Prediction of Low Frequency Vibration Caused by Power Train Using Multi-Body Dynamics

Event
SAE 2009 Noise and Vibration Conference and Exhibition
Authors Abstract
Content
1
To predict accurately low frequency vibration caused by the power train, it is essential to consider both the non-steady state characteristics of the engine exciting force and the frequency and amplitude dependent non-linear characteristics of the various components of the transfer system. Conventional steady-state linear analysis using finite element methods (FEM) is unable to handle these characteristics, and as a result, its prediction accuracy is insufficient. This research is based on a multi-body dynamics (MBD) model that is capable of handling non-steady state and non-linear analysis, into which in-cylinder pressure prediction methods were incorporated. The technology developed took into consideration the non-linear characteristics of the transfer system and thereby enabled highly accurate predictions of all systems associated with the vibration reaching the vehicle body. Engine in-cylinder pressure predictions based on empirical formulas were combined with MBD models including those for the engine mounts, the drive shaft constant velocity universal joints and the exhaust pipe ball joints. The prediction technology was used to predict low frequency vibration caused by the power train such as cranking vibration, idle vibration, and lock-up vibration in actual operating conditions and the predicted results correlated well with actual vehicle test results. Input contribution analysis of cranking vibration and idle vibration was also carried out to clarify the mechanisms at work.
Meta TagsDetails
DOI
https://doi.org/10.4271/2009-01-2193
Pages
7
Citation
Sugimura, H., Donoue, Y., Takei, M., and Yamaoka, H., "Prediction of Low Frequency Vibration Caused by Power Train Using Multi-Body Dynamics," SAE Int. J. Passeng. Cars - Mech. Syst. 2(1):1470-1476, 2009, https://doi.org/10.4271/2009-01-2193.
Additional Details
Publisher
Published
May 19, 2009
Product Code
2009-01-2193
Content Type
Journal Article
Language
English