Sound Quality prediction for automotive components

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Sound Quality prediction for automotive
components

• Applications at Advanced Analysis Ltd

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Sound Quality Predictions Why and How ?

• WHY?
• The sound of a motorbike or car interior feels
  harsh.
• The interior sound of a vehicle is not sporty
  enough.
• The overall sound of a motorbike is not boomy,
  i.e. low frequencies are not heard loud enough.
• HOW?
• Noise source ranking tests identify main noise
  contributors. Noise prediction helps to identify
  frequency bands affected by the individual
  components. Hence, predictions help to shape
  the quality of the sound.
• Given that measured pressure data is available,
  predictions allow for rapid study of different
  models and for the generation of audio files for
  sound quality assessment.

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Applications Intake / Exhaust Sound Quality
Visualisation of pressure phase distributions
aids design of internal chambers and transfer
tubes for minimum noise transmission and/or
modifying the quality.
Sound pressure distribution of radiated noise
from intake system
Sound pressure distribution inside exhaust system
Sound quality prediction on exhaust system
Noise intensity vectors in Intake system
Click on the speakers!
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Applications Exterior Noise Radiation from
Structures
Engine covers noise radiation The graphs below
show a comparison of sound power levels (SWL) for
different materials. The vibrating surfaces were
those from an engine cover. Changes to the
geometry and/or material can modify the quality
of the noise radiated.
Intake manifold skin noise Rapid studies of
basic concepts to minimise or shift vibration
modes, and hence to obtain minimum radiated noise.
Noise radiation from engine assembly Rapid
studies of basic changes to the structure to
minimise noise levels. Also sound quality
assessment from predictions.
Click on the speakers!
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Applications Car Interior, Acoustic Materials
Study of sandwich type configuration Prediction
of the absorption coefficient and transmission
loss for foam type acoustic materials when
coupled to structures. Rapid optimization tools
predict the best foam thickness or other
parameter defining the foam acoustic properties.
Study of panels, Prediction of the sensitivities
of panel sandwiches (e.g. footwell, dash)
configuration with regards to absorption
coefficient and transmission loss.
Glass fibre Thickness10mm Density95kg/m3
Perforated metal sheet 0.9mm-thick. Open
area37 Hole radius1.5mm
Impedance sensitivity analysis Predictions help
to identify the sensitivity at the drivers ear
to the absorptive areas treated with acoustic
materials. This tool helps to identify the most
efficient areas to be modified in order to affect
noise levels and quality.
Sound level predicted at drivers ear
SPL distribution at 80 Hz
Panel Contribution
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Case Study Motorcycle Sound Quality Targets
Sound quality target generation AAL compiled a
set of different recording for different
motorcycles in order to help the client to decide
the direction for the final sound quality.
Furthermore, AAL generated artificial audio
samples for jury testing.
Actual motorbike recordings (All wave files are
normalised)
Suggested audio samples (All wave files were
normalised) The sound files below were generated
by AAL Engineering by mixing pure sine waves from
50Hz to 600Hz. These are intended to be a guide
for the sound quality target.
60s Bonneville, drive-by 2nd gear
908MD Bonneville, high revs (no gear)
Ducati 996R, on board recording
GEN_A
GEN_G
BMW R1150GS, on board recording
GEN_B
GEN_H
Harley-Davidson Sportster 883R, on board recording
GEN_C
GEN_I
Triumph 955i Daytona, on board recording
GEN_D
GEN_J
HondaV5 RCV, drive-by recording
GEN_E
GEN_K
GEN_F
NOTE The above recordings were taken at
different engine speeds and microphone positions.
Therefore, the comparisons should be done
carefully to take these different conditions in
consideration.
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Case Study Motorcycle Sound Quality Targets
Sound quality target generation AAL can supply
the frequency spectra of any recording. This
helps to identify the important frequencies
giving character to a particular sound.
Furthermore, it proves a very helpful information
when optimising a design using numerical
simulations.
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Case Study Exhaust Sound Quality Analysis
Predicted results The graphs show predicted SWL
for the baseline and AAL design. The predicted
audio files indicate the reduction achieve above
800Hz and the enhancement at low frequency (below
300Hz) achieved with the AAL design.
Acoustic model Figure on the left shows a typical
boundary element model (BEM or acoustic model)
for noise prediction.
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Case Study Final Results
Baseline recording
Note that the recordings on the left contain
frequencies up to 3000Hz only and corresponds to
short duration for fair comparison with
predictions. Furthermore, the recordings were
obtained from the whole motorbike not only the
exhaust.
AAL design recording
CONCLUSIONS The trends predicted in the analysis
can be heard, and correlated well with the actual
prototypes. Furthermore, the overall noise levels
of the motorbike were kept within legal noise
limits. This type of work was performed for the
development of the Triumph Bonneville silencers.
An SAE paper was written describing the work and
it is available on request. See below comments
extracted from the BIKE magazine in November
2000 regarding the sound quality of the new
Bonneville Getting the exhaust note right was
vital and a deep drone from the two pipes is as
throaty as youd expect given todays silencing
regs.