학술논문

Model Modulated Predictive Control (M2PC) of Induction Motors including Magnetic Saturation and Iron Losses
Document Type
Conference
Source
2022 International Conference on Electrical Machines (ICEM) Electrical Machines (ICEM), 2022 International Conference on. :606-612 Sep, 2022
Subject
Engineering Profession
Power, Energy and Industry Applications
Signal Processing and Analysis
Employee welfare
Induction motors
Heuristic algorithms
Computational modeling
Predictive models
Iron
Numerical models
Rotating Induction Motor (RIM)
Model Predictive Control (MPC)
Predictive Current Control (PCC)
Language
Abstract
This paper proposes a Model Modulated Predictive Control (M2PC) for rotating induction motors (RIM) taking into consideration both the magnetic saturation and the iron losses. The proposed M2PC is based on a previously developed dynamic model of the RIM considering both self and cross saturation and iron losses; the proposed algorithm uses the discrete-time version of the dynamic model to compute the current prediction and the resulting predicted current error. The built-in PWM modulator chooses the optimal pair of voltage space-vector to be applied by the inverter to minimize the current error. The magnetic model permits obtaining good dynamic performance in every working condition. The results obtained in numerical simulation have shown that the control can maintain good dynamic performances in both loaded and unloaded working conditions.