Development of a Multi-Factor Control System for the Electric Drives of Pumping Units in Coal Mining Quarries Utilizing an Extended Kalman Filter

This study presents the development of an intelligent sensorless control system for a pumping unit driven by an asynchronous motor under variable hydraulic load conditions. The proposed approach integrates an electromechanical motor model based on the Park–Gorev transformation with a hydraulic load model and applies an extended Kalman filter (EKF) for real-time estimation and prediction of stator current and rotor speed. Unlike conventional systems, the method eliminates the need for pressure and flow sensors by relying solely on electrical measurements. Simulation and experimental results demonstrate high accuracy, with deviations below 5%. The developed model improves energy efficiency, enhances system reliability, and enables stable operation under fluctuating conditions, making it suitable for industrial pumping applications.

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