High speed train optimal adhesion control method based on a Cubature Kalman filter

Abstract

The safe running of high-speed trains depends on the adhesion between the wheel and the rail. This paper suggests an optimal adhesion control for high-speed trains based on the use of the CKF (Cubature Kalman Filter) in order to completely exploit the adhesion between the wheel and rail and attain the ideal adhesion condition. The method allows for the approximative estimate of train speed using CKF and is based on the wheel-rail dynamics and high-speed train adhesion model. The extremum search algorithm without steady-state oscillation is used to build an optimization adhesion control, which eventually directs the train to run as closely as feasible to the peak adhesion point, overcoming the effects of external interference and estimating errors on the system. Finally, MATLAB/Simulink is used to create a simulation model of the adhesion control for the traction transmission of the CRH2 high-speed train. With an average adhesion utilization rate over 95%, the simulation results demonstrate the viability of the suggested approach, ensuring the effective and secure running of high-speed trains.