Relative velocity estimation for semi-active suspension with disturbance-decoupled Kalman filtering using production vehicle sensors

This paper presents a method for estimating the relative velocity of a semi-active suspension using in-vehicle sensors. To overcome the challenges of unobservability of the full vehicle model and the inaccuracies inherent in 1/4 and 1/2 vehicle models, a disturbance-decoupled observer is adapted, incorporating model compensation. An augmented Kalman filter is employed to enable relative velocity estimation without needing prior knowledge of the sprung mass. Additionally, road height is estimated using the front suspension’s relative velocity, eliminating the need for the wheelbase preview assumption. In addition, roll motion compensation improves the accuracy of the estimation using in-vehicle 3D-IMU sensors. The proposed method is validated through both simulations and vehicle experiments. The results demonstrate that this approach effectively reduces the substantial estimation errors found in previous studies, especially during severe pitch and roll motions.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Published
2026-06-25
DOI
https://doi.org/10.1177/09544070261458412
Primary Topic
Vibration Control and Rheological Fluids
Type
article
Field-Weighted Citation Impact
0.00
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article

Relative velocity estimation for semi-active suspension with disturbance-decoupled Kalman filtering using production vehicle sensors

Seibum B. Choi, Byungjun Kim, Yun-Tae Kim, Sooyoung Kim
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Vibration Control and Rheological Fluids
article

Relative velocity estimation for semi-active suspension with disturbance-decoupled Kalman filtering using production vehicle sensors

Seibum B. Choi, Byungjun Kim, Yun-Tae Kim, Sooyoung Kim
article en

Abstract

This paper presents a method for estimating the relative velocity of a semi-active suspension using in-vehicle sensors. To overcome the challenges of unobservability of the full vehicle model and the inaccuracies inherent in 1/4 and 1/2 vehicle models, a disturbance-decoupled observer is adapted, incorporating model compensation. An augmented Kalman filter is employed to enable relative velocity estimation without needing prior knowledge of the sprung mass. Additionally, road height is estimated using the front suspension’s relative velocity, eliminating the need for the wheelbase preview assumption. In addition, roll motion compensation improves the accuracy of the estimation using in-vehicle 3D-IMU sensors. The proposed method is validated through both simulations and vehicle experiments. The results demonstrate that this approach effectively reduces the substantial estimation errors found in previous studies, especially during severe pitch and roll motions.

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Korea Advanced Institute of Science and Technology (KR), Sookmyung Women's University (KR), Korea Automotive Technology Institute (KR)
Affordable and clean energy
Openalex Percentile: Top 10%
Vibration Control and Rheological Fluids
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