Improvement of active safety systems by the extended Kalman filter based estimation of tire-road friction coefficient

Author

Enisz, Krisztian ; Fodor, Denes ; Szalay, Istvan ; Kohlrusz, Gabor

Author_Institution

Dept. of Automotive Mechatron., Univ. of Pannonia, Veszprem, Hungary

fYear

2014

Firstpage

1

Lastpage

5

Abstract

The tire-road friction coefficient is a significant parameter of the motor and safety system control algorithms in electric and hybrid cars. This paper presents a new method able to estimate the instantaneous and maximum values of tire-road friction coefficient. The algorithm applies the discrete-time extended Kalman filter for state estimation. Based on two-wheel longitudinal vehicle dynamics a discrete-time nonlinear statespace model was implemented. A new real-time HIL (HardwareIn-the-Loop) simulation environment was created for verifying the Kalman filter based algorithm and the results were in concordance with the expectations.

Keywords

Kalman filters; friction; hybrid electric vehicles; mechanical engineering computing; nonlinear filters; roads; safety; tyres; vehicle dynamics; wheels; active safety systems; discrete-time extended Kalman filter; discrete-time nonlinear statespace model; electric cars; hardware-in-the-loop; hybrid cars; motor; real-time HIL; state estimation; tire-road friction coefficient; two-wheel longitudinal vehicle dynamics; Equations; Estimation; Friction; Mathematical model; Vehicle dynamics; Vehicles; Wheels; Hardware-in-the-loop; extended Kalman filter; friction coefficient; vehicle dynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Vehicle Conference (IEVC), 2014 IEEE International

Type

conf

DOI

10.1109/IEVC.2014.7056186

Filename

7056186