A Method of the Locomotive Speed Estimation Based on Fuzzy Logic and Extended Kalman Filter

In this paper, a method is proposed to estimate the locomotive speed based on extended Kalman filter and fuzzy logic, with considering four-axle locomotive model. The wheel speed information is the only known input of the whole estimation system. Firstly, according to the locomotive dynamic model, combined with the extended Kalman filter, the estimated wheel speed and the estimated locomotive speed of each wheel pair can be obtained. Secondly, the estimated creep value and wheel acceleration of each wheel pair are determined by the estimated wheel speed and the estimated locomotive speed. Then the condition of rail surface is judged by the estimated creep value difference between different wheel pairs, and the estimated locomotive speed is further modified to obtain the corrected locomotive speed. Finally, the wheel acceleration and the creep value of each wheel pair are taken as the inputs of fuzzy logic to estimate the final locomotive speed. Simulation results show that this method can accurately estimate the locomotive speed.