Aircraft operations during landing or takeoff depend strongly on runway surface
conditions. Safe runway operations depend on the tire-to-runway frictional force
and the drag offered by the aircraft. In the present research article, a
methodology is developed to estimate the braking friction coefficient for varied
runway conditions accurately in real-time. To this end, the extended Kalman
filtering technique (EKF) is applied to sensor-measured data using the on-ground
mathematical model of aircraft and wheel dynamics. The aircraft velocity and
wheel angular velocity are formulated as system states, and the friction
coefficient is estimated as an augmented state. The relation between the
friction coefficient and wheel slip ratio is established using both simulated
and actual ground roll data. Also, the technique is evaluated with the simulated
data as well as real aircraft taxi data. The accuracy of friction estimation,
with and without the measurement of normal reaction force on the landing gear,
is analyzed using the simulated data. The friction coefficient vs slip ratio
curve, derived from the empirical “Magic formula”, compares well with the
estimated maximum tire-to-ground braking friction, and a shift in optimal slip
is observed in actuality compared to the predictions. The brake disc friction
coefficient is also estimated during the process since the brake torque
measurements are not available in the actual data. The estimated friction
coefficient, which represents the real characteristics of the runway, can be
used to tune the control algorithms of the aircraft’s anti-skid brake management
system for various runway conditions. While improvements in anti-skid efficiency
alone may not directly prevent all runway excursions, accurate real-time
friction estimation enhances the predictability and reliability of braking
action, supporting safer operations under degraded or uncertain runway
conditions. Moreover, the real-time estimation of tire-to-ground friction
coefficient vs slip ratio curves can be used to develop adaptive control
algorithms for the brake management system.
