Warning Effect Evaluation and Control for Vehicle Turn Signal Sound

The sound quality of a turn signal sound is directly related to the driving safety and influences comfort during driving. A turn signal sound and interior noise always exist simultaneously while driving. However, none of the studies are performed to observe and control the change of a turn signal sound when the vehicle interior noise was changed. Therefore, this paper develops a method to evaluate and control the warning effect of a turn signal sound masked by vehicle interior noise. First, the turn signal sound and the vehicle interior noise at different speeds are measured and the time-frequency characteristics of the turn signal sound is analyzed. Second, the pairwise comparison method is applied to subjectively evaluate the warning effect of the sounds and the warning effect of the turn signal sound at 6~speeds relative to that at 40~km/h was obtained. Third, a new hearing threshold evaluating the warning effect is developed and used as a sound metric. This metric is employed to evaluate objectively the warning effect of warning sounds at different speeds. The subjective evaluation results are consistent with the objective evaluation results, which confirms the validity of objective evaluation. To keep the warning effect of the warning sound during the driving, two methods of controlling the turn signal sound are proposed and will be researched further in the future.

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A New Method of Sound Quality Analysis Based on Design of Experiment

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001416580015 ◽

2016 ◽

Vol 30 (05) ◽

pp. 1658001

Author(s):

Gangping Tan ◽

Gang Jie ◽

Ming Cao

Keyword(s):

Active Noise Control ◽

Objective Evaluation ◽

Sound Quality ◽

Interior Noise ◽

Quality Analysis ◽

Optimum Level ◽

Optimization Strategy ◽

Vehicle Interior ◽

Band Noise ◽

Vehicle Interior Noise

An optimization strategy of sound quality was proposed to improve sound quality inside a vehicle. The frequency of vehicle interior noise was divided into sub-bands by equivalent rectangular bandwidth (ERB) in the frequency domain, and the intensity of sub-band noise located in the mid-low frequency can be modified by using the measure of active noise control (ANC) in order to analyze its influence on the sound quality of original noise. Orthogonal experiments of vehicle interior noise were conducted according to experimental design. A model of sound quality objective evaluation (SQOE) was proposed as an experimental index. The role of sub-band on the model of SQOE was analyzed at different speeds so as to achieve the optimum level, optimum combination of sound quality and main factors. The results, obtained by implementing the optimization strategy of sound quality, were verified by means of tests. By validation, it showed that optimum sound quality can be achieved by changing the intensity of sub-band noise.

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Sound Quality Evaluation for the Vehicle HVAC System After Active Noise Control

Volume 11: Mechanical Systems and Control ◽

10.1115/imece2008-66584 ◽

2008 ◽

Cited By ~ 2

Author(s):

In Hyung Yang ◽

O. Cheol Kwon ◽

Jung Youn Lee ◽

Jae-Eung Oh

Keyword(s):

Regression Model ◽

Noise Control ◽

Subjective Evaluation ◽

Active Noise Control ◽

Sound Quality ◽

Interior Noise ◽

Hvac System ◽

Vehicle Interior ◽

Active Noise ◽

Vehicle Interior Noise

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver’s perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. In previous study, we have developed to verify identification of source for the vehicle HVAC system through multiple-dimensional spectral analysis. Also we carried out objective assessments on the vehicle HVAC noises and subjective assessments have been already performed with 30 subjects. In this study, the linear regression models were obtained for the subjective evaluation and the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Appropriation of regression model is necessary to R2 value and F-value. And testing for regression model is necessary to Independence, Homoscedesticity and Normality. To enhance sound quality, we applied active noise control (ANC) which is effective in the low-frequency bandwidth. Primary noise of the HVAC system is less than 500Hz. As a result of ANC application, sound quality is improved by more quiet, powerful, expensive, smooth.

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SOUND QUALITY ANALYSIS AND PREDICTION OF VEHICLE INTERIOR NOISE BASED ON GREY SYSTEM THEORY

Fluctuation and Noise Letters ◽

10.1142/s0219477512500162 ◽

2012 ◽

Vol 11 (02) ◽

pp. 1250016 ◽

Cited By ~ 5

Author(s):

SHUMING CHEN ◽

DENGFENG WANG ◽

JIE LIANG

Keyword(s):

System Theory ◽

Prediction Models ◽

Subjective Evaluation ◽

Sound Quality ◽

Grey System Theory ◽

Interior Noise ◽

Quality Analysis ◽

Gray Relational Analysis ◽

Vehicle Interior ◽

Vehicle Interior Noise

This paper presents a novel effective methodology for sound quality analysis and prediction of vehicle interior noise using gray system theory. Four objective psychoacoustic parameters selected to evaluate acoustic performance of vehicle interior environment are loudness, sharpness, roughness, and fluctuation. Subjective evaluation is presented using paired comparison method, and Bradley–Terry model is also created. The relationship between subjective evaluation and psychoacoustic parameters is determined by using gray relational analysis. Meanwhile, the correlation among psychoacoustic parameters is also revealed. Sound quality prediction models are created based on GM (0, N) and GM (1, N) model. The prediction results show that GM (1, N) model is more capable than GM (0, N) model for prediction of sound quality. Thus, the analysis and prediction results confirm that the proposed method in this study can be a useful tool to analyze and predict sound quality of the vehicle interior noise.

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Hybrid time–frequency algorithm for active sound quality control of vehicle interior noise based on stationary discrete wavelet transform

Applied Acoustics ◽

10.1016/j.apacoust.2020.107561 ◽

2021 ◽

Vol 171 ◽

pp. 107561

Author(s):

Y.S. Wang ◽

S. Zhang ◽

H. Guo ◽

X.L. Wang ◽

C. Yang ◽

...

Keyword(s):

Quality Control ◽

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Sound Quality ◽

Interior Noise ◽

Discrete Wavelet ◽

Vehicle Interior ◽

Time Frequency ◽

Vehicle Interior Noise

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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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