Optimal Utilization of Adhesion Force for Heavy-Haul Electric Locomotive Based on Extremum Seeking with Sliding Mode and Asymmetric Barrier Lyapunov Function

Abstract

An optimal utilization of adhesion force based on extremum seeking with sliding mode (SMES) and asymmetric barrier Lyapunov function (ABLF) is proposed for heavy-haul electric locomotives (HHELs), which can eliminate the wheel skidding at optimal adhesion point and achieves maximum traction for HHELs. First, the state equation of wheel-rail adhesion control system is described. The optimal utilization of adhesion force and anti-slip control are analyzed considering the condition changes at the wheel-rail surface. Then, the nonsingular terminal sliding mode observer (NTSMO) is designed to achieve the accurate adhesion coefficient of the wheel-rail. Finally, the SMES method for HHEL is developed to obtain the optimal slip speed and the maximum adhesion coefficient of the uncertain wheel-rail surface. Meanwhile, the ABLF controller is designed to achieve anti-slip control for HHELs in the optimal adhesion state. Comparing with the conventional differential acceleration control (DAC) method, the simulations and experiments verify that the proposed method can achieve optimal adhesion anti-slip control with quick dynamic response, and the HHEL achieves maximum traction.

Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

“…Lu et al [27] presented a robust adaptive cooperative control to control the slip velocity in high-speed trains. He et al and Zhao et al [28,29] introduced an integral sliding mode control to obtain the optimal adhesion. The advantage of the method is its robustness in dealing with model uncertainty and disturbances, while the dynamics of the traction motors has not been considered in the model.…”

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

“…To estimate the creep rate and achieve tracking control, a recursive least squares approach with a forgetting factor was suggested in [3], but the effects of unidentified perturbations on the system were not taken into consideration. A heavy-duty train adhesion control with sliding-mode extreme value searching in [4].This control technique, however, has a slow rate of convergence and significant steady-state oscillation. Therefore, a better control algorithm must be developed.…”

Maximum adhesion point search method of high-speed train based on fuzzy logic

“…Therefore, the core idea of optimal adhesion control is to obtain the maximum adhesion point of the current rail through online search along with the train running process and design the corresponding torque controller to control the train running at the maximum adhesion point. The main methods are: sliding mode control method [2] , adaptive control method [3] , predictive control method [4] , fuzzy control theory based method [5] and so on.…”