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Technical Paper

Tire and Car Contribution and Interaction to Low Frequency Interior Noise

2001-04-30
2001-01-1528
A joint study was conducted between BMW and Goodyear with the objective of analysing the cause and identifying methods to reduce the structure-borne interior noise in a vehicle driving on rough road surfaces. A vibro-acoustic characterization of the car was performed by measuring the car vibro-acoustic transfer functions and by using a transfer path analysis technique to identify the main suspension parts affecting the interior noise at target frequencies. The vibration transmissibility characteristics of the tire were measured and also simulated by Finite Element in [1-200Hz] frequency range. The vibro-acoustic interaction between the tire and car sub-systems was examined. A Finite Element sensitivity analysis was used to define and build new prototype tires. A 3dB(A) interior noise improvement was obtained with these new tires at target frequencies.
Technical Paper

Structural Modelling of Car Panels Using Holographic Modal Analysis

1999-05-17
1999-01-1849
In order to optimise the vibro-acoustic behaviour of panel-like structures in a more systematic way, accurate structural models are needed. However, at the frequencies of relevance to the vibro-acoustic problem, the mode shapes are very complex, requiring a high spatial resolution in the measurement procedure. The large number of required transducers and their mass loading effects limit the applicability of accelerometer testing. In recent years, optical measuring methods have been proposed. Direct electronic (ESPI) imaging, using strobed continuous laser illumination, or more recently, pulsed laser illumination, have lately created the possibility to bring the holographic testing approach to the level of industrial applicability for modal analysis procedures. The present paper discusses the various critical elements of a holographic ESPI modal testing system.
Technical Paper

Digital Aeroacoustics Design Method of Climate Systems for Improved Cabin Comfort

2017-06-05
2017-01-1787
Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.
Technical Paper

Prediction of Eigenfrequencies and Eigenmodes of Seatbelt Retractors in the Vehicle Environment, Supporting an Acoustically Optimal Retractor Integration by CAE

2018-06-13
2018-01-1543
From an acoustical point of view, the integration of seatbelt retractors in a vehicle is a real challenge that has to be met early in the vehicle development process. The buzz and rattle noise of seat belt retractors is a weak yet disturbing interior noise. Street irregularities excite the wheels and this excitation is transferred via the car body to the mounting location of the retractor. Ultimately, the inertia sensor of the locking mechanism is also excited. This excitation can be amplified by structural resonances and generate a characteristic impact noise. The objective of this paper is to describe a simulation method for an early development phase that predicts the noise-relevant low frequency local modes and consequently the contact of the retractor with the mounting panel of the car body via the finite element method.
Technical Paper

Uncertainty Quantification in Vibroacoustic Analysis of a Vehicle Body Using Generalized Polynomial Chaos Expansion

2020-09-30
2020-01-1572
It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.
Technical Paper

Challenges in Vibroacoustic Vehicle Body Simulation Including Uncertainties

2020-09-30
2020-01-1571
During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.
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