Optimized Performance and Acoustic Design
and Jonathan Silver
IAI – Israel Aerospace Industries, Lod, 70100, Israel
and Raam Sundhar3
Mejzlik Propellers s.r.o., Brno-Židenice, 61500, The Czech Republic
This paper describes the activities held to design, fabricate, and test propellers optimized
for hover conditions. The results validate the design procedure and shed light on the
importance of propeller performance and acoustic characteristics together with the tradeoff
between these two disciplines (performance and acoustics). The comprehensive development
process together with discussion on each of the design and test phases, makes the current
paper a rich source for both propeller designers and hover-vehicle developers.
A = disk area
c = chord
FM = figure-of-merit
I0 = no-load current
IESC = ESC output current
Kv = motor speed constant
Pshaft = shaft power
Q = torque
t = thickness
r = radial coordinate
R = radius, distance
Ra = armature resistance
VESC = ESC output voltage
ηe = electric system efficiency
ηESC = ESC efficiency
μ = average
θ = observer azimuth angle
σ = standard deviation
ρ = air density
AC = alternating current
BEM = blade-element model
BPF = blade-pass-frequency
ESC = electronic speed controller
MDO = multidisciplinary design optimization
OASPL = overall sound pressure level
Mechanical Design Department.
PM = permanent magnet
SPL = sound pressure level
UAM = urban air mobility
Urban Air Mobility (UAM) development has been expanding since the publication of UBER-Elevate white paper
published in 2016. Since then numerous manufacturers have been developing various UAM configurations for
example Refs.  and  show two possible configurations for such vehicles; most of which are multi-propeller based.
This makes the propellers a critical item in these vehicles, especially at hover conditions. At hover the propulsion
system performance is at its highest required power, thus propeller required power at hover impacts the overall
vehicle performance. In addition, the acoustic signature at hover is the highest and together with new regulations 
the importance of optimized hovering propellers increase dramatically.
In this paper the design and testing procedures for hover propellers is depicted. First the design procedure which
includes both analyses validation and optimization will be reviewed. From this design stage, several propellers were
chosen and fabricated. These propellers were then tested on specialized test rig. The tests include both performance
and acoustic measurements. Finally, test results analysis was conducted and comprehensive comparison of test results
to analysis validated the design procedure.
Although UAM requires high thrust, an equivalent small propeller is specified, thus the entire design, fabrication
and testing procedures are simpler and more rapid. Still, all results are highly related to all hovering configuration,
with the appropriate scaling.
IV. Design Specification
As a reference propeller, the Mejzlik 18×6 is used. Fig. 1 shows the Mejzlik 18×6 propeller and Fig. 2 shows its
geometric properties as function of radial coordinate, r, i.e. pitch, β, chord-to-radius ratio, c/R, and thickness-ratio, t/c,
distribution. According to design criteria, the propeller radius is limited to R ≤0.23m, which is the radius of Mejzlik
The propeller in this effort is specified according to its produced thrust. At design conditions, the Mejzlik 18×6
gives thrust of T = 2.8 kgf which is established as the required thrust for hover (static operation) for all future designs.
The propulsion system is based on Sobek 20-38 Spider AC-motor with Kontrol-X 55LV electronic speed controller,
ESC. The acoustic signature is optimized for an observer which is located at azimuth angle, θ=100º, relative to the
propeller axis, as depicted in Fig. 3.
The above specifications allow the design of propeller with various goals. The most important is the required
battery power, electric power, Pe. Different from other design efforts, here the battery power is the most important,
thus the electric propulsion system is to be considered through the design iterations. The second parameter to
minimized is the acoustic signature as heard by the observer. The tradeoff between these two goals is to be found
Fig. 1 Mejzlik 18×6 Propeller, front and top views
Fig. 2 Mejzlik 18×6 Propeller, front and side views
Fig. 3 design conditions of observer-propeller attitude
V. Analysis Validation
To allow proper optimization, the required analyses are to be validated. In this case, three models were validated
extensively: the propeller performance model, electric system model, and propeller acoustic model.
The propeller performance model is based on blade-element model (BEM) which was extensively validated in the
past. Still, in the current case, the small dimensions and low Reynolds number require revised validation. Moreover,
most past validation cases were of axial flight regime, while in the current case hover condition is treated. Although
hover rotor cases were validated in the past, new revised validation is required.
The performance test was conducted with 2 and 4 blades Mejzlik 18×6 propeller, i.e. both 2 & 4 blades share the
same blade geometry. The test was conducted on a test rig which measures the thrust, T, shaft power, Pshaft, speed, Ω,
and electric power, Pe. The electric power is based on the measurement of the input-ESC voltage and current. The
validation test rig is depicted in Fig. 4. The results are presented in Fig. 5 in both shaft power and figure-of-merit, FM,
versus thrust. Figure-of-merit is defined in Eq. (1).
where ρ is the air density and A is the propeller disk area.
Fig. 4, 2 & 4 blades Mejzlik 18×6 propeller performance validation test rig, no fairing installed
BEM analysis uses a 2-D aerodynamic database based on the geometry of the propeller cross sectional airfoils.
Accuracy of the 2-D aerodynamic database is an important part of BEM level-of-confidence. Thus, substantiation of
the current database was conducted using EZair RANS (Reynolds Average Navier-Stokes) software. In addition,
some installation losses, due to the propeller and test rig interaction, were implemented on the BEM analysis.
According to Fig. 5, the analysis exhibits good agreement to test results. Moreover, the various trends concerning
dependency of power and FM with thrust, are replicated accurately. Also the number-of-blades trend, 2 and 4 blades,
is predicted accurately. This enables the usage of the BEM analysis under optimization design procedure.
In the current effort a simple motor model is used to find the required electric power. The model is based on four
constant parameters: speed constant, Kv, armature resistance, Ra, no-load current, I0, and controller efficiency, ηc.
The model is based on the following assumptions:
a. Power factor is equal to unit. This assumption is applicable to small brushless Permanent Magnet (PM) motors.
b. Magnetic losses (eddy/Foucault Current and magnetic hysteresis) can be neglected.
2 blades, no fairing
2 blades, with fairing
4 blades, no fairing
Fig. 5 2 & 4 blades Mejzlik 18×6 propeller performance validation
Dots – experiment, Line - Analysis
ESC output current, IESC, and voltage, VESC, are estimated using Eq. (2).
Total electric power, Pe, used from the energy storage (batteries), is calculated using the ESC efficiency, ηESC, as
depicted in Eq. (3).
Thus, the electric system efficiency, ηe, can be calculated using the ratio of Pshaft and Pe
The motor manufacturer suggested some values for the above parameters (Kv, Ra, I0, and ηESC). Still, an optimized
estimation was done to find the parameters values which give best agreement to the performance test. To increase the
level of accuracy, the speed constant, Kv, is assumed to be linear dependent with the torque, Q, of the motor.
Comparison of test and analysis results is presented in Fig. 6. The original manufacturer parameters resulted with
average ηe error of μ=2.4% with standard deviation of σ=1.8%. Note that for μ and σ, only the speed above 3,500 rpm
are used. Below this speed, the system is far from its design conditions (of T=2.8 kgf).
The optimized parameters resulted with μ=0.75% and σ=0.5%. This agreement may be related to the optimized
parameters estimation. Still, after testing other various propeller configurations (the designed propeller which are to
be presented in what follows) the agreement remained good as presented in Fig. 7 (μ=1.0% and σ=0.7%). This
validated the electric model which is used in the design process.
Fig. 6 electric model efficiency – test to model comparison
Left – original manufacturer parameters, Right - optimized parameters
Fig. 7 electric model efficiency – results of various propellers which were not used to estimate the model
The last analysis to be validated is the acoustic analysis. The test was held in Resideo 5×5×5 m anechoic chamber,
located in Brno, Czech Republic. Fig. 8 shows the faired test rig with the Mejzlik 18×6 propeller installed in the
chamber. A total of 20 microphones on a standard hemisphere was hung above the propeller. The propeller was
located off-center from the array and at a 45° angle so as to minimize the number of microphones which would be
located in the wake or recirculation flows. As a result, a range of radii from 1.1-2.9 meters and propeller azimuthal
angles 75.2-154.7° was recorded.
The current acoustic model predicts only the tonal noise of the propeller. The model is based upon Farassat
formulation as used in former design cases. The model went through extensive validation for various cases of
propeller on various flight regimes., 
The results for 3 of the microphones, located at different azimuth angles, θ, are presented on Fig. 9. The results
from the test are tonal spectra integrated from narrow-band autospectral densities (Δf = 5.9 Hz) about each of the
tonal peaks. (This method varies slightly from method of Farassat which uses a Δf equal to the BPF.) Note that the
microphones are located at different distances, R, from the propeller, thus the comparison between microphones is
useless without a distance correction. Both test and analysis were conducted at the same propeller speed of Ω=4,980
rpm, thus both has the same BPF (blade passing frequency). To match the same thrust (2.8 kgf) as measured in the
acoustic test, the analysis was conducted with pitch change of Δβ=+0.9°, this discrepancy is small.
The comparison of the separate harmonics between test and analysis in Fig. 9 indicates that the first, second, and
sometimes the third harmonics, are predicted quite accurately. This includes the trend of decreased sound pressure
level, SPL, with increased harmonic. As analysis SPL decreases below 50÷55 dB, the test’s SPL remain constant at
about 50÷55 dB. This behavior is not typical for propellers in a free field and is related to the test environment and
test data reduction. Similar results were observed in the work of Block.
Fig. 8 Mejzlik 18×6 propeller installed on a faired rig in Resideo anechoic chamber
Some enforcement to this hypothesis is found in Ref. , which encounter the same type of results and stated:
Typically, the results from Method 1 and Method 2 agree for the first few harmonics, which are above
the background noise of the tunnel. As the harmonic number increases, Method 2 gives the levels of the
background noise, whereas Method 1 gives levels below the background noise which appear to follow the
trends expected for propeller noise.
In the above quote “method 1” refers to normal behavior of propeller SPL harmonics, while “method 2” refers to
results similar to what presented here. A typical example from the same reference can be found in Fig. 10 which shows
test results from Ref. . This exhibits the typical behavior of “method 1” versus “method 2”. Similar methods with
the same phenomena are discussed in Ref. . There, several post-processing techniques are implemented to better
recognize and separate the tonal and broadband noise.
A recent work , has shown these increased peaks to be resultant from unsteadiness in the flow caused by
recirculation in a closed environment. In Ref.  the authors show the importance of air recirculation in the test
chamber which can cause some of the high frequency deviation. In the current effort, the results are not treated with
non-circulatory techniques, thus the higher harmonics of the test results are heavily influenced. Ref.  was published
after the collection of the present paper's data set and hence the knowledge gained from their methods could not be
applied to the current data set. Future works hope to incorporate methods influenced by these results.
Fig. 9 Mejzlik 18×6 propeller acoustic results as function of azimuth angle
Fig. 10 Acoustic results according to “method 1” and “method 2” from Ref. 
Fig. 11 shows the 1st and 2nd harmonics, and the tonal overall SPL, OASPL as function of θ angles. In this chart
the microphone distances are normalized to R=1.5 m. At low θ angles, in front and next to the propeller disk, up to
about θ =120°, the agreement is good. At rear azimuth, θ =150°, the agreement deteriorates. At these rear position,
the microphones were located far from the propeller, thus their 2nd harmonic and above SPLs, were about 55 db, which
caused the background noise to dominate the measurements.
At the design conditions (see Fig. 3) namely θ =110°, the comparison shows good agreement, thus the model is
validated for this design procedure.
Fig. 11 Mejzlik 18×6 propeller acoustic results as function of azimuth angle, R=1.5m
Left – 1st and 2nd harmonics, Right - OASPL
VI. Optimized Designs
Design technique is similar to former cases accomplished with the same tools. These tools include using the
validated analysis tools (BEM, electric model, and acoustic model) together with Esteco modeFRONTIER
Fig. 12 presents a screen capture of the modeFRONTIER framework. modeFRONTIER design environment
enables the integration of different simulation models into a single synergetic design tool. In addition, it allows the
use of various optimization procedures, thus a MDO tool is obtained. In the current case, first the propeller
performance is calculated and then the propeller acoustic is estimated. The use of modeFRONTIER enables an easy
usage of any of the input or output parameters, either as design variables or to include them in the goal function and
In addition, a geometric pre-analysis and performance post-analysis, are implemented using Excel. The geometry
pre-analysis is used to parametrize the design variables which are the pitch, β, thickness-ratio, t/c, and chord-to-radius
ratio, c/R, distribution along the blade. The current effort uses a Bezier spline to achieve smooth distribution of the
geometry, 5 parameters for each distribution. Thus, the design problem contains total of 15 design variables. All
airfoils are based on the Mejzlik 18×6 cross sections and the propeller radius is R=0.23 m.
To ensure the structural properties of the optimized designs, two geometric constraints are to satisfied. First the
blade thickness distribution should not be lower than the original Mejzlik 18×6. Thin blade might be “soft” or exposed
to high stresses, which might cause unacceptable aeroelastic behavior, and high deflections. In addition, the root chord
should not be larger than the Mejzlik 18×6’s root chord. This might cause a very thick hub which increases the
To overcome these issues, the design procedure incorporated two geometric constraints over the thickness
distribution and root chord. The first constraint limits the thickness distribution and the second the rood chord. The
thickness distribution, t (not t/c) has to be higher or equal to the Mejzlik 18×6 up to r/R=0.90, with a tolerance of 0.1
mm. The blade tip (0.9< r/R <1) was freed from this constraint – the impact over the design was high and it seems the
importance of this constraint, at the very tip of the blade, is less important. The root chord is limited to c/R < 0.15.
Note that the Mejzlik 18×6’s c/R = 0.14 at the root (Fig. 2), thus small increase of the root chord is allowed.
The performance post-analysis excel module is used to find the propeller-motor matching speed. Using the
performance calculation, for given propeller geometry, several rotational speeds are calculated. To find the correct
rotational speed, which the propeller produces the required thrust, T =2.8 kgf, a linear interpolation is used. Then,
using the electric model, Eqs. (2)-(4), the electric power, Pe, is found.
Fig. 12 modeFRONTIER design framework screen capture
2B min Pe
2B min SPL
3B min Pe
4B min Pe
The optimization was conducted 3 times for 2, 3, and 4 blades configurations. Pareto frontiers which resulted from
the optimization are presented in Fig. 13. The optimization method and additional details concerning the solution
procedure are available in Ref. .
in Fig. 13 propellers based on the Mejzlik 18×6 blades are marked by red circles. The influence of number-of-
blades is prominent – increased number-of-blades causes both tonal-OASPL decrease and Pe increase.
From the Pareto frontiers, 4 propeller configurations were chosen – these are marked with arrows in Fig. 13 and
a. 2 blades, minimum Pe (2B min Pe)
b. 2 blades, minimum SPL (2B min Pe)
c. 3 blades, minimum Pe (3B min Pe)
d. 4 blades, minimum Pe (4B min Pe)
The propeller characteristics are depicted in Table 1, and their blade geometric parameters in Fig. 14. The clear
difference is the rotational speed. This appears both as the mechanism of reducing the OASPL for the 2 blades
propeller and for achieving the proper thrust for the 3 and 4 bladed propeller. To reduce the rotational speed, thus
achieving min SPL for the 2 bladed propeller, the pitch was increased and the chord slightly increased.
For the 3 and 4 blades, the rotational speed had to decrease to achieve the required T=2.8 kgf. The chord cannot
decrease due to the geometric constraint, thus the chord remained similar and thickness remains above the Mejzlik
18×6 blade. To maintain high enough rotational speed, the pitch decreased for the 3 and 4 bladed propellers, thus the
electric efficiency and FM remain relatively high.
While the 3 bladed propeller exhibits high FM and low ηe, the 4 bladed exhibits low FM and high ηe. Generally,
all tradeoff in such complex design case, is beyond simple intuition and it is a result of handling with all constraints
while striving to minimize all design goals. This proves the advantage of such MDO (multidisciplinary design
optimization) framework, which takes contradicting requirements and find the best compromise.
Fig. 13 Pareto frontiers for the optimized results
Red circles mark the results for propeller based on Mejzlik 18×6 blades
Table 1 optimized propeller characteristics
Electric Power, Pe, W
Shaft Power, Pshaft, W
Electric efficiency, ηe
Tonal SPL, dB
Fig. 14 Optimized blade geometries
VII. Test of Optimized Designs
The four optimized designs were fabricated and then tested on the test rig for both their performance and acoustic
characteristics. The performance test was done on the same test rig which measured the thrust, shaft power, electric
power and rotational speed. Fig. 17 shows the optimized propellers and their installation in the anechoic chamber.
The thrust as function of motor speed is presented in Fig. 15. The curves are quadratic regression which fits the
theory of hover propellers – their thrust is proportional to the square of the rotational speed. From the right chart in
Fig. 15 one can find the propeller rotational speed at the desired thrust, T=2.8 kgf.
Pe versus T1.5 results are presented in Fig. 16 as. In this method, the theoretical linear relation between T1.5 and
required power is shown. Simple linear regression is used to define the propeller performance curve. This enable an
accurate estimation of the required power for achieving T=2.8 kgf from the right chart (zoomed) of Fig. 16.
Fig. 15 Thrust as function of motor speed
Right chart is zoomed
Fig. 16 Required electric power vs. thrust^1.5
Right chart is zoomed
Fig. 17 Optimized propellers
Using the above results, the performance at the design conditions, T=2.8 kgf can be found and compared to the
design estimations, thus validate the design procedure (performance-wise first). Fig. 18 presents the same zoomed
view of the thrust and electric power in Fig. 15 and Fig. 16. The added solid lines represent the analysis. The design
condition of T=2.8 kgf is marked on the charts, thus the design performance can be found and are shown in Table 2.
It seems that the required electric power is over-predicted, for all 2-blades configurations by 15 W ÷ 25 W (4%÷6%).
For the 3 and 4 bladed propellers, the results are more accurate and the analysis is over-predicted by no more than
15 W (3%). Considering the rotational speed, the analysis is over-predicting by up to 150 rpm (3%). These errors
seem reasonable, considering the complex relationship between all parameters.
More interesting is the design trends. The last 2 rows of Table 2 use the Mejzlik 18×6 as a reference, and the
electric power difference, together with rotational speed difference are shown. This is done twice, once for the test
results and then for the analysis (in parentheses). All electric power and rotational speed differences are predicted
accurately. Thus, validates the design procedure process.
2B, min. SPL
2B, min. Pe
3B, min. Pe
2B, Min Pe
3B, Min Pe
4B, Min Pe
Table 2 optimized propeller performance test vs analysis (in parenthesis with difference percentage)
415 (435, 5%)
410 (425, 4%)
425 (450, 6%)
445 (460, 3%)
495 (495, 0%)
325 (335, 3%)
320 (330, 3%)
320 (340, 6%)
330 (345, 5%)
360 (365, 1%)
5,000 (5,150, 3%)
5,100 (5,200, 2%)
4,600 (4,650, 1%)
4,600 (4,700, 2%)
ΔPe, W (18×6 is ref.)
Δ Ω, rpm (18×6 is ref.)
Fig. 18 Thrust vs. rotational speed and Pe vs. T1.5
Dots – test, Dash line – test regression, Solid line - analysis
All optimized and reference propellers went into anechoic chamber acoustic test and their tonal SPL were
measured. Two test series were conducted: thrust of 2.8 kgf, and speed of 5,000 rpm. These two different condition
will shed light on the noise accuracy of the used analysis and the design trends as predicted by the optimization
For thrust of 2.8 kgf, the results are presented in Fig. 19 and for 5,000 rpm results are presented in Fig. 20. Both
chart presents 1st harmonic and tonal-OASPL difference between the optimized propeller and the reference Mejzlik
18x6. The results are presented as function of the microphone θ angle. Note the data is taken from microphones which
are located on different distances from the propeller. Thus, no conclusion can be deducted from the OASPL or SPL
vs. θ dependency from the present figures.
The main purpose of this comparison is to compare the trends of test and analysis. The delta is calculated by
subtracting the various propellers data from the reference Mejzlik 18x6. This shows the design trend as found by the
measurements and by analysis. For low azimuth angles, θ, which exhibits high SPL, the comparison is good.
Difference is less than 1 dB which exhibits good validation of the analysis. Moreover, the design trends are correct,
thus the optimization procedure is also validated.
The minimum Pe propeller was designed to maintain the same noise level and to reduce the required power as
compared to the Mejzlik 18x6 propeller. The former is kept in a very good way – the difference between the minimum
Pe and the reference Mejzlik 18x6 is almost zero.
The minimum SPL propeller reduced noise level (compared to the 18x6) is reproduced in a good manner by the
The 3-bladed min Pe propeller’s SPL is improved by about 10 dB – this is again predicted correctly by the analysis
compared to the anechoic chamber test. Also the 4 bladed, exhibits good results in the limited available data (forward
azimuth for the “5,000 rpm case”).
As θ increases, the microphone distance increase, thus the SPL decrease. This brings the SPL level within the
60÷50 dB range, for which the test result analysis is questionable. This is the reason that high θ, for high number-of-
blade propellers is not presented.
Fig. 19, Delta of 1st harmonic SPL and OASPL comparison vs. θ, Thrust=2.8 kgf
Fig. 20, Delta of 1st harmonic SPL and OASPL comparison vs. θ, , Ω=5,000rpm
As stated above, capability of the current measurement to detect the tonal SPL, for SPL lower than ~50 dB is poor.
This is due to the influence of all noise components, except the tonal: background, motor, and broadband. Each of
these contributions is hard to quantify, but the ~50 dB threshold is very distinct along the entire results.
To demonstrate this claim, measurements of microphone at θ=88° of 3 different propellers: 2, 3, and 4 blades
minimum Pe optimized propellers are given in Fig. 21. It is noticeable that all results predict the first harmonics with
good accuracy. As tonal harmonics decrease below 50 dB, the high harmonic measurement becomes almost constant.
Hence, other noise components become higher than the tonal. As the propeller is louder, higher number of harmonic
is detected. Solid first 3 harmonics for the 2 blades, 2 harmonics for the 3 blades and only the first for the 4 blades.
This also apparent for the OASPL which is accurately predicted for the 2 blades and deteriorates as number-of-blades
The same phenomenon is replicated concerning the azimuth of the microphone via a comparison between the rear
microphones (θ≥115°) and the front (θ≤115°). As azimuth angle increases, the microphone absolute distance from the
propeller increases, due to the microphone installation in the chamber. Thus, the rear microphones detect lower noise
level, which brings it closer to the ~50 dB threshold. Comparison of 3 different azimuth angles for the 2 blades
minimum Pe propeller is given in Fig. 22. These charts again exhibit the ~50 dB threshold of the current measurements.
While the most forward microphone located at θ=88° detect solid 3 harmonics, the most aft microphone (θ=150°)
hardly detects the first. This 50 dB threshold also causes the 4-bladed propeller tonal-noise to be hard to measured.
This is especially true for the rear microphones of the 4-bladed propellers which makes the 4 bladed propeller test
results quite questionable.
The good match between the test trends and analysis trends should be considered in the scope of tonal vs. total
OASPL. As mentioned above, the total OASPL contains the background, motor, and broadband noise on top of the
tonal OASPL. Fig. 23 shows the OASPL of the 2, 3, and 4 blades optimized minimum Pe propellers. The results are
given for the tonal (both test and analysis) and the total OASPL.
For the 2 bladed propellers, there is almost a constant difference of 2dB between the total and tonal OASPL, for
the azimuth of θ≤120°. For the θ=150° azimuth, the difference increases dramatically to ~10 dB. The 3 blades and 4
blades exhibit even higher differences which can reach 15 dB and more.
An interesting common trend, is the minimal value of the total OASPL which reaches 75 dB. This might imply
again on some measurement capability threshold, although 75 dB is quite high.
Another issue is the importance of the tonal versus other noise sources. Importance meaning not just the OASPL,
but also the perception of noise by the human hear. This is more of a psycho-acoustic issue which is not dealt in the
Fig. 24 presents the 1st harmonic test results via the propeller's directivity map. Directivity is another way of
presenting the data that allows one to grasp the sound radiation pattern from the propeller, at which positions will a
propeller sound louder or quieter for a fixed observer distance. Here, results from all microphones that were measured,
are presented. To compare the 5 test cases all microphones were normalized to a nominal radius of 1 meter. Since the
microphones were placed on a hemisphere above the propeller, several microphones will have similar angular
locations and will allow for a symmetry check. The results reveal there are no asymmetrical anomalies, and with the
exception of the 3 and 4 bladed propellers at angles close to 90°, whose amplitudes are the smallest, results are
consistent. Similar to the above results, lack of difference between the cases for positions behind the propeller is due
to the low SPL
Fig. 21, θ=88° measurements, 2, 3, and 4 blades minPe, optimized propellers, Thrust=2.8 kgf
Fig. 22, 2 blades, minimum Pe propeller acoustic measurements, Thrust=2.8 kgf
Fig. 23, Tonal vs. total OASPL results
Fig. 24 1st Harmonic Propeller Directivity. All SPLs have been normalized to a reference distance of 1 meter.
In this paper a comprehensive and methodic design process for hover-propeller is described. The design process
requires a detailed specification. In the current case, an existing propulsion system with of-the-shelf propeller is
considered as a reference for the system specification. For this specification, an optimization design framework was
developed which allows the optimized design of various propeller configurations.
In the basis of the design process are 3 analytic models: blade-element model for the propeller performance
estimation, electric model for the propulsion system characteristics, and acoustic model which analyze the propeller
tonal sound-pressure-level. Each of these models was previously validated versus various results in the literature. Still,
in the current case, dedicated tests were conducted to improve the validation of the design analyses.
After the validation process, the analyses were incorporated in a design framework based on modeFRONTIER
software and a multidisciplinary-design-optimization environment was substantiated. This environment includes,
beside the analyses, various definitions of design variables, constraints, and design goals. Hence a multi-objective
optimization problem is defined.
The design framework was run 3 times for designing 2, 3, and 4 bladed propellers. Each run resulted with a Pareto
frontier which exhibits the tradeoff between the propulsion-system performance and its acoustic signature. From these
tradeoffs, optimized propeller configurations were chosen. These are then fabricated and tested. The test results for
both performance and acoustics is then compared with the design trends, thus the design process is validated.
In the current effort 4 propeller were fabricated. Two of them are 2 bladed, minimal electric power and minimal
acoustic signature. In addition, 3 bladed and 4 bladed propellers for minimum electric power were chosen. The four
propellers exhibited accurate performance and acoustic trends, thus validated the design process.
The research was funded by Israel-Europe Research & Innovation Directorate, ISERD, of the Israel Innovation
Authority, and DELTA-2 programme of the Technology Agency of the Czech Republic, TAČR. The authors thank
these two organizations for their generous contribution.
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