Vehicle center of gravity estimation without prior knowledge of vehicle parameters using a recursive least squares approach*

The position of the center of gravity (CG) of a vehicle is an important parameter as it significantly affects vehicle loads distribution and vehicle dynamics. This article proposes an approach to estimate the longitudinal position of the CG from inertial measurements. The proposed approach does not require prior knowledge of vehicle parameters apart from vehicle wheelbase. The estimation procedure combines a direct estimation from the equations of motion with the state variable filter method used in the identification of continuous time model from sampled data. The filter is chosen based on general knowledge of vehicle dynamics such as the order of magnitude of characteristic frequencies of pitch motion. The estimates are obtained through a least squares method with instrumental variables. The algorithm can be implemented in both offline batch and online recursive forms, with low computational cost suitable for embedded applications. The method is tested and validated on a high-fidelity road vehicle simulation, with good results for different load distributions.

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Publication Details

Published
2025-10-22
DOI
https://doi.org/10.1109/icsc67755.2025.11335081
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Vehicle center of gravity estimation without prior knowledge of vehicle parameters using a recursive least squares approach*

Damien Ebérard, Michaël Di Loreto, Paolo Massioni, Hamza Benadada
Vehicle Dynamics and Control Systems
article

Vehicle center of gravity estimation without prior knowledge of vehicle parameters using a recursive least squares approach*

Damien Ebérard, Michaël Di Loreto, Paolo Massioni, Hamza Benadada
article en

Abstract

The position of the center of gravity (CG) of a vehicle is an important parameter as it significantly affects vehicle loads distribution and vehicle dynamics. This article proposes an approach to estimate the longitudinal position of the CG from inertial measurements. The proposed approach does not require prior knowledge of vehicle parameters apart from vehicle wheelbase. The estimation procedure combines a direct estimation from the equations of motion with the state variable filter method used in the identification of continuous time model from sampled data. The filter is chosen based on general knowledge of vehicle dynamics such as the order of magnitude of characteristic frequencies of pitch motion. The estimates are obtained through a least squares method with instrumental variables. The algorithm can be implemented in both offline batch and online recursive forms, with low computational cost suitable for embedded applications. The method is tested and validated on a high-fidelity road vehicle simulation, with good results for different load distributions.

Université Claude Bernard Lyon 1 (FR), École Centrale de Lyon (FR), Centre National de la Recherche Scientifique (FR), Laboratoire Ampère (FR)
École Centrale de Lyon
Openalex Percentile: Top 57%
Vehicle Dynamics and Control Systems
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Vehicle center of gravity estimation without prior knowledge of vehicle parameters using a recursive least squares approach* — Damien Ebérard, Michaël Di Loreto, et al. · (2025) | TGRS Research Map | TGRS