Motorcycle inertial parameters identification via algorithmic computation of state and design sensitivities

Majda Fouka (1) , Lamri Nehaoua (1) , Hichem Arioui (1) , Saïd Mammar (1)

1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes

Recent advanced riding assistance safety systems, such as electronic yaw stability control, adaptive cruise control, and lane-keeping systems, require good approximations of motorcycle inertial properties, such as yaw, roll and pitch moment of inertia, this parameter can vary significantly with the rider's weight and heavy baggage placed on the luggage rack. This paper presents further research on parametric identification of two wheeler vehicles, carried out using a recursive Levenberg-Marquardt parameter identification formulation. This approach needs the use of sensitivity functions to identify acceleration responses in time domain by updating coupled inertial parameters value. The identification algorithm is implemented in MATLAB / Simulink software. Data and prior value are taken from the professional motorcycle simulation software BikeSim (based on high fidelity virtual motorcycle models).

Domaines: Automatique / Robotique

Majda Fouka, Lamri Nehaoua, Hichem Arioui, Saïd Mammar. Motorcycle inertial parameters identification via algorithmic computation of state and design sensitivities. IEEE Intelligent Vehicles Symposium (IV 2018), Sep 2018, Changshu, Suzhou, China. pp.3926--3929, ⟨10.1109/IVS.2018.8500437⟩. ⟨hal-01948644⟩