Road roughness estimation based on discrete Kalman filter with unknown input

The road roughness acts as a disturbance input to the vehicle dynamics, and causes undesirable vibrations associated with the ride and handing characteristics. Furthermore, the accurate measurement of road roughness plays a key role in better understanding a vehicle dynamic behaviour and active susp...

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Bibliographic Details
Published in:Vehicle system dynamics 2019-10, Vol.57 (10), p.1530-1544
Main Authors: Kang, Sun-Woo, Kim, Jung-Sik, Kim, Gi-Woo
Format: Article
Language:English
Subjects:
Acceleration
Active control
Algorithms
Kalman filter
Kalman filters
Profilometers
quarter-car suspension model
road roughness estimation
Roughness
unknown input
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Summary:The road roughness acts as a disturbance input to the vehicle dynamics, and causes undesirable vibrations associated with the ride and handing characteristics. Furthermore, the accurate measurement of road roughness plays a key role in better understanding a vehicle dynamic behaviour and active suspension control systems. However, the direct measurement by laser profilometer or other distance sensors are not trivial due to technical and economic issues. This study proposes a new road roughness estimation method by using the discrete Kalman filter with unknown input (DKF-UI). This algorithm is built on a quarter-car model and uses the measurements of the wheel stroke (suspension deflection), and the acceleration of the sprung mass and unsprung mass. The estimation results are compared to the measurements by laser profilometer in-vehicle test.
ISSN:0042-3114
1744-5159
DOI:10.1080/00423114.2018.1524151