Work

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

Year: 2025

Type: conference-paper

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.

Source: International Conference on Systems and Control (ICSC)

DOI: 10.1109/icsc67755.2025.11335081

Authors: Hamza Benadada, Michael Di Loreto, Damien Eberard, Paolo Massioni

Institutions: Lyon 1 Université, École Centrale de Lyon, Centre National de la Recherche Scientifique, Institut de Recherche en Informatique de Toulouse, Laboratoire Ampère

Language: English

Topic: Vehicle Dynamics and Control Systems

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funder: École Centrale de Lyon