Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability

To achieve sustainability goals, such as greenhouse gas emissions and environmental noise reduction, continuous innovation plays a key role in the vehicle industry. The noise emitted by vehicles negatively impacts both the environment and public health, making the development of noise reduction stra...

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Main Authors: Krisztián Horváth, Ambrus Zelei
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2024-12-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/15033
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author Krisztián Horváth
Ambrus Zelei
author_facet Krisztián Horváth
Ambrus Zelei
author_sort Krisztián Horváth
collection DOAJ
description To achieve sustainability goals, such as greenhouse gas emissions and environmental noise reduction, continuous innovation plays a key role in the vehicle industry. The noise emitted by vehicles negatively impacts both the environment and public health, making the development of noise reduction strategies crucial. Vibroacoustic simulation methodologies provide an opportunity to optimise vehicle power transmission systems by reducing the emitted noise level. Besides, the energy efficiency and performance of the vehicles can be improved by vibroacoustic simulations. In this research, a vibroacoustic simulation methodology is presented, focusing on the power transmission systems of vehicles. This approach integrates the Finite Element Method and Multibody Dynamics simulations with vibroacoustics to identify and redesign noisy components even during the conceptual design stage. This approach tackles the challenge of high-frequency tonal noise for electric vehicles, using psychoacoustic reviews to enhance passenger comfort. Key tasks involve electromagnetic force analysis in the drivetrain, structural vibration simulations, and noise reduction strategy optimisation using machine learning algorithms to reduce the reliance on physical prototypes. Capturing the current momentum of the industry, machine learning capabilities in vibroacoustic models can help engineers identify sources and eliminate or mitigate noise in the early design phase. Reducing the number of prototypes leads to more sustainable design processes. Our study shows the noise level can be reduced by 3-5 dB. This is particularly important in the context of electric vehicles, where high-frequency tone noise should be reduced, benefiting both passengers and their environment. Improving these factors is in line with the goals of the United Nations and improves the quality of urban life. Our research highlights the importance of vibroacoustic simulation and opens new directions in the field of noise reduction, promoting the spread of sustainable transport solutions.
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spelling doaj-art-f24d5eceefc44849829302a2dcd618ee2025-08-20T02:00:13ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162024-12-01114Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for SustainabilityKrisztián HorváthAmbrus ZeleiTo achieve sustainability goals, such as greenhouse gas emissions and environmental noise reduction, continuous innovation plays a key role in the vehicle industry. The noise emitted by vehicles negatively impacts both the environment and public health, making the development of noise reduction strategies crucial. Vibroacoustic simulation methodologies provide an opportunity to optimise vehicle power transmission systems by reducing the emitted noise level. Besides, the energy efficiency and performance of the vehicles can be improved by vibroacoustic simulations. In this research, a vibroacoustic simulation methodology is presented, focusing on the power transmission systems of vehicles. This approach integrates the Finite Element Method and Multibody Dynamics simulations with vibroacoustics to identify and redesign noisy components even during the conceptual design stage. This approach tackles the challenge of high-frequency tonal noise for electric vehicles, using psychoacoustic reviews to enhance passenger comfort. Key tasks involve electromagnetic force analysis in the drivetrain, structural vibration simulations, and noise reduction strategy optimisation using machine learning algorithms to reduce the reliance on physical prototypes. Capturing the current momentum of the industry, machine learning capabilities in vibroacoustic models can help engineers identify sources and eliminate or mitigate noise in the early design phase. Reducing the number of prototypes leads to more sustainable design processes. Our study shows the noise level can be reduced by 3-5 dB. This is particularly important in the context of electric vehicles, where high-frequency tone noise should be reduced, benefiting both passengers and their environment. Improving these factors is in line with the goals of the United Nations and improves the quality of urban life. Our research highlights the importance of vibroacoustic simulation and opens new directions in the field of noise reduction, promoting the spread of sustainable transport solutions.https://www.cetjournal.it/index.php/cet/article/view/15033
spellingShingle Krisztián Horváth
Ambrus Zelei
Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability
Chemical Engineering Transactions
title Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability
title_full Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability
title_fullStr Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability
title_full_unstemmed Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability
title_short Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability
title_sort noise reduction methods in the vehicle industry using vibroacoustic simulation for sustainability
url https://www.cetjournal.it/index.php/cet/article/view/15033
work_keys_str_mv AT krisztianhorvath noisereductionmethodsinthevehicleindustryusingvibroacousticsimulationforsustainability
AT ambruszelei noisereductionmethodsinthevehicleindustryusingvibroacousticsimulationforsustainability