Auralization of electric vehicle's interior noise SEA simulation

2021 ◽  
Vol 263 (4) ◽  
pp. 2887-2895
Author(s):  
Eunsoo Jo ◽  
Ki Sang Chae ◽  
Dong Chul Park ◽  
Wookeun Song ◽  
Moonju Hwangf
Keyword(s):  
Sound Pressure ◽  
Energy Analysis ◽  
Driving Simulator ◽  
Finite Impulse Response ◽  
Coherence Function ◽  
Interior Noise ◽  
Subjective Effect ◽  
Vehicle Interior ◽  
Time Signals ◽  
The One

Statistical Energy Analysis (SEA) has become an essential step to minimize the vehicle interior noise level. The outcome of SEA is typically 1/3 octave spectrum, and consequently it is difficult to understand the subjective effect of interior noise. This study investigated two approaches to achieve the binaural synthesis of SEA results. One is directly from the SEA 1/3 octave result and the measured coherence function. The other makes use of Source Path Contribution (SPC) to estimate the time signals on the exterior panels and subsequently applies the SEA results as a set of Finite Impulse Response (FIR) functions. Both approaches seem to result in realistic binaural signals as well as the correctly scaled sound pressure levels at the receivers. The one using SPC results can generate the input data for an NVH driving simulator by decomposing the harmonics and the masking noises. This means that the SEA result can be experienced by driving the simulated vehicle freely.

An Experimental Analysis of Interior Noise in an Ambulance and Noise Reduction with Damping Materials

2013 ◽  
Vol 316-317 ◽  
pp. 1118-1122
Author(s):  
Song Bai ◽  
Xin Xi Xu ◽  
Meng Yang ◽  
Xiao Hui Liu ◽  
Wei Hua Su ◽  
...  
Keyword(s):  
Structural Modification ◽  
Coherence Function ◽  
Interior Noise ◽  
Partial Coherence ◽  
Coherence Analysis ◽  
Analysis Method ◽  
Vehicle Interior ◽  
Single Output ◽  
Acoustic Contribution ◽  
Damping Materials

To solve the problem of an ambulance interior noise, a multi-input and single-output linear system model is established based on the partial coherence analysis method. In this model, vibration acceleration signals of panels are treated as input, sound pressure signals is treated as output. The relevant influence among the system inputs are ruled out and the partial coherence function value is considered as an indicator to estimate the panels’ acoustic contribution to the field point. On the basis of analysis, the structural modification with damping materials is performed on the panels with greater contribution. The results show that panels’ acoustic contribution can be analyzed by partial coherence analysis method effectively and structural modification with damping materials based on the method has significant effect on reducing the vehicle interior noise and decreasing additional mass.

Simulation and Optimization to Vehicle Interior Noise in Mid and High Frequency Using VAone

2012 ◽  
Vol 268-270 ◽  
pp. 851-855
Author(s):  
Xin Chen ◽  
Chang Feng Gao ◽  
Xiao Hua Geng ◽  
Chen Xie
Keyword(s):  
High Frequency ◽  
Energy Analysis ◽  
Noise Analysis ◽  
Good Alternative ◽  
The Body ◽  
Interior Noise ◽  
Vehicle Interior ◽  
Simulation And Optimization ◽  
Vehicle Interior Noise ◽  
Better Than

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.

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.

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