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 state-space model was implemented. A new real-time HIL (Hardware-In-the-Loop) simulation environment was created for verifying the Kalman filter based algorithm and the results were in concordance with the expectations.
Improvement of active safety systems by the extended Kalman filter based estimation of tire-road friction coefficient
2014-12-01
491065 byte
Conference paper
Electronic Resource
English
Extended Kalman Filter Based Road Friction Coefficient Estimation and Experimental Verification
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