RT Journal Article
T1 Sensor fusion based on a Dual Kalman Filter for estimation of road irregularities and vehicle mass under static and dynamic conditions
A1 López Boada, Beatriz
A1 López Boada, María Jesús
A1 Zhang, Hui
AB Mass is an important parameter in vehicle dynamics because it affects not only safety but also comfort. The mass influences the three movements corresponding to vehicle dynamics. Therefore, having an accurate value of mass is essential for having a suitable model which will lead to proper controller and observer operation. Additionally, unlike other vehicle parameters, the mass can vary during a trip due to loading and unloading items and passengers onto the vehicle, greatly influencing its dynamics. This is critical in heavy vehicles where the mass can vary by around 400%. Therefore, the mass must be updated on-line. The novelty of this paper is the construction of a state-parameter observer which allows the mass under static and dynamic driving conditions to be estimated using measurements from sensors that can be mounted easily on vehicles. In this study, a vertical complete model is considered based on the dual Kalman filter for mass and road irregularities estimation using the data obtained from suspension deflection sensors and a vertical accelerometer. Both simulation and experimental results are carried out to prove the effectiveness of the proposed algorithm.
SN 1083-4435
YR 2019
FD 2019-06
LK https://hdl.handle.net/10016/28306
UL https://hdl.handle.net/10016/28306
LA eng
NO This work was supported by Projects TRA2008-05373/AUTand TRA2013-48030-C2-1-R from the Spanish Ministry ofEconomy and Competitiveness.
DS e-Archivo
RD 18 may. 2024