Loss Minimization Model Predictive Current Control for Linear Induction Motors

Abstract

To further improve the operating efficiency of linear induction motor, this paper proposes a loss minimization model predictive current control method based on governable loss online calculation. First, the method derives the equivalent circuit of linear induction motor containing independent iron loss branches, and establishes the loss model containing iron loss. Second, the expressions of stator d-axis current with governable losses and secondary flux amplitude are derived from theoretical analysis, and then a given value of stator d-axis current is derived when the governable losses are minimal. Then, a chain observer is designed to observe the secondary flux and calculate the governable loss and stator d-axis current under the current operation. Finally, a method is proposed to introduce the stator d-axis current observation results into the model predictive current control, which ensures the loss suppression effect and improves the dynamic performance at the same time. In addition, this article also compares the loss minimization controllers with or without iron loss. The simulation results are consistent with the theory, and the optimal control of the secondary flux of the linear induction motor can be successfully realized, thus effectively reducing the energy loss of the motor in the dynamic operation process. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.