PRODUCT PROFILE 53
FIGURE 3 (ABOVE
LEFT): Integrated
acoustic toolkit
inside the MSC
Adams environment
FIGURE 4 (BELOW):
Electric motor noise
prediction workflow
FIGURE 5 ABOVE
RIGHT): Workflow
for electric motor
noise prediction
by Renault
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November/December 2019 • VehicleDynamicsInternational.com
sound. Such relatively new workflows
can greatly reduce the time and cost
required to conduct acoustic analysis on
moving mechanisms such as a gearbox,
allowing for more iterations in the same
time than with conventional methods.
Indeed the methodology fully automates
this workflow into a single simulation
environment by embedding an acoustic
solver into an MBD tool (Figure 3).
If deemed necessary, acoustic
engineers can also perform a more
detailed analysis by investigating
acoustic maps or further post-process
results and then analysing the acoustic
frequency content of their results.
Reducing electric motor noise
Noise radiation from an electromagnetic
motor is driven by the
structure of the motor that vibrates
due to the internal electromagnetic
forces in the air gap between the rotor
and stator of the motor. Indeed if
the frequency of the radial forces on
the stator teeth are close to, or equal
to, any of the natural frequencies of
the stator frame, resonance of the
stator will occur. This resonance leads
to deformation of the stator, which
ultimately causes vibrations and
generates noise. Assessing the noise
radiated by an electric powertrain
therefore requires co-simulation analysis
of structural vibrations induced by the
electromagnetic forces.
A hybrid engineering simulation
methodology (Figure 4) for predicting
electric motor noise has been created
by Renault in France (Reference 1) that
relies on a weak coupling between the
three steps of the process: the predictive
computation of electromagnetic forces,
structural vibrations and acoustic
radiation, respectively.
This multiphysics workflow has
been used to validate EV powertrain
designs at Renault. and relies on the
integration between 2D electromagnetic
simulation software, structural
deformation in MSC Nastran, and then
Actran for the acoustic prediction.
This workflow enables the Renault NVH
team to simulate the acoustic radiated
power of an EV powertrain at different
RPMs up to 10kHz in order to validate
the design of electric motors.
Summary
Car buyers generally have a very
high expectation of low noise levels
for electric vehicles. Predicting the
acoustic behavior of their electric
powertrain involves the study of the
noise generation mechanisms for
both the electric motor and the gear
reduction system.
This article illustrates a very clear
workflow for engineers to analyze the
noise generated by both the electric
motor and also the gear reducer,
leveraging multidisciplinary computeraided
engineering analyses using MSC
Software tools. The expertise generated
helps auto OEMs and suppliers improve
the acoustic signature of their electric
vehicle powertrains.
Reference
“Numerical methodologies to address
electromagnetic noise at each phase
of development of electric machines”
by G. Fritz and H. Mechmeche, SIA
International Conference, Automotive
NVH Comfort, 2014.
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