A Study of Vehicle Interior Noise Using Statistical Energy Analysis

Finite Element-Statistical Energy Analysis (FE-SEA) hybrid method is better than SEA method for vehicle interior noise analysis in mid frequency. The noise predictions using FE-SEA in mid and SEA in high frequency are good in consistent with the experiments, so the computer-aided simulation using above two methods is a good alternative to experiments. The results shows that the Poly Methyl Meth Acrylate (PMMA) instead of glass as the windshield material can reduce the interior noise at the driver’s ear in mid frequency, also lighten the body weight. The results shows the new polymer transparent material can looked as a good new way for vehicle interior noise reduction and body lightweighting.

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

Tire Science and Technology ◽

10.2346/1.2137495 ◽

1995 ◽

Vol 23 (1) ◽

pp. 2-10 ◽

Cited By ~ 23

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.

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

Noise Control Engineering Journal ◽

10.3397/1/376737 ◽

2019 ◽

Vol 67 (6) ◽

pp. 405-414 ◽

Cited By ~ 2

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.

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