Hybrid PI and Fuzzy Logic Control for Energy Optimization in Train Operations

This paper presents a Fuzzy logic-based train control algorithm designed to enhance energy efficiency across a complete railway route. The proposed framework dynamically integrates practical information such as curvature data, gradient profiles, and station schedules to optimize acceleration, coasting, and braking phases. By using Fuzzy logic, the algorithm adaptively balances energy consumption, travel time, and stopping precision. Key features include predictive speed scanning and adaptive PI control, enabling comprehensive energy optimization. Simulation results confirm significant energy savings or voltage regulation while maintaining operational reliability and precision. This study highlights the potential of Fuzzy-based control systems in advancing sustainable railway operations.