Study of seat-to-head vertical vibration transmissibility of commercial vehicle seat system through response surface method modeling and Genetic Algorithm

dc.contributor.authorZhao, Yuli
dc.contributor.authorBi, Fengrong
dc.contributor.authorKhayet Souhaimi, Mohamed
dc.contributor.authorSymonds, Timothy
dc.contributor.authorWang, Xu
dc.date.accessioned2026-01-09T16:47:22Z
dc.date.available2026-01-09T16:47:22Z
dc.date.issued2023-02
dc.description2023 Elsevier Ltd.
dc.description.abstractLow-frequency vibration is a significant hazard to commercial vehicle drivers. Research on how to reduce seat vibration and improve human comfort in a seating system through seat design optimization is important. The novelty of this paper is to study the sensitivity analysis of seat design parameters and their interaction effects and optimize seat design for the minimum vibration transmission to human dri-vers. The uniqueness of this paper is the identification of the system parameters from the measured vibration acceleration data rather than from the material test.The purpose of this paper is to develop a prediction model of vibration transmissibility from input design parameters using the response surface method modeling. The statistical significance of the RSM model will be validated by analysis of variance. The design parameters will be optimized through the RSM modeling and Genetic Algorithm.The method can enhance the vibration isolation performance of the existing vehicle seat suspension system with reduced cost and without additional parts and energy consumption and make the design change and optimization of the seat suspension system simple and easy to be implemented. According to the research results, the vibration transmissibility ratio of the optimized seat system is reduced by about 10%.
dc.description.departmentDepto. de Estructura de la Materia, Física Térmica y Electrónica
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipAustralian Research Council
dc.description.statuspub
dc.identifier.citationZhao, Y., Bi, F., Khayet, M., Symonds, T., & Wang, X. (2023). Study of seat-to-head vertical vibration transmissibility of commercial vehicle seat system through response surface method modeling and Genetic Algorithm. Applied Acoustics, 203, 109216.
dc.identifier.doi10.1016/j.apacoust.2023.109216
dc.identifier.essn1872-910X
dc.identifier.issn0003-682X
dc.identifier.officialurlhttps://dx.doi.org/10.1016/j.apacoust.2023.109216
dc.identifier.relatedurlhttps://www.sciencedirect.com/science/article/pii/S0003682X23000142?via%3Dihub
dc.identifier.urihttps://hdl.handle.net/20.500.14352/129790
dc.journal.titleApplied Acoustics
dc.language.isoeng
dc.page.final109216-36
dc.page.initial109216-1
dc.publisherElsevier
dc.relation.projectIDLP160100132
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.cdu51-73
dc.subject.cdu656.13
dc.subject.keywordSeat vibration isolation
dc.subject.keywordParameter identification
dc.subject.keywordSensitivity analysis
dc.subject.keywordGenetic Algorithm
dc.subject.keywordResponse surface method
dc.subject.ucmFísica-Modelos matemáticos
dc.subject.unesco3317 Tecnología de Vehículos de Motor
dc.titleStudy of seat-to-head vertical vibration transmissibility of commercial vehicle seat system through response surface method modeling and Genetic Algorithm
dc.typejournal article
dc.type.hasVersionAM
dc.volume.number203
dspace.entity.typePublication
relation.isAuthorOfPublication8e32e718-0959-4e6c-9e04-891d3d43d640
relation.isAuthorOfPublication.latestForDiscovery8e32e718-0959-4e6c-9e04-891d3d43d640

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