scholarly journals Intercultural Differences in the Perception of HVAC Sound Quality in Car Cabins: From Conventional to Electric Vehicles

2021 ◽  
Vol 11 (23) ◽  
pp. 11431
Author(s):  
Massimiliano Masullo ◽  
Katsuya Yamauchi ◽  
Minori Dan ◽  
Federico Cioffi ◽  
Luigi Maffei
Keyword(s):  
Factor Analysis ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Sound Quality ◽  
Japanese Subject ◽  
Remarkable Difference ◽  
Hvac System ◽  
Flow Rates ◽  
Japanese Group

In electric-powered cars, the production of which is increasing, the HVAC system is responsible for most of the noise inside the car’s cabin, causing significant discomfort for passengers. Moreover, the noise produced by the HVAC affects the perceptible sound inside the car cabin, significantly impacting the perceived quality of the vehicle. It is thus essential to investigate and quantify people’s preferences concerning HVAC noise. Our previous research revealed differences in the HVAC noise between hybrid electric (HEV) and internal combustion engine (ICEV) vehicles. A subsequent factor analysis revealed that the adjectives used to describe the sounds can be grouped into two main dimensions: Aesthetic and Loudness. The present paper highlights the results of a listening test that aimed to identify possible differences in the perception of HVACs’ sound quality between Italian and Japanese subject groups, for ICEV and HEV, in different functioning conditions. Results revealed that the most remarkable difference emerges at high air flow rates, where the Japanese group perceived the quality of sound and annoyance, respectively, to be significantly lower and significantly higher than the Italian group.

Perceptual Difference on HVAC Sound Quality between Electric and Conventional Vehicles

2021 ◽  
Vol 263 (2) ◽  
pp. 4189-4198
Author(s):  
Katsuya Yamauchi ◽  
Minori Dan ◽  
Federico Cioffi ◽  
Luigi Maffei ◽  
Massimiliano Masullo
Keyword(s):  
Electric Vehicles ◽  
Background Noise ◽  
Collaborative Research ◽  
Combustion Engine ◽  
Subjective Evaluation ◽  
Sound Quality ◽  
Hvac System ◽  
Air Flow Rate ◽  
Vehicle Noise ◽  
The Difference

The heating, ventilation and air-conditioning (HVAC) system is one of the most critical sources in in-vehicle noise environment, especially when cars are moving at low speed or at lower engine rotation. With the transition to electric vehicles (EV) from internal combustion engine vehicles (ICEV), the contribution of powertrain becomes lower on the background noise inside car cabins. The authors have been conducting a collaborative research on HVAC sound quality inside car cabins. In this paper the results of a subjective evaluation of HVAC sound quality were presented, that attempted to compare the perceptual differences among the two groups, i.e. EVs and ICEVs. The result revealed the difference in the noise perception among the two types of vehicles especially softer air flow rate conditions.

Investigation of the perceived sound quality of an automotive HVAC system

2006 ◽  
Author(s):  
Ricardo Penna Leite ◽  
Stephan Paul ◽  
Samir N. Y. Gerges
Keyword(s):  
Sound Quality ◽  
Hvac System

A study on sound quality of vehicle engine sportiness using factor analysis

2020 ◽  
Vol 34 (9) ◽  
pp. 3533-3543
Author(s):  
Jae Hyuk Park ◽  
Hansol Park ◽  
Yeon June Kang
Keyword(s):  
Factor Analysis ◽  
Sound Quality ◽  
Vehicle Engine

scholarly journals Sound Quality Estimation of Electric Vehicles Based on GA-BP Artificial Neural Networks

2020 ◽  
Vol 10 (16) ◽  
pp. 5567 ◽  
Author(s):  
Kun Qian ◽  
Zhichao Hou ◽  
Dengke Sun
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Back Propagation ◽  
Sound Quality ◽  
Quality Estimation ◽  
Sound Perception ◽  
Artificial Neural ◽  
Mlr Model

The sound quality (SQ) and sound perception assessments of electric vehicles (EVs) clearly differ from those of conventional internal combustion engine vehicles (ICEVs). Therefore, it is essential to describe and evaluate the SQ of EVs. To evaluate the SQ in EVs, it is necessary to organize evaluators for conducting subjective jury tests, which are time-consuming and labor-intensive. In addition, the evaluation results are subject to the evaluators themselves and other external interferences. With the advancement of machine learning and artificial neural networks (ANNs), this problem can be well solved. This paper outlines a model for SQ estimation in EVs based on a genetic algorithm-optimized back propagation artificial neural network (GA-BP ANN). Moreover, the correlation between the physical-psychoacoustical parameters and the subjective SQ estimations obtained from the jury tests was investigated in this study. It was found that the GA-BP ANN SQ model has many advantages in comparison with the multiple linear regression (MLR) model in terms of precision and generalization. In addition, this method is ready to be applied for rapidly evaluating the SQ in EVs without jury tests, and it can also be of high significance in dealing with the acoustical designs and improvements of EVs in the future.

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