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International Journal of Automotive Technology

, Volume 20, Issue 4, pp 789–800 | Cite as

Simulating Tire Inflation Pressure Loss Rate Test by the Ideal Material Method

  • Chen LiangEmail author
  • Xinyu Zhu
  • Changda Li
  • Guolin Wang
  • Liu Ji
Article
  • 2 Downloads

Abstract

Tire Inflation Pressure Loss Rate (IPLR) test is a widely accepted test method to evaluate the tire pressure retention performance, which helps increase fuel economy and prevent premature tire failures. At present, an IPLR test usually lasts for several months, which greatly reduces the efficiency of relevant research. Several analytical models are available to estimate the IPLR value, however, it mainly considers the gauge and permeability of innerliner, ignoring the effect of other components and detailed tire structure. In order to perform a thorough study of tire pressure loss process, a finite element model was developed with the material input of both mechanical and permeability properties of various rubber compounds and tire geometry input. A creative method, ideal material method, was proposed to describe the transient pressure loss process. Through this solution, a finite element model of Passenger Car Radial tire is established to predict IPLR, with a difference from the experimental result less than 5 %. Based on the model, air diffusion path in the tire is studied to better understand the process, which explains the bubble location in tire immersion tests. The effect of innerliner parameters, including halobutyl content, gauge and ending length of innerliner, on IPLR has been investigated based on simulation models.

Key words

Tire inflation pressure loss rate Mass diffusion Finite element analysis Innerliner Halobutyl 

Nomenclature

A

area, m2

C

mass concentration, mol/m3

D

diffusivity, m2/s

J

mass flux, mol/m2 s

N

amount of substance, mol

P

partial pressure, Pa

R

gas constant

S

solubility, mol/m3 Pa

T

temperature, K

t

time, s

V

volume, m3

x

distance, m

φ

normalized concentration, 1/Pa

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Notes

Acknowledgement

Thanks to Bentil Asafo-Duho, (PhD. Candidate at the School of Automotive and Traffic Engineering, Jiangsu University) for his assistance in improving the Language. Appreciations to ExxonMobil’s Engineer, Owen for his help during the IPLR and Rubber permeability test.

References

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Copyright information

© KSAE 2019

Authors and Affiliations

  • Chen Liang
    • 1
    Email author
  • Xinyu Zhu
    • 1
  • Changda Li
    • 2
  • Guolin Wang
    • 1
  • Liu Ji
    • 1
  1. 1.School of Automotive and Traffic EngineeringJiangsu UniversityZhenjiangChina
  2. 2.ExxonMobil Asia Pacific Research & Development Co. LtdShanghai Technology CenterShanghaiChina

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