Article Peer-Reviewed
Dynamic Parameter Identification of a Bicycle Using Sliding Mode Observer and Particle Swarm Optimization
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Laboratoire Perceptions, Interactions, Comportements Simulations des usagers de la route et de la rue (PICS-L), Components and Systems Department (COSYS), Gustave Eiffel University, Champs sur Marne 77420, France
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Laboratoire Images, Signaux et Systèmes Intelligents, Université Paris-Est Créteil, France
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For correspondence.
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Received: 7 October 2024 Accepted: 11 July 2025 Published: 12 September 2025
Abstract
The aim of the present work is to identify the unknown dynamic parameters of a bicycle using a sliding mode observer and Particle Swarm Optimization (PSO) approaches. The estimation of bicycle dynamics requires a good knowledge of dynamic parameters such as damping coefficient, spring stiffness, and unsprung masses, among others. In this paper, suspension stiffness and damping coefficient have been identified using the Least Squares Method and compared with those obtained using the PSO technique. Real-time tests have been carried out on an instrumented bicycle equipped with various sensors to measure its dynamics. The measures coming from these sensors have been considered to validate the estimation tools. However, only the vertical wheel displacement measurements have been used to perform the observer. Experimental results are presented and discussed to demonstrate the quality of the proposed approach.
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Copyright © 2025
Imine et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use and distribution provided that the original work is properly cited.
Funding
This work is funded by Marie Skłodowska-Curie actions (H2020 MGA MSCA-ITN) within the SAFERUP project under grant agreement number 765057.
Cite this Article
Imine, H., Madani, T., & Shoman, M. (2025). Dynamic Parameter Identification of a Bicycle Using Sliding Mode Observer and Particle Swarm Optimization. Highlights of Vehicles, 3(2), 15–29. https://doi.org/10.54175/hveh3020002
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