High Speed Train Adhesion Control based on Extend Kalman Filter State Estimation

Efficient adhesion control is crucial for high-speed trains to ensure safe and reliable operation. It helps in preventing wheel slip or slide, which could lead to delays or increased wear on the tracks and wheels, even affect safety of the high speed train. Determining real-time accurate torque and train speed, is a key point of train adhesion control. This paper focuses on an Extended Kalman filter-based adhesion control approach which uses estimated the train state. The train adhesion model is built, and the optimization adhesion control method is proposed in the paper. The estimated real-time states are used in high speed train adhesion control. A Hardware-in-the-loop setup based on the real-time simulator PXIe-1082 is built to verify the proposed method. The result shows the method improves the adhesion utilization between the wheel and rail.