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Energy-efficient predictive control for field-orientation induction machine drives

  • Purpose. To improve the efficiency of the closed-cycle operation of the field-orientation induction machine in dynamic behavior when load conditions are changing, considering the nonlinearities of the main inductance. Methodology. The optimal control problem is defined as the minimization of the time integral of the energy losses. The algorithm observed in this paper uses the Matlab/Simulink, dSPACE real-time interface, and C language. Handling real-time applications is made in ControlDesk experiment software for seamless ECU development. Findings. Adiscrete-time model with an integrated predictive control scheme where the optimization is performed online at every sampling step has been developed. The optimal field-producing current trajectory is determined, so that the copper losses are minimized over a wide operational range. Additionally, the comparison of measurement results with conventional methods is provided, which validates the advantages and performance of the control scheme. Originality. To solve the given problem, the information vector on the current state of the coordinates of the electromechanical system is used to form a controlling influence in the dynamic mode of operation. For the first time, the formation process of controls has considered the current state and the desired future state of the system in the real-time domain. Practical value. Apredictive iterative approach for optimal flux level of an induction machine is important to generate the required electromagnetic torque and to reduce power losses simultaneously.

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Author of HS ReutlingenSchullerus, Gernot; Dominic, Antony
Publisher:Dnipro University of Technology
Place of publication:Dnipro, Ukraine
Document Type:Journal article
Publication year:2020
Tag:dynamic operation; energy efficiency; predictive control; real-time implementation
Page Number:7
First Page:61
Last Page:67
DDC classes:600 Technik, Technologie
Open access?:Ja
Licence (German):License Logo  Open Access