Study of Fan Noise Reduction
f o r Au t o m o t i v e R a d i a t o r
Cooling Fans
ATSUSHI SUZUKI*1
TETSUO TOMINAGA* 2
TSUYOSHI EGUCHI* 2
TOSHIFUMI KUDO*2
TOMOSHIGE TAKATA*2

In order to reduce automotive radiator cooling fan noise, it is necessary to reduce the system's blade passing
frequency noise (BPF), a periodical noise unpleasant to the ear, in addition to an overall noise reduction. The authors have successfully developed and applied a BPF noise prediction technique, which consists of a computational
fluid dynamics (CFD) and sound wave propagation analyses prior to trial. The accuracy of the BPF noise prediction
was verified through an element test. Further, the geometrical parameters influencing the BPF noise have been
optimized by applying quality engineering to evaluate the effect of noise reduction.

1. Introduction
With the remarkable reduction of noise inside and outside cars, there has been an increasing demand in recent
years to reduce the noise of automotive radiator fans installed in the engine compartment to ensure a comfortableenvironment for the passengers. The BPF (blade passing
frequency) noise is considered to be especially unpleasantto the ear and is easily affected by non-uniform flows inside the engine compartment, so that when the fancomponents are integrated into a compact module such asa condenser radiator fan module (CRFM), it is very important to predict and reduce the BPF noise. However,experimental studies of CRFMs installed in various vehicles
are not always realistic due to the high lead-time and development costs.
This paper introduces the results of accuracy verification of a BPF noise prediction technique and presents adesign example, including quality engineering optimization of BPF-noise-sensitive shroud configurations.

Shroud casing

Condenser

Radiator

Fan
Fig. 1 Overview of automotive CRFM
Indicates the structural elements of the module.

becomes comparatively uniform passing through the radiator. After leaving the radiator, the air stream iscontracted by the shroud as it flows from the rectangularradiator surface to the annular fan opening before flowing
into the fan with non-uniform velocity distributions in the
direction of fan rotation. Inside the fan, the flow pressure
is increased, and the cyclic outgoing flow then interacts
with the motor support beam located downstream from the
CRFM, and with the engine and other components locatedfurther downstream within the engine compartment.

2. Features of CRFM
Figure 1 shows an outline of an automotive CRFM. The
CRFM for this research has the fan and heat exchangers
arranged in the space of 500 mm (width) x 400 mm (height)
x 75 mm (depth). Compact as the module is, it has narrow
spaces upstream and downstream. The heat exchanger(condenser) for the air conditioning system is located in
the most upstream position, so that when fitted, flows coming into the condenser from the radiator grill and bumper
have non-uniform velocity distributions. The condenser finshelp to correct the flow direction and to equalize the exit
flow velocities. After passing through the condenser, theairflow passes downstream into the radiator. Here, the flowinteracts with the clearance flow coming from between thecondenser and the radiator. Inside the radiator, as in thecondenser, the flow direction is corrected to promote uniform flow velocity distributions. Therefore, the flow

3. Analogy of cause of BPF noise occurrence
The causes of BPF noise from a CRFM can be summarized as follows.
(1) Spatial transfer of pressure distributions generated
on the blade surface by the fan rotation. (2) Time fluctuation of pressure distributions on the blade surface by
non-uniform velocity distributions upstream of the fan. (3)Time fluctuation of pressure distributions on the bladesurface by the potential interaction with engine components
downstream of the fan. Thus, for BPF noise prediction, theuse of a simulation method which can represent the three
items above will be required.
Mitsubishi Heavy Industries, Ltd.
Technical Review Vol. 43 No. 3 (Sep. 2006)*1 Air-Conditioning & Refrigeration Systems Headquarters*2 Takasago Research & Development Center, Technical Headquarters

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bellmouth casing as time series data. A universal thermal-liquid analysis code STAR-CD was used in thisresearch. The calculation mesh used for the analysis, as
2, consists of a total of 1200000 cells, withshown in Fig. 2
the bellmouth casing including the fan consisting of approximately 700000 cells. Figure 3 shows the tested
models and CFD mesh models, while Table 2 shows themodel dimensions and test conditions. In the unsteadycalculation a 72-step frequency resolution per rotation wasused, with the frequency resolution per time step being
3.3 kHz, approximately equivalent to 17 times the primary component of the BPF frequency (185 Hz). Thus,
the frequency resolution is sufficiently high for BPF noise
prediction. One cycle of rotation data of the static pressure values on all surface cells of one blade, the bellmouthcasing and the flow interaction device for each time step
were acquired. The authors have predicted the BPF noiseof a CRFM based on simplified formula (1) by assuming
the subsonic and far-distance acoustic fields, on the basisof Curle's formula(2), predicting a noise occurrence due tothe pressure fluctuations on a solid wall surface.

4. Modeling of CRFM
In order to facilitate a comparison between the predicted and experimental results for the BPF noise, asimplified model from the viewpoints of the flow and acoustic fields surrounding the fan was used. Table 1 shows alist of the simplified models used for this research.
First, the circumferential non-uniformity is eliminatedby removing the rectangular heat exchanger and the real
shroud casing to allow a sufficiently large space composed
only of a bellmouth casing with a circumferentially uniform cross-section and a cylindrical fan and motor support
rod. Further, the non-uniform upstream velocity distributions are modeled by the wake generated by the
obstacles (the flow interaction device) located upstreamof the fan. On the other hand, the potential interactions
are modeled by a flow interaction device located downstream of the fan. In order to investigate the degree ofinteraction of the upstream and downstream, flow interaction devices, straight type and cross type, wereprepared.

5. BPF noise prediction method
In order to consider the change in the pressure field
caused by the fan rotation and the cause of BPF occurrence, an unsteady CFD was carried out using sliding
meshes to receive the fluctuations of the static pressure
on the blade surface, the flow interaction device and theTable 1 Comparison of study models
Shape of flowinteraction device

Position of flowinteraction device

Model 1

Straight-type

Inlet side

Model 2

Cross-type

Inlet side

Model 3

Straight-typeOutlet side

Model 4

Cross-typeOutlet side

Model 5

None

None

Flow

Table 2 Element test conditions

Model 2Model 4Model 5Model 3

ValuesItems
Fan diameter

Model 1(mm)

Number of blades

300
4

Rotating speed

(rpm)

2 770

BPF (primary)

(Hz)

185

Fan

Flow

Fig. 3 Comparison between element test sample andexperimental sample
Shows the comparison of models.

Fig. 2 Overview of experimental sample and Model 1

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Where,P (x,t): Sound pressure at observation point (Pa)Pw (y): Pressure fluctuation at wall surface(sound source) (Pa)dS: Area elements of each sound source (m2)c: Acoustic velocity (m/s)
r: Distance from sound source to observation point (m)θ : Angle from sound source to observation point (rad)[]: Delay on time (t-r/c)
The BPF noise was analyzed with an analysis code(3),which applied the above formula by regarding each wall
surface cell as a sound source. In this analysis code, only
the spatial distance decay between the sound source andthe assessment point, the directivity concerning the timedelay and the propagation, which are dependent on thesound velocity and the distance, are taken into consideration, with no consideration paid to reflection anddiffraction. As shown in Fig. 44, the noise assessment points
were positioned at regular intervals upstream of the shroud
casing, where the influence of reflection and diffraction are
negligible and the experimental difficulty is also reduced.
The analysis code requires the calculation spatial grid coordinates of the unsteady calculation results, thecoordinates of assessment points and the static pressure
fluctuations on all the wall surfaces. As a result, the soundpressure time history and its FFT analysis results at theassessment points were obtained. The rotating system including the fan and the static system including shroud
casing, etc. were individually analyzed, and the effect ofsound pressure on the assessment points due to the surface wall static pressure was clarified.

Bellmouth

Fan

Flow direction
1 000 mmo

Suction 0oSuction 22.5oSuction 45oSuction 67.5

Fig. 4 BPF noise assessment points
Indicates the relation between the object ofanalysis and the noise assessment point.

Fig. 5 Overview of test instrument
Indicates the state in the anechoic chamber.

High

6. Verification test of prediction accuracy
Pressure

In order to carry out an experimental verification of thepredicted results of the BPF noise, a test instrument equivalent to the analysis model was manufactured. Figure 5
shows an overview of the test instrument. The noise wasmeasured at the same measuring points as the assessment
points shown in Fig. 4 with the test instrument. At eachmeasuring point, the noise was measured with the noise
measuring equipment with a 1/2 inch microphone made byRion, and the frequency was also analyzed with a frequency
analyzer. A maximum frequency of 2 kHz and frequency
resolution of 1 Hz were obtained.

Low
Fig. 6 Pressure distribution by flow analysis
Indicates the static pressure distribution throughout the fluid region.

surface. The behavior of the temporal static pressure distribution was investigated focusing on the suction surfaceof the rotor blade where the influence of the flow interaction device is large. Figure 7 shows the pressure
distribution on the suction surface for Model 1. The vertical axis and color contour of the graph show static pressure
on the blade as the relationship between the flow interaction device and the monitored rotor blade on the left sideof the figure. As shown in the figure, the static pressure
distribution on the rotor blade is the maximum on the blade
leading edge, and is the minimum once it goes to the trailing edge and increases in a monotonic manner. Moreover,the minimum static pressure caused by the reverse flowfrom the rotor blade pressure surface exists in the tip section near the trailing edge.

7. BPF noise prediction result
Figure 6 depicts the static pressure distribution on thesolid surfaces around the fan obtained by the unsteady CFD
analysis. As shown in the figure, atmospheric pressure canbe observed on almost all the surfaces of the bellmouth
and the flow interaction device while a high suction pressure can be observed on the fan blade surface. The
analytical results, therefore, suggest that the staticpressure fluctuation, which causes the BPF noise, can beconsidered to have a large amplitude on the rotor blade

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Top

Monitorblade

Static pressure (Pa)

Lowered staticpressure

Flow interaction device

250
150
50
-50
-150
-250
-350
50
25

72 time steps

-450
0
-25

Top

-75
-100
-125

325

285

205

165

85 45

Y (mm)

Monitor
blade

250
150
50
-50

BottomRelative position of
blade and wake bar

-150
-250
-350
50

90 time steps

-450
0
-25

-50
-75
-100
-125

325

285

205

165

Static pressure (Pa)

350

25

Flow interaction
device position(bottom)

350
265
180
95
10
-75
-160
-245
-330
-415
-500

Point 3
Point 2
Point 1

-130
-140
-150
72

80

88

96

104 112 120 128 136
Time step

144

96

104 112 120 128 136
Time step

144

-550

-50

Flow interaction device

350
265
180
95
10
-75
-160
-245
-330
-415
-500

Static pressure (Pa)

BottomRelative position of
blade and wake bar

Static pressure (Pa)350

Flow interaction
device position
(top)
-110
: Point 1: Point 2
-120

-180
: Point 3
-190
-200
-210
-220
72

80

88

Fig. 8 Pressure change on fan blade surface
Indicates time record for one turn of fan.
Bellmouth

Fan

-550
85 45

High

Y (mm)

Fig. 7 Static pressure distribution on rotor blade
Indicates the instantaneous static pressure distribution of a rotating fan.

PressureTurning attention to the change with time, the lower
value can be observed around the mid-chord near the rotational center, compared with 90 time steps after a 1/4 turnin 72 time steps, which is attributed to the influence of theflow interaction device. The time history of static pressure
values for a typical cell near the mid-chord was investigated as shown in Fig. 8
8. At Point 3 near the tip, wakeinteraction between the rotor blade and the flow interaction device can be observed, because the static pressure isfound to be low in the vicinity of the flow interaction device. On the other hand, at Points 1 and 2 relatively near
the rotational center, although the static pressure reduction due to wake interaction occurs near 72 time steps, thestatic pressure is increasing near 108 time steps. The amplitude of the static pressure fluctuation is about 15 Pa at
Points 1 and 3, and the amplitude increases by 1.6 times
to be about 25 Pa at mid-span Point 2. It is supposed that
this phenomenon originates in the distance between therotor blade and the flow interaction device and the nonaxisymmetry of the flow interaction device. The staticpressure distribution at the flow interaction device
centerline cross-section is shown in Fig. 9
9. As the suction
surface of the rotor blade approaches the rotational centerfrom the blade tip, the distance from the flow interaction
device becomes nearer, causing the static pressure value
to increase. Moreover, in contrast with View A, the rotor
blade which is above the fan center shaft in the contour
figure, (i.e. near 72 time steps), approaches from a perpen-

BellmouthLow

Fan

A view
A viewFlow

Flowinteraction
deviceA view

Motor
Flowinteraction
deviceMotor

Fig. 9 Pressure distribution around flow interaction device and fan
Indicates the static pressure distribution in the center section of flowinteraction device.

dicular side at the down side (108 time steps), to the rotor
blade, approaching from the side where the flow interaction device is cut obliquely. For this reason, a phenomenon
similar to the potential interaction occurs near the fan rotational center at 108 time steps, causing the static pressure
to increase.
Next, the BPF components are extracted. These are considered to have great significance for BPF noise due to thestatic pressure fluctuation on the rotor blade surface. The
magnitude of the static pressure BPF fluctuation component on the blade surface for Model 1 is shown in Fig. 10
10.
The vertical axis of the graph and the color contours
show the non-dimensional static pressure fluctuation
which divides the rotor blade static pressure fluctuation by the bellmouth average inlet dynamic pressure.
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Technical Review Vol. 43 No. 3 (Sep. 2006)4

10 dBSound pressure (Pa): Stationary parts + rotating blades: Rotating blades: Stationary parts

Sound pressure (Pa)Sound pressure level

Suction surface side
Pressure surface side
Fig. 10 Pressure fluctuation distribution on fan blade
Indicates amplitude of fluctuating pressure (non-dimensional value)
on rotor blade pressure surface and suction surface of Model 1

-250

-580

Sound pressure (Pa)Region with large
fluctuating pressure-850

Stationary parts only

-260
-270
-280

Fan rotating cycle

-290
-300

Rotating blades only

-590
-600
-610
-620
-630

Stationary parts+rotating blades

-860
-870
-880
-890
-900
72

0

200

400

600

800

80

88

96

104

112 120128

136 144

Time step

1 000

Frequency (Hz)Fig. 11 Time history of sound pressure at assessment
point (predicted)
Indicates the waveform per one turn of the fan at assessment
point on suction side 0 o of Model 1.

Fig. 12 Result of frequency analysis of sound waveform
Shows the large influence of the rotating blades.

frequencies of the second (370 Hz) and the third (555 Hz)
BPF components. In the higher level of components, except for the primary BPF, an extremely large difference ofmore than 20 dB in the sound pressure level can be observed. When comparing the first BPF spectra, a differenceof 7 dB can be predicted between the peak levels due to theeffect of the stationary parts and rotating blades. Moreover, the combined BPF noise level shows a large differenceof 11 dB for the stationary parts, and the comparatively
small difference of 3 dB for the rotating blades. As a result, the static pressure fluctuation on the solid surface inthe rotating blades has a dominant influence on the peaklevel of BPF noise. It has been confirmed that this tendency is the same for all models except Model 1 and at allassessment points. Figure 13 shows the predicted primary
BPF noise level at each noise assessment point based on
Sound pressure level (dB)

The high amplitude of the BPF component on the suction
surface can be widely observed at the leading edge and at
the mid-chord position near the rotational center of Model
1, in which the flow interaction device is installed upstreamof the fan. This phenomenon is thought to occur due to thewake interaction near the tip, similar to the phenomenonof the occurrence of potential interaction near the rotational
center. On the pressure surface, although a high fluctuation component exists in a few areas of the leading edge,
the fluctuation becomes remarkably low in other areas because the influence of the flow interaction device is small.
Figure 1
1 shows the results predicted by the unsteady11
CFD and BPF noise analysis code, with the sound pressure waveform at the assessment point, suction 0 deg ofModel 1. Each figure shows the predicted sound pressure
wave results: the first obtained by the static system solid
wall surfaces including the bellmouth casing and the flowinteraction device; the second by the rotary system solid
wall surfaces of 4 rotor blades; and the third by combining
the first and second sound pressure waves. It turns outthat each wave includes a four-cycle fluctuation, i.e. the
BPF component. The sound pressure due to the effect of thestationary parts has an amplitude of about 8 Pa, while thesound pressure due to the effect of the rotating blades has
about twice the amplitude, 15 Pa.
Figure 12 shows the sound spectra based on the frequency analysis with FFT. The spectra show the maximum
peak value at the frequency of 185 Hz, which is the primary BPF component and also show clear peaks at the20
Reference point: Model 1: Model 2

10: Model 3: Model 4: Model 5

0
-10
-20
-30

Suction0 deg

SuctionSuction22.5 deg
45 degAssessment point

Suction67.5 deg

Fig. 13 Prediction result of BPF noise level (primary component)
Shows the prediction results at each assessment point for each model.

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Model 1 as a reference. The value of the BPF noise has
almost the same level at each noise assessment point, except for Model 5, without a flow interaction device. An
especially remarkable directivity cannot be seen for Models 1 to 4 with flow interaction devices. On the other hand,for Model 5 with no flow interaction device, the smallest
value is on the fan axis and it increases as it advances
toward the fan radial assessment point. In Model 5, both
the rotor blade and other stationary structure components
are positioned in an axisymmetric manner, and if assuming that the flow field is completely axisymmetric, the noiseof the BPF component will be generated only from the rotor blade load noise. For this reason, all the static pressure
fluctuations from the solid wall surfaces are canceled at
the assessment point on the fan axis and the sound pressure on the fan axis theoretically becomes zero. At radialassessment points, on the other hand, a BPF noise occurs
due to the load noise resulting from the condition that the
distance between the fan rotor blade and the assessment
point is fluctuated by the fan rotation. The spatial distribution of the BPF noise predicted for Model 5 corresponds
to the direction of propagation of the load noise. Table 3
summarizes the BPF noise level for each model at each
assessment point. This is equivalent to the energy generated by the sound source, i.e. the power level.
Model 2 > Model 1 > Model 4 > Model 3 > Model 5
Thus, the pressure fluctuation on the blade surface has
the same relation for each model as described previously.
It can, therefore, be deduced that the static pressure fluctuation on the blade surface is the main cause of BPF noiseoccurrence.

Table 3 Overall BPF noise level for each model (prediction)
Shape of flowinteraction device

Position of flowinteraction device

BPF noise level

Model 1

Straight-type

Inlet side

0 dB

Model 2

Cross-type

Inlet side

6dB
(relative to Model 1)

Model 3

Straight-typeOutlet side

-5.7 dB (ditto)

Model 4

Cross-typeOutlet side

-0.5 dB (ditto)

Model 5

None

None

-12.6 dB (ditto)

component with a level of 58.1 dB also have their peakvalues around 20 dB higher than the broadband noise level.
Thus the BPF noise components are captured clearly by
this experiment. For Models 1 to 5, the primary BPF component, which is shown in Fig. 14, has the highest value atall points of measurement, and the level is clearly higher
than the broadband noise level.

9. Comparison between predicted and experimental
results
In order to verify the accuracy of BPF noise prediction,
the BPF noise level obtained in this experiment was overlapped onto Fig. 13, the BPF noise prediction result, andplotted to compare the predicted value with the experimental value as shown in Fig. 15
15. The figure depicts the relative
difference regarding the primary BPF noise level (185 Hz)for each assessment point for Model 1 and regarding the
BPF noise level at the 0 deg assessment point of the suction side as the reference point, and the following items
were confirmed through comparisons of the predicted andexperimental values for Models 1 to 5.

8. Experimental results of BPF noise

80

Relative soundpressure level (dB)

60
50
40
30

500

1 000
1 500
Frequency (Hz)

0
-10
-20

20

o

: Model 1 inlet 0010Reference point
Inlet side
0 deg

70

20

: Model 1 (Predicted): Model 2 (Predicted): Model 1 (Experimental): Model 2 (Experimental)

20

-30

Relative soundpressure level (dB)

Sound pressure level (dB)Figure 14 shows the results of noise measurement at
the assessment point suction 0 deg for Model 1. As shownin the graph, the conspicuous peak values from the primary component (185 Hz) to the higher degree BPF
components including the second (370 Hz) through theeighth (1,480 Hz) components can be observed. The primary BPF is highest at 66.8 dB and the level is 27 dB higher
than the broadband noise level of about 40 dB. Similarly,
the secondary BPF component with a level of 58.0 dB, thethird component with a level of 62.2 dB and the fourth

2 000

Fig. 14 Experimental sound spectrum at assessment pointo
Indicates sound pressure level at inlet side 0 assessment pointof Model 1.

Inlet side
Inlet side
22.5 deg
45 degAssessment point

Reference point

100

Inlet side
67.5 deg: Model 3 (Predicted): Model 4 (Predicted): Model 5 (Predicted): Model 3 (Experimental): Model 4 (Experimental): Model 4 (Experimental)

-10
-20
-30

Inlet side
0 deg

Inlet side
Inlet side
22.5 deg
45 degAssessment point

Inlet side
67.5 deg

Fig. 15 Comparison between predicted and measured results
Indicates the results relative to BPF primary noise component (185 Hz).

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Sound pressure level (dB)(1) In the comparison of Models 1 and 2 with upstream
flow interaction devices, the BPF noise level with "crosstype" is about 7 dB higher than that with "straighttype."(2) In both cases with these flow interaction devices, noremarkable directivity can be seen.
(3) In the tendencies described above, both the experimental and predicted values are equivalent, and both
relative differences show excellent agreement.
(4) In the comparison of Models 3 and 4 with downstream
flow interaction devices, the experimental values differ from the predicted values. The BPF noise ispredicted to be propagated throughout the suction side;on the other hand in the experiment it has directivity
at a low level at the assessment points in the radial
direction.
(5) Also, in Models 3 and 4, both relative differences coincide within the error of about 3 dB at the assessment
points near the suction side in the axial direction (0 deg
and 22.5 deg).
(6) In Model 5 with no flow interaction device, a big differences in the distribution and the level can be seen
between the measured and the predicted values.
The difference between the predicted and experimental values for the cases where the flow interaction devices
are installed downstream as described in (4) and (5), is
attributed to the differences in the reflection of soundwaves and the sound insulation not being taken into consideration in the prediction code. When a flow interaction
device is installed upstream, since the static pressure fluctuation occurring on the rotor blade suction surface is thedominant factor for causing BPF noise, a solid wall surface which can shut off a sound wave at the noiseassessment points does not exist. On the other hand, when
the flow interaction device is installed downstream, themain static pressure fluctuation occurs on the rotor blade
pressure side, and the rotor blade itself and the solid wall
surface of the bellmouth casing, etc. exist in the noiseassessment point area. For this reason, it is thought thatthe experimental values show relatively lower values at
the assessment points in the fan radial direction than thepredicted values.
In order to eliminate the influence of reflection, soundinsulation, etc. as much as possible, the predicted value
was compared with the experimental value with regard
to the total sum of BPF noise levels at all assessment
points with the first harmonic as a guideline corresponding to the power level. Figure 16 shows the results thus
obtained. In Models 1 to 4 with flow interaction devices,
the figure shows excellent agreement, within 0.8 dB difference in the relative comparison between the predicted
and the experimental values. As for Model 5 with no flowinteraction device, there still exists a difference of about
2.5 dB. The reason for this is thought to be as follows. In
the prediction, it is assumed that the flow from upstream

10: Predicted: Experimental

5
0
-5
-10
-15
-20

Model 1 Model 2 Model 3 Model 4 Model 5
Model typeFig. 16 Comparison of overall BPF noise level between
predicted and measured result
Indicates high prediction accuracy for Models 1 to 4 with flowinteraction devices.

BPF noise level is fluctuating

Fig. 17 Noise level in sonar grapho
Indicates BPF noise level of Model 5 at assessment point of Inlet 0 .

is uniform and the code predicts periodic noise mainly
due to load noise. In the measurement, on the other hand,the flow around the test instrument was not equalized
sufficiently and it is thought that the BPF noise was amplified because the unstable periodic noise fluctuated at
the low level and eventually occurred, as shown in Fig.17
Fig.17.
However, in a CRFM, whose upstream and downstream
flows do not become uniform in the direction of fan rotation, this tendency is not a problem. The results obtained
from the present study, therefore, show that the BPF noise
can be predicted with an accuracy of about 1 dB for theoverall sound pressure, and within 3 dB for spatial distribution at the sound field where the effect of reflection
and sound insulation is comparatively small. Hence, it
has been confirmed that the newly developed technique
has sufficient practical accuracy to predict the BPF noiseof a CRFM.

10. Example of application of the BPF noise prediction
methodIn the CRFM design for each vehicle, a standard fan
is used in order to reduce the lead time and development costs. Regarding the various problems (airflow rate,
noise, input, etc.) to be considered when using a CRFM,
it is generally acceptable to take countermeasures using the shroud casing which requires individual designs
to be made for each vehicle. Moreover, since the shroud
casing configuration and dimensions, etc. are comparatively sensitive to fan noise including BPF noise, it ismostly closed to the rotating blade. Therefore the authors carried out an optimization design for the shroud
casing using the BPF noise prediction method in Fig. 1.
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Table 4 Control and error factors for CRFM

Control factor

Level 1

A Gap between strut androtor blade (mm)B Width of strut
C Fan diameter

(mm)
(mm)

D Strut shape
Error factor
A External static pressure

Shape of strut(Pa)

Level 2

Table 5 L9 (34) Orthogonal array for CRFM

Level 3

3

18

33

5

10

15

300

277.5

Control factor

Case

255

A

B

C

D

1

Level 1

Level 1

Level 1

Level 1

2

Level 1

Level 2

Level 2

Level 2

3

Level 1

Level 3

Level 3

Level 3

4

Level 2

Level 1

Level 2

Level 3

5

Level 2

Level 2

Level 3

Level 1

Rectangle

EllipseAirfoil

6

Level 2

Level 3

Level 1

Level 2

Level 1

Level 2

Level 3

7

Level 3

Level 1

Level 3

Level 2

8

Level 3

Level 2

Level 1

Level 3

9

Level 3

Level 3

Level 2

Level 1030

60

Gap between strut
and rotor blade

5dB

Width of strut

SPL

Fan diameter

Error factor
Level 3 (60 Pa)
Level 2 (30 Pa)
Level 1 (0 Pa)

1

2

3

4

5

6

7

8

9

Case No.
Fig. 19 Predicted BPF noise level based on Lg (34)
Indicates the result of numerical experiment based on orthogonalarray (L9).

Fig. 18 Control factor for CRFM
Indicates the section extracted at the time of application ofquality engineering.

A parametric study of the shroud casing by using numerical simulation with the prediction technique above
was performed, for the optimization of BPF noise reduction. The case selection of parametric study and the
optimization technique are based on the Taguchi method.
Table 4 shows the control factor, error factor and eachlevel for the shroud casing items for this study, whileFig.18 shows an outline of the control factors. Further,error factor was set as an external static pressure of
CRFM on the assumption that the flow channel pressure loss changes according to the layout difference
around the fan for each vehicle. The experimental plan
was made by assigning the control and error factors toTable 5 L9 (34) orthogonal table for CRFM. The error
factors were set as 3 levels for each experiment casenumber and the unsteady CFD and BPF noises werepredicted for a total of 27 cases. The BPF noise was assessed by the sound pressure level at a position 1 m
upstream of the fan axis, which is the noise assessment
point usually used for CRFM. Moreover, the noise waspredicted in all cases at the constant airflow volume of
1 200 m 3/h.
Figure 19 shows the predicted results for the BPF
noise in each case. As shown in the figure, the noise gets
worse for each case in the order of the error factors level 1

SN ratio (dB)

Strut-blade gap

Fan diameter

41.00
41.10
41.20

Shape of strut

Width of strut

41.30
A1 A2 A3

B1 B2 B3

C1 C2 C3

D1 D2 D3

Control factor
Fig. 20 Control factor effect diagram
Indicates SN ratio of each error factor.

(0 Pa) to Level 3 (60 Pa) because the fan load is increased
by adding an external static pressure at a constant airflow volume. The SN ratio for each case was calculatedon the basis of SN ratio formula using the above BPF
noise prediction values.
Figure 20 shows the factor effect. The optimum combination of design parameters could be obtained fromthe present design optimization study, and the SN ratioof each design parameter for BPF noise suggested thatthe potential interaction of the motor support beam androtor blade has a dominant influence. These results areuseful in the design of shroud casings of automotive
CRFMs.
Mitsubishi Heavy Industries, Ltd.
Technical Review Vol. 43 No. 3 (Sep. 2006)

811. Conclusion

References(1) Curle,N., The Influence of Solid Boundaries upon Aerodynamic
Sound, Proc. of the Royal Soc., A231 (1955) p.505(2) Shiraki, K. et al., Noise Prevention Design and Simulation,
Industry and Chemistry Systems (1987)(3) Kudo, T. et al., Development of Noise Reduction Method for
Radiator Fun of Automobile, Japan Society of MechanicalEngineers of Annual Meeting Lecture Collected Papers in2004 (7) pp.75-76 (2004) (in Japanese)A prediction technique using the unsteady CFD results for the BPF noise generated from the CRFM fan
has been developed for application to the noise reduction of the automotive CRFMs. A verification test forprediction accuracy was carried out, and it was confirmed, regarding the spatial sound field distribution,that the relative differences of BPF noise can be predicted with an accuracy to less than 1 dB in the regions
where solid surfaces causing reflection do not exist between the sound source and the sound reception point.
By a minimization study using the Taguchi method on
the BPF noise derived from the BPF noise prediction
technique, effective data on the CRFM shroud casing was
obtained. In the future, this prediction technique will be
used in order to accelerate the quantitative study of noise
reduction of CRFMs for various vehicles. Moreover, a new
analysis code considering reflection and diffraction will
be investigated in order to improve the accuracy of thespatial sound field distribution of BPF noise.

Atsushi Suzuki

Tetsuo Tominaga

Toshifumi Kudo

Tomoshige Takata

Tsuyoshi Eguchi

Mitsubishi Heavy Industries, Ltd.
Technical Review Vol. 43 No. 3 (Sep. 2006)9