Reduction of Vehicle Interior Noise Using Our New Structural-Acoustic Sensitivity Analysis Methods

1991 ◽  
Author(s):  
Ichiro Hagiwara ◽  
Wakae Kozukue ◽  
Zheng-Dong Ma
Keyword(s):  
Sensitivity Analysis ◽  
Coupled System ◽  
Interior Noise ◽  
Design Stage ◽  
Vehicle Interior ◽  
Acoustic Coupling ◽  
Analysis Process ◽  
Analysis Methods ◽  
Orthogonality Conditions ◽  
Acoustic Sensitivity

Abstract Since interior noise has a strong effect on vehicle salability, it is particularly important to be able to estimate noise levels accurately by means of simulation at the design stage. The use of sensitivity analysis makes it easy to determine how the analytical model should be modified or the structure optimized for the purpose of reducting vibration and noise of the structural-acoustic systems. The present work focused on a structural-acoustic coupling problem. As the coefficient matrices of a coupled structural-acoustic system are not symmetrical, the conventional orthogonality conditions obtained in structural dynamics generally do not hold true for the coupled system. To overcome this problem, the orthogonality and normalization conditions of a coupled system were derived by us. In this paper, our sensitivity analysis methods are applied to an interior noise problem of a cabin model. It will be shown how a sensitivity analysis process is performed, and how vibration and noise can be reduced.

A Regression-Based Energy Method for Estimating Vehicle Interior Noise in Road Tests

2005 ◽  
Author(s):  
Shung H. Sung ◽  
Donald J. Nefske
Keyword(s):  
Energy Method ◽  
Transfer Functions ◽  
Interior Noise ◽  
Design Stage ◽  
Vehicle Design ◽  
Passenger Compartment ◽  
Vehicle Interior ◽  
Energy Excitation ◽  
Vehicle Architecture ◽  
Actual Response

A regression-based energy method is developed for rapid estimation of the overall passenger-compartment interior noise (dBA) and Articulation Index (AI) in a vehicle of prescribed architecture when the vehicle travels on a particular road at a particular speed. The method is developed for use in the early vehicle design stage when only limited vehicle architecture design information are known. Regression analyses from a database of vehicle on-road tests and vehicle wind-tunnel tests are used to identify the energy transfer functions that represent the prescribed vehicle architecture. Energy excitation from both tire-road interaction and aerodynamic loads is then used to predict the interior dBA and AI responses. Comparisons of the predicted versus measured dBA and AI responses show reasonable agreement for car and wagon-type vehicles, although limited architecture data somewhat underestimates the actual response in certain vehicles

Plane Wave Resonance in the Tire Air Cavity as a Vehicle Interior Noise Source

1995 ◽  
Vol 23 (1) ◽  
pp. 2-10 ◽  
Author(s):  
J. K. Thompson
Keyword(s):  
Closed Form Solution ◽  
Form Solution ◽  
Interior Noise ◽  
Cavity Resonance ◽  
Test Results ◽  
Vehicle Interior ◽  
Air Cavity ◽  
Vehicle Interior Noise ◽  
Wave Resonance ◽  
Resonance Frequencies

Abstract Vehicle interior noise is the result of numerous sources of excitation. One source involving tire pavement interaction is the tire air cavity resonance and the forcing it provides to the vehicle spindle: This paper applies fundamental principles combined with experimental verification to describe the tire cavity resonance. A closed form solution is developed to predict the resonance frequencies from geometric data. Tire test results are used to examine the accuracy of predictions of undeflected and deflected tire resonances. Errors in predicted and actual frequencies are shown to be less than 2%. The nature of the forcing this resonance as it applies to the vehicle spindle is also examined.

Active control for vehicle interior noise using the improved iterative variable step-size and variable tap-length LMS algorithms

2019 ◽  
Vol 67 (6) ◽  
pp. 405-414 ◽  
Author(s):  
Ningning Liu ◽  
Yuedong Sun ◽  
Yansong Wang ◽  
Hui Guo ◽  
Bin Gao ◽  
...  
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Convergence Speed ◽  
Interior Noise ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Vehicle Interior ◽  
Vehicle Interior Noise ◽  
Variable Step

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.

scholarly journals Analysis of vibrodiagnostics methods in the technical state study of designed multimedia mobile scenes

2019 ◽  
Vol 302 ◽  
pp. 01011
Author(s):  
Marcin Łukasiewicz ◽  
Michał Liss ◽  
Natalia Dluhunovych
Keyword(s):  
Modal Analysis ◽  
Diagnostic Tests ◽  
Research Process ◽  
Technical Condition ◽  
Technical State ◽  
Normal Operation ◽  
Design Stage ◽  
Analysis Methods ◽  
State Study ◽  
Diagnostic Research

The paper presents the possibilities of using vibroacoustic methods in the study of the technical condition of designed multimedia mobile scenes. In particular, the possibility of implementing modal analysis methods in modelling and diagnostic research process has been presented. The use of virtual methods enables diagnostic tests both at the design stage and at the stage of normal operation, whereas modal methods help to explain the nature of the work of the element under investigation.

scholarly journals Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation

2007 ◽  
Vol 11 (2) ◽  
pp. 793-817 ◽  
Author(s):  
Y. Tang ◽  
P. Reed ◽  
T. Wagener ◽  
K. van Werkhoven
Keyword(s):  
Sensitivity Analysis ◽  
Model Identification ◽  
Local Analysis ◽  
Time Interval ◽  
Watershed Model ◽  
Soil Moisture Accounting ◽  
Analysis Methods ◽  
Accounting Model ◽  
Sobol’S Method ◽  
Comparative Results

Abstract. This study seeks to identify sensitivity tools that will advance our understanding of lumped hydrologic models for the purposes of model improvement, calibration efficiency and improved measurement schemes. Four sensitivity analysis methods were tested: (1) local analysis using parameter estimation software (PEST), (2) regional sensitivity analysis (RSA), (3) analysis of variance (ANOVA), and (4) Sobol's method. The methods' relative efficiencies and effectiveness have been analyzed and compared. These four sensitivity methods were applied to the lumped Sacramento soil moisture accounting model (SAC-SMA) coupled with SNOW-17. Results from this study characterize model sensitivities for two medium sized watersheds within the Juniata River Basin in Pennsylvania, USA. Comparative results for the 4 sensitivity methods are presented for a 3-year time series with 1 h, 6 h, and 24 h time intervals. The results of this study show that model parameter sensitivities are heavily impacted by the choice of analysis method as well as the model time interval. Differences between the two adjacent watersheds also suggest strong influences of local physical characteristics on the sensitivity methods' results. This study also contributes a comprehensive assessment of the repeatability, robustness, efficiency, and ease-of-implementation of the four sensitivity methods. Overall ANOVA and Sobol's method were shown to be superior to RSA and PEST. Relative to one another, ANOVA has reduced computational requirements and Sobol's method yielded more robust sensitivity rankings.

Sign in / Sign up

Export Citation Format

Share Document