Structural Strength Evaluation of the Lightweight Frame of Bus Passenger Seat with High-Tensile Material and Analysis of the Importance of Independent Variables by Regression

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Authors Abstract
Content
This study aims to develop a lightweight bus passenger seat frame by conducting structural nonlinear finite element analysis (FEA) on various thickness combinations of seat frame components to identify the optimal configuration. The thicknesses of critical structural members that primarily bear the load when force is applied to the seat frame were selected as independent variables, while stress on each component and compliance with ECE R14 seatbelt anchorage displacement regulations were set as dependent variables. A regression analysis was performed to calculate the importance of each component and analyze the influence of each design variable on the dependent variables. Strain gauges were attached to critical areas of the actual seat frame to conduct a seatbelt anchorage test, and simulations under identical conditions were performed using the nonlinear FEA software (LS-DYNA) to validate the reliability of the analysis results. The optimized seat frame exhibited a maximum stress of 734 MPa and a displacement of 300.5 mm, satisfying the ECE R14 compliance criteria. A total of 81 scenarios with varying thickness combinations for the seat frame components were generated, and the results of each scenario were used to analyze the importance of design variables on the seat frame’s structural strength. The regression model achieved an R2 value of 0.927, confirming its reliability in predicting the structural response. These findings contribute to the development of optimized lightweight seat frames that enhance both safety and weight efficiency in commercial vehicles.
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DOI
https://doi.org/10.4271/02-18-04-0022
Pages
13
Citation
Ko, Y., Cho, K., Lee, J., and Kang, K., "Structural Strength Evaluation of the Lightweight Frame of Bus Passenger Seat with High-Tensile Material and Analysis of the Importance of Independent Variables by Regression," Commercial Vehicles 18(4), 2025, https://doi.org/10.4271/02-18-04-0022.
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Publisher
Published
May 10
Product Code
02-18-04-0022
Content Type
Journal Article
Language
English