In order to make the locomotive work in the optimal adhesion state, a sliding mode control algorithm based on extended Kalman filter (EKF) is proposed. Firstly, based on the wheelrail dynamics and the locomotive adhesion model, the EKF is used to approximate the wheelset speed and the vehicle body speed of the locomotive. Then, in order to overcome the external disturbance on the system, a sliding mode control algorithm based on exponential convergence disturbance observer is proposed. Considering the problem that the optimal wheelrail creep speed is unknown, a variable steplength search algorithm is designed according to the locomotive sticking model to track the optimal creep speed of the current track surface. Simulation results show that the EKFbased sliding mode control algorithm can effectively improve the stability of locomotive operation and the utilization of adhesion.