Machine Learning Based Method for Impedance Estimation and Unbalance Supply Voltage Detection in Induction Motors.

Induction motors (IMs) are widely used in industrial applications due to their advantages over other motor types. However, the efficiency and lifespan of IMs can be significantly impacted by operating conditions, especially Unbalanced Supply Voltages (USV), which are common in industrial plants. Detecting and accurately assessing the severity of USV in real-time is crucial to prevent major breakdowns and enhance reliability and safety in industrial facilities.

Speed Estimation of Six-Phase Induction Motors, Using the Rotor Slot Harmonics.

Multiphase machines have recently been promoted as a viable alternative to traditional three-phase machines. Most experts are looking for strategies to estimate the rotation speed of such complex systems, since speed data are required for high-performance control purposes. Traditionally, electromechanical sensors were used to detect the rotor speed of electric motors.

High-performance vector control without AC phase current sensors for induction motor drives: Simulation and real-time implementation.

The main purpose of this paper is to develop a high-level performance, and low-cost current sensorless control strategy for Induction Motor (IM) drives. Therefore, a new phase-current regeneration method, for current sensorless vector control in induction motor drives is introduced. The idea is based on the reconfiguration of the Luenberger adaptive observer for currents estimation, using the information provided by the dc-link voltage sensor.