Research on Aircraft Towing Taxiing Braking Control Based on Estimation of Road Surface Friction Coefficient

Towbarless aircraft towing system (TLATS) is gradually becoming the mainstream in airport operations.In aircraft towing and taxiing operation, the complex conditions of the road surface produce unpredictable potential risks to the driving state of the electric tractor, among which the road surface friction coefficient is a crucial factor that directly affects the safety and efficiency of the aircraft towing taxiing and braking. In order to achieve real-time estimation of the tire-road friction coefficient, a method is proposed for estimating the road surface friction coefficient in this paper, which is based on the normalized Dugoff tire model and the Unscented Kalman Filtering (UKF) algorithm. By establishing a dynamic model of the aircraft tractor and integrating it with the normalized Dugoff tire model, this paper uses the Extended Kalman Filter (EKF) algorithm and the UKF algorithm to estimate the friction coefficients under different road surface conditions, based on the tire loading conditions and tractor driving state parameters obtained from the integrated model. Simulation experiments under various road conditions are conducted in Simulink. The comparative analysis of the results shows that the method of estimating the road surface friction coefficient based on the normalized Dugoff tire model and the UKF algorithm is more effective and accurate in estimating the road surface friction coefficient during the aircraft towing taxiing process. Furthermore, by introducing the estimated road surface friction coefficient into the calculation of the Time-To-Collision (TTC), a new aircraft taxiing braking control strategy is proposed. The simulation results demonstrate the effectiveness and reliability of this strategy.