Abstract
As
automotive technology has been developed, gear whine
has become a prominent contributor for cabin noise as the
masking has been decreased. Whine is not the loudest source,
but it is of high tonal noise which is often highly unpleasant.
The gear noise originates at gear mesh. Transmission Error
acts as an excitation source and these vibrations pass through
gears, shafts and bearings to the housing which vibrates to
produce noise on surrounding air. As microgeometry
optimization target to reduce the fundamental excitation
source of the noise, it has been favoured method to tackle
gear whine noise, especially for manual transmission.
However, practicality of microgeometry optimization for the
planetary gear system has been still in question, because of
complex system structure and interaction among multi mesh
gear sets make it hard to predict and even harder to improve.
In this paper, successful case of whine noise improvement by
microgeometry is presented. System level simulation model
with accurate details of actual test system condition such as
clearances, measured microgeometry and test rig condition
were constructed. The vibration at the accelerometer locationat the housing was predicted using the model. The
comparison
of the result to test result showed very good
correlation. Especially, the absolute housing vibration level
matched very well, which allowed engineers to use the
simulation result during optimization process to make
decision quickly without having to run the actual test to know
if the improvement was sufficient enough to meet the
vibration target. Microgeometry optimization was done for all
gear set in the rear planetary. The predicted result of vibration
showed 3 m/s2 reduction at the target speed range under
target torque condition. The noise test result confirmed that
the noise was reduced by 5∼ 6 dBA and the design target
could be satisfied
Keywords
Transmission NVH, Whine, Micro geometry optimization,
System modelling, Planetary
6 Speed Automatic Transmission Vibration
Magnitude Prediction and Whine Noise
Improvement through Transmission System
Modeling2011-01-1553
Published
05/17/2011
Won Shin
Romax Technology, Ltd.
Ashish Kanase
Romax Solutions Pvt Ltd.
Sungwook Hwang, Sangbum Baek and Hyutae
Shim
Hyundai Motor Company
Seiwoong Oh
Romax Technology, ltd
Copyright © 2011 SAE International
doi:10.4271/2011-01-1553Downloaded from SAE International by University of Wisconsin - Madison , Sunday, September 09, 20181. Introduction
With
the advancement in automotive technology, gear whine
has become a prominent contributor for cabin noise as the
masking has been decreased. Whine is not the loudest source,
but it is of high tonal noise which is often highly unpleasant.
The gear noise originates at gear mesh. Transmission Error
[1] acts as an excitation source and these vibrations pass
through gears, shafts and bearings to the housing which
vibrates to produce noise in surrounding air and structure-
borne noise via the mounts on the casing. As microgeometry
optimization target to reduce the fundamental excitation
source of the noise, it has been favoured method to tackle
gear whine noise, especially for manual transmission [ 2].
However,
applying similar direct methods to planetary
system has not been practical, because of the complexity of
the system structure which consists of coupled multi mesh
condition making it hard to predict and even harder to
optimize.
The paper discusses such practical method in reducing gear
whine noise of a 6 speed FF automatic transmission by
microgeometry optimization of a planetary gear set.
At first, challenges in applying microgeometry optimization
to planetary gear set are presented. This is followed with
suggestions to overcome the challenges in modelling and
optimization. The result includes the validation of simulation
result by vibration testing to prove the fidelity of the
approach. Finally, the result of the numerical optimization is
presented
SAE_2011-01-1553_Hyundai_6 Speed Automatic Transmission Vibration Magnitude Prediction and Whine Noise Improvement through Transmission System Modeling
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