Locomotive wheel slip detection based on multi-rate state identification of motor load torque

This paper presents a locomotive slip phenomenon detection method based on the Multi-rate Extended Kalman Filter (MREKF) state identification method. The proposed method combines the multi-rate method and the EKF method to identify traction motor load torque in order to detect locomotive slip phenomenon. Unlike traditional methods, the proposed detection only based on electrical quantities, achieves a shorter detection time due to the much smaller time constants in the electrical systems. The adhesion availability, which is an important performance index of a locomotive, is improved by rapid detection method. An extended model which contains vector-controlled induction motor model, wheel-set multiple axle model and locomotive motion model is proposed. The locomotive slip phenomenon corresponding to the actual slipping is realized in the simulation. The simulation result matches with the actual data obtained from HXD2 locomotive. Moreover, the proposed locomotive slip phenomenon detection method has been applied to the extended model, and experimental results verified the accuracy and effectiveness of this model. A comprehensive analysis is proposed by compare multi-rate and single-rate EKF method. Experimental results depict that the detection time of slip phenomenon has been greatly reduced.