An Investigation on the Data Mining to Develop Smart Tire

Jae-Cheon Lee, Hao Liu, Young Gi Seo, Seong Woo Kwak, Ho Seung Lee, Hae Jun Jo, Sangsu Park

2019

Abstract

A smart tire is required to improve driving safety for an intelligent vehicle especially for automated driving electric vehicles. It is necessary to provide information of tire contact forces (vertical, longitudinal, and lateral directions) to control velocity and steering angle of the autonomous vehicle so as to ensure driving stability. This study presents a smart tire system with the data mining to estimate the vertical load by using the tire deformation data in particular. Firstly, the hardware system construction of the smart tire in which tire deformation on driving by using strain gauge is described. And then the test condition is set up and total 27 sets of experimental data are processed to perform correlation analysis for specifications of measured waves. Next, the estimation algorithm of smart tire vertical load is derived by considering the area of tire-ground contact patch and also by introducing compensate coefficient of transverse direction length of contact area. The experimental results show the proposed estimation algorithm is feasible and precise. The advanced adaptive and precise estimation algorithm with artificial neural network will be developed further.

Paper Citation

in Harvard Style

Lee J., Liu H., Seo Y., Kwak S., Lee H., Jo H. and Park S. (2019). An Investigation on the Data Mining to Develop Smart Tire.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 480-487. DOI: 10.5220/0007311104800487

in Bibtex Style

@conference{icaart19,
author={Jae-Cheon Lee and Hao Liu and Young Seo and Seong Kwak and Ho Lee and Hae Jo and Sangsu Park},
title={An Investigation on the Data Mining to Develop Smart Tire},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={480-487},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007311104800487},
isbn={978-989-758-350-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - An Investigation on the Data Mining to Develop Smart Tire
SN - 978-989-758-350-6
AU - Lee J.
AU - Liu H.
AU - Seo Y.
AU - Kwak S.
AU - Lee H.
AU - Jo H.
AU - Park S.
PY - 2019
SP - 480
EP - 487
DO - 10.5220/0007311104800487