Prediction method for the reaction force of vehicle door sealing systems

The accuracy of calculating the reaction force in vehicle sealing systems using moment equilibrium equations from statics is highly dependent on the degree of simplification in the mathematical model. This study demonstrates that employing the Finite Element (FE) method allows for a comprehensive consideration of the coupling effects between the door and the flexible seal, thereby eliminating errors inherent to model simplification and single-boundary variables. Consequently, this approach improves the prediction accuracy of the sealing system's reaction force. In this work, a multi-boundary coupling simulation method for a vehicle door sealing system was established using the Finite Element (FE) method, which accounts for the interaction between the seal and the complex door structure. The results, based on data from three distinct vehicle models (with three doors tested per model), show a mean absolute percentage error (MAPE) of 7% between the simulated and experimentally measured static closing forces. This close agreement verifies the reliability of the proposed method. This study provides a comprehensive strategy for predicting and optimizing the reaction force in vehicle sealing systems. It was found that a 75% increase in the compression load deflection (CLD) of the lock-side seal yields a 22% increase in the total sealing system reaction force.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-11-25
DOI
https://doi.org/10.1371/journal.pone.0336802
Primary Topic
Tribology and Lubrication Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prediction method for the reaction force of vehicle door sealing systems

Zhong Yang, Z. Y. Wang, Guoqing Chen, Luoxing Li et al.
PLoS ONE
Tribology and Lubrication Engineering
article

Prediction method for the reaction force of vehicle door sealing systems

Zhong Yang, Z. Y. Wang, Guoqing Chen, Luoxing Li, Zhengqing Liu, Jing Huang
article en

Abstract

The accuracy of calculating the reaction force in vehicle sealing systems using moment equilibrium equations from statics is highly dependent on the degree of simplification in the mathematical model. This study demonstrates that employing the Finite Element (FE) method allows for a comprehensive consideration of the coupling effects between the door and the flexible seal, thereby eliminating errors inherent to model simplification and single-boundary variables. Consequently, this approach improves the prediction accuracy of the sealing system's reaction force. In this work, a multi-boundary coupling simulation method for a vehicle door sealing system was established using the Finite Element (FE) method, which accounts for the interaction between the seal and the complex door structure. The results, based on data from three distinct vehicle models (with three doors tested per model), show a mean absolute percentage error (MAPE) of 7% between the simulated and experimentally measured static closing forces. This close agreement verifies the reliability of the proposed method. This study provides a comprehensive strategy for predicting and optimizing the reaction force in vehicle sealing systems. It was found that a 75% increase in the compression load deflection (CLD) of the lock-side seal yields a 22% increase in the total sealing system reaction force.

PLoS ONEVol. 20(11)
Hunan University (CN), Hunan Institute of Engineering (CN), Zhejiang University of Technology (CN)
Openalex Percentile: Top 62%
Tribology and Lubrication Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.