle (13.2 grams);
• produce hover thrust (11 grams) at input voltage lower than voltage provided by the battery chosen for this vehicle;
• operate at a power consumption low enough to provide hover thrust for almost 20 minutes; and
• cancel close to 99% of the torque generated in the propulsion system.
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1.6
1.5
1.4
1.3
1.2
1.1
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.5
Normalized Thrust vs. Normalized Input Voltage
9,000−3
9,000−4
9,000−5
10,000−3
11,000−3
0.6
0.7
0.8
0.9
1
V in
/V in des
1.1
1.2
1.3
1.4
Figure 14.
Normalized thrust vs.
Normalized input voltage (Thrust des
= 11 gf. V indes
= 3 .
4 V)
99
98.5
98
97.5
97
96.5
96
95.5
Torque cancellation efficiency vs. Normalized Thrust
9,000−3
9,000−4
9,000−5
10,000−3
11,000−3
95
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 1.1
1.2
1.3
1.4
1.5
1.6
Thrust/Thrust des
Figure 15. Performance of torque-canceling mechanism
A.
Introduction
The main purpose of this propulsion system is to power a vehicle which mainly conducts reconnaissance missions inside buildings which requires this vehicle to have a small noise footprint relative to typical indoor noise levels. Table 2 shows the typical average decibel levels (dBA) of some common environments.
Table 2. NAV noise compared to typical average decibel levels (dBA) of common environments
Noise level Sound
80 dBA
70 dBA
60 dBA
50 dBA
45 dBA
Automobile (at 7.5 m)
Main road during the day
Normal conversation
Quiet street
Background of normal living
42.56 dBA NAV @ hover at 1m distance
9,000-5 propeller combination
40 dBA
30 dBA
0 dBA
Quiet home
Quiet whisper (at 1 m)
Threshold of human hearing
Based on this information, the goal of the noise footprint was set to 45 dBA overall sound pressure level at a reasonable distance from the vehicle, to make it inaudible in the typical indoor background noise of everyday life. Considering that this vehicle will operate inside a room to conduct reconnaissance missions, the typical distance of this vehicle from a person was assumed to be approximately 1 m. The noise reduction goal was therefore set to a noise footprint ≤ 45 dBA at 1 m away and at any direction from the vehicle.
Based on the acoustic measurement, it was found that the propeller combination 9000-5 was able to achieve an Overall Sound Pressure Level (OSPL) of 42.56 dBA, at 1m distance. Test procedures and results follow.
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B.
Acoustic Test Result
4D
1
0 o
2D
1
45 o
2
2
Microphones
HNAV
HNAV
3 90 o 3
4
Wake
135 o
4
Figure 16. Location of microphones
Figure 17. Experimental setup used during this experiment
Figure
17
shows the experimental setup used. The microphones and the propulsion system were fixed using a stand which was covered with foam in order to avoid acoustic signal reflection. The microphones were located at 2 and 4 propeller diameters, in the near field of the noise. This might not be representative of the acoustic signal perceived at 1 m (approx. 13.3 diameters) from the propulsion system, where the receiver is expected to be in the far field. Unfortunately, based on our preliminary measurements, the low acoustic signal at distances over 1 m was almost indistinguishable from the background noise. Hence, the acoustic data had to be taken close to the propulsion system. However, it is possible to predict the sound pressure level at 1 m by scaling.
Using the measured acoustic signature, an A-weighted Overall Sound Pressure Level (OSPL) was calculated in order to construct the noise footprint. Assuming a decay in sound pressure level proportional to
1/r 2 , the OSPL at 1 m away from the propulsion system can be estimated as
OSP L |
1 m
= OSP L |
4 D
− 20 log
10
1 m
4 D
(17)
This estimation overestimates the amount of noise perceived at that location, since some of the components of noise tend to decay faster than 1/r 2 . Figure
18
illustrates the noise footprint of the propulsion system with different propellers. The noise footprint is smallest at 90
◦
. From this estimate, it was found that the maximum sound pressure levels of the noise generated by the propulsion system for the 9000-4 and 9000-5 propellers were below 45 dBA 1 m away from the vehicle, with a maximum overall sound pressure level of
42.56 dBA and 42.55 dBA respectively.
Based on this result, it was concluded that the propulsion system not only meets the thrust and power consumption requirement, but at 1 m away from the vehicle, it is quieter than the background noise inside a house in everyday life.
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150
120
HNA V acous tic footprint, (dB A )
90
60
30
9,0003
9,0004
9,0005
10,0003
11,0003
180
60   40   20
0
210 330
240 300
270
Figure 18. Noise footprint of the propulsion system, 1 m away from the propulsion system
A rotary wing propulsion system using a novel configuration was successfully developed using a design optimization model which strongly coupled the motor and the propeller. Based on the experiments, it was demonstrated that the propulsion system achieved the following:
• total weight of 3.5 grams;
• nearly perfect passive torque cancellation at all power levels
• mechanical simplicity, with no gears and only two moving parts
• generation of thrust up to 17.28 grams;
• hovering endurance close to 20 minutes;
• input voltage of 3.3 Volts at hover thrust, well matched to a Li-Po battery cell
• low noise level of 42.5 dBA at 1m distance.
Based on these results, it can be concluded that this propulsion system successfully met the requirements set by DARPA.
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Defense Sciences Office (DSO) Nano Air Vehicle (NAV) program”, Technical Report, DARPA DSO, 2005
2
Drela, M., “Sizing of Hovering Rotors at Small Reynolds Number”, Notes, Massachusetts Institute of Technology, 2003
3
Drela, M., “XROTOR Formulation”, Formulation of computer program XROTOR, Massachusetts Institute of Technology,
2005
1
Darryll Pines, “06-06 Proposer Information Pamphlet (PI) for Defense Advanced Research Project Agency (DARPA)
4
Drela, M., “RVL Formulation”, Formulation of computer program RVL, Massachusetts Institute of Technology, 2007
5
Drela, M., “RAXAN Formulation”, Formulation of computer program RAXAN, Massachusetts Institute of Technology,
2008
6
Drela, M., “XFOIL Formulation”, Formulation of computer program XFOIL, Massachusetts Institute of Technology, 2008
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American Institute of Aeronautics and Astronautics