Editorial Type:
Article Category: Research Article
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Online Publication Date: 16 Dec 2024

Modelling Intrinsic Sources of Nonuniformity and Their Interplay

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Page Range: 294 – 322
DOI: 10.2346/144030
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ABSTRACT

Uniformity characteristics of a tire are a direct reflection of the quality of the manufacturing process that produced it. This is realized in the homogeneity of its different stiffnesses and dimensions around the tire. Evidently, this is the most closely monitored aspect for consistency, from the original equipment manufacturers and manufacturers alike, and the requirement for tighter acceptance criteria is ever-increasing.

However, the authors endeavor to find the lowest theoretical level for the same, given the intrinsic sources. The current study attempts to establish a framework to investigate the effect of the most pronounced factors individually, their interplay, and how their combined effect can be minimized. The present work on a 185/65R15 passenger car radial tire attempts to determine the effect of variable pitch sequencing as well as splicing and tread runout for a patterned tire on radial force variation (RFV). The study is carried out using finite element simulation for it presents the opportunity to study the individual effects systemically and economically. The study reveals a nearly 20% of the specification limit can be due to tread pattern sequence while the effect of the overlapping components may vary by 10% of the same limit. The study also suggests spotting arrangements to target and avoid. Finally, the authors present a method, captured in a MATLAB program that benefits the tire designer, plant engineer, and quality control manager.

Keywords: finite element analysis; tire uniformity; radial force variation; runout; fast Fourier transform; correlation coefficient; radial force peak-to-peak
Copyright: 2024
FIG. 1
FIG. 1

Tire segment highlighting major components.

FIG. 2
FIG. 2

Finite element tire modelling sequence.

FIG. 3
FIG. 3

Tread pattern configurations: (a) Slick pitch, (b) Mono pitch, (c) Variable pitch, and (d) Carcass segmentation.

FIG. 4
FIG. 4

Tire spotting arrangement.

FIG. 5
FIG. 5

Innerliner overlap.

FIG. 6
FIG. 6

Ply overlap.

FIG. 7
FIG. 7

Radial force variation due to varying order of element.

FIG. 8
FIG. 8

Radial force variation due to different mesh refinement.

FIG. 9
FIG. 9

Radial force variation due to contact definition.

FIG. 10
FIG. 10

Radial force variation due to simulation control parameter.

FIG. 11
FIG. 11

Radial force response for a slick pitch tire.

FIG. 12
FIG. 12

Radial force response for a mono pitch tire.

FIG. 13
FIG. 13

Radial force response for a variable pitch tire.

FIG. 14
FIG. 14

Effect of pitch sequencing on radial force.

FIG. 15
FIG. 15

Harmonic analysis of radial force variation data for a production tire.

FIG. 16
FIG. 16

A graphical comparison of harmonics values between test and FEA.

FIG. 17
FIG. 17

Correlation between normalized amplitudes of harmonics of test and FEA.

FIG. 18
FIG. 18

Influence of radial runout over radial force variation.

FIG. 19
FIG. 19

Correlation between radial runout and radial fore variation.

FIG. 20
FIG. 20

Validation of radial runout effect on radial force variation: (a) Test central radial run out, (b) Test RFV, and (c) FEA-derived RFV.

FIG. 21
FIG. 21

Radial force variation due to innerliner overlap.

FIG. 22
FIG. 22

Radial force variation due to ply overlap.

FIG. 23
FIG. 23

Radial force variation with default spotting combination.

FIG. 24
FIG. 24

Radial force variation with the best spotting combination.

FIG. 25
FIG. 25

Radial force variation with the worst spotting combination.

FIG. 26
FIG. 26

Harmonic decomposition of combined effect candidates.

FIG. 27
FIG. 27

Screenshot of the MATLAB program to achieve different RFV combinations.

FIG. 28
FIG. 28

Comparison between test and FEA for variable pitch.

FIG. 29
FIG. 29

Comparison between test and FEA for worst spotting.

FIG. 30
FIG. 30

Comparison between test and FEA for best spotting.

FIG. 31
FIG. 31

Comparison between test and FEA for worse sequence.

FIG. 32
FIG. 32

Comparison between test and FEA for better sequence.

Contributor Notes

1 Hari Shankar Singhania Elastomer and Tire Research Institute, Plot 437, Hebbal Industrial Area, Mysore, Karnataka, 570016, India
2 Corresponding author: Email: vkbedi@jkmail.com
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