A PSO-based computational framework to design active noise cancelation systems for smart vehicle enclosures

Mojtaba Porghoveh, Kourosh Heidari Shirazi*, Antonio Messia, M. Erden Yildizdag

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this study, active noise cancelation (ANC) systems are developed by a computational optimization framework based on particle swarm optimization (PSO), aiming to attenuate engine noise inside smart cubic vehicle enclosures. To have rapid estimation of acoustic properties, the main PSO algorithm is coupled with an analytical solution based on modified modal interaction method to evaluate the cost function. The optimum configurations, i.e., best positions and volume velocities of secondary sound sources, are defined for each resonant frequency. For numerical simulations, two vehicle enclosures of different size are considered to assess the applicability of the optimization algorithm. The overall performance of determined ANC systems is investigated, and it is shown that substantial noise reduction is achieved.

Original languageEnglish
JournalMathematics and Mechanics of Solids
DOIs
Publication statusAccepted/In press - 2022

Bibliographical note

Publisher Copyright:
© The Author(s) 2022.

Funding

The authors would like to express their gratitude to the Deputy of Research of Shahid Chamran University of Ahvaz and Iran’s National Elites Foundation for supporting this project. The authors would also like to thank the International Research Center for Mathematics & Mechanics of Complex Systems (M&MOCS) in Italy for providing the software package used in this work.

FundersFunder number
Shahid Chamran University of Ahvaz and Iran’s National Elites Foundation

    Keywords

    • active noise control
    • Engine noise
    • fluid–structure interaction
    • particle swarm optimization
    • resonant frequencies

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