Russian Federation
Russian Federation
Russian Federation
Kolomna Institute (branch) of the Moscow Polytechnic University (Senior Lecturer)
Russian Federation
Purpose: To create an algorithm for controlling locomotive traction effort that maximizes locomotive traction performance under varying adhesion conditions while minimizing wheel-rail slip forces. Methods: Fuzzy logic systems, fuzzy set and fuzzy logic theory, elements of artificial intelligence, automatic control theory, and numerical modelling techniques. Results: The presented flowchart for controlling locomotive traction effort with a fuzzy logic controller enables effectively to maximize locomotive traction effort through optimizing wheel slip control in response to changing adhesion conditions. Fuzzy control rules have been developed based on a linguistic evaluation of setpoint behaviour along the adhesion coefficient curve, eliminating the need for precise numerical modelling of wheel-rail contact. A fuzzy logic-based algorithm has been developed using a specialized MATLAB extension from the Fuzzy Logic Toolbox. Numerical simulations of the fuzzy controller’s performance have been conducted using the established full-scale longitudinal/vertical dynamic model of the 2TE25A diesel locomotive. Practical significance: The simulation results demonstrate the effectiveness of the proposed fuzzy logic-based controller, highlighting enhanced traction performance of the diesel locomotive across the entire range of speeds and various railway track conditions. The traction control algorithm can be used to design and implement advanced, high-efficiency wheel slip/slide protection systems, thereby significantly enhancing locomotive traction and optimizing wheel-rail wear.
Diesel locomotive, wheelset, slippage, adhesion, traction effort, adhesion coefficient, Polach model, contact conditions, fuzzy control, locomotive slide control
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