Efficient engine encapsulation strategy using poroelastic finite element simulation 2024-01-2957
With the increasing importance of electrified powertrains, electric motors and gear boxes become an important NVH source especially regarding whining noises in the high frequency range. Engine encapsulation noise treatments become often necessary and present some implementation, modeling as well as optimization issues due to complex environments with contact uncertainties, pass-throughs and critical uncovered areas.
Relying purely on mass spring systems is often a too massive and relatively unefficient solution whenever the uncovered areas are dominant. Coverage is key and often a combination of hybrid backfoamed porous stiff shells with integral foams for highly complex shapes offer an optimized trade-off between acoustic performance, weight and costs. A dedicated experimental set-up has been designed in order to measure both structureborne and airborne NVH performances of engine encapsulation insulators applied on an engine casing placed in a coupled reverberant / semi-anechoïc rooms suite.
Experimental measurements, including airborne and structureborne Insertion Losses have been performed on a mocked-up test set-up with and without leakages and have been compared to an accurate poroelastic finite element model including maximum treatment mock-ups. A good correlation between simulation and measurements has been observed and the difficulties of this modeling task are pinpointed. Uncovered areas as well as tuckers radiation issues will be highlighted both experimentally and numerically and improvement potentials will be shown as well.
Author(s):
Arnaud Duval, Guillaume Crignon, Mickael Goret, Lei lei, Alexandre Wilkinson, Nicolas Dauchez, Laurent POLAC
Affiliated:
Treves, UTC, Renault
Event:
13th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Electric motors
Finite element analysis
Transmission gears
Engines
Simulation and modeling
Measurements
Optimization
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