New Indirect Tire Pressure Monitoring System Enabled by Adaptive Extended Kalman Filtering of Vehicle Suspension Systems
| Autor: | Dal-Seong Yoon, Dong-Hoon Lee, Gi-Woo Kim |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
TK7800-8360 Computer Networks and Communications Computer science Automotive industry tire pressure monitoring system unknown road roughness input 02 engineering and technology Tire pressure 020901 industrial engineering & automation 0203 mechanical engineering Control theory medicine Electrical and Electronic Engineering Controller design sensor fusion business.industry Estimator Stiffness 020302 automobile design & engineering Kalman filter Sensor fusion time-varying parameter estimation adaptive extended Kalman filter Hardware and Architecture Control and Systems Engineering Signal Processing tire stiffness Tire-pressure monitoring system medicine.symptom Electronics business |
| Zdroj: | Electronics, Vol 10, Iss 1359, p 1359 (2021) Electronics Volume 10 Issue 11 |
| ISSN: | 2079-9292 |
| Popis: | This paper presents a new indirect tire pressure monitoring system (TPMS) based on adaptive extended Kalman filtering with unknown input (AEKF-UI) estimation of vehicle suspension systems. The suggested methodology is based on the explicit correlation between tire pressure and tire stiffness and is available in real time. AEKF-UI is used to simultaneously estimate the time-varying parameter (tire stiffness) of vehicle suspension systems and the road roughness using an unknown input estimator. Simulation studies demonstrate that the proposed algorithm can simultaneously estimate tire stiffness (i.e., tire inflation pressure) variation and unknown road roughness input. The feasibility and effectiveness of the proposed estimation algorithm are verified through a laboratory-level experiment. This study offers a potential application for an alternative indirect TPMS and the estimation of unknown road roughness used for automotive controller design. |
| Databáze: | OpenAIRE |
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