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EN
Today, a clear trend in electrification process has emerged in all areas to cope with carbon emissions. For this purpose, the widespread use of electric cars and wind energy conversion systems has increased the attention and importance of electric machines. To overcome limitations in mature control techniques, model predictive control (MPC) strategies have been proposed. Of these strategies, predictive torque control (PTC) has been well accepted in the control of electric machines. However, it suffers from the selection of weighting factors in the cost function. In this paper, the weighting factor associated with the flux error term is optimised by the non-dominated sorting genetic algorithm (NSGA-II) algorithm through torque and flux errors. The NSGA-II algorithm generates a set of optimal solutions called Pareto front solutions, and a possible solution must be selected from among the Pareto front solutions for use in the PTC strategy. Unlike the current literature, three decision-making methods are applied to the Pareto front solutions and the weighting factors selected by each method are tested under different operating conditions in terms of torque ripples, flux ripples, cur-rent harmonics and average switching frequencies. Finally, a decision-making method is recommended.
PL
W artykule przedstawiono sterowanie predykcyjne silnikiem synchronicznym z magnesami trwałymi, nazwane DTC-3V. Nowy regulator predykcyjny bazuje na kryterium minimalizacji uchybu regulacji momentu i strumienia. Sterowanie zostało zoptymalizowane zarówno w stanach statycznych, zapewniając wysoką dokładność regulacji, małe tętnienia momentu oraz stałą częstotliwość przełączeń, jak i dynamicznych, zapewniając dynamikę kształtowania momentu porównywalną z najszybszymi metodami nieliniowymi. Zaprezentowano założenia nowej metody oraz wyniki badań symulacyjnych i laboratoryjnych, potwierdzające poprawność przeprowadzonej analizy.
EN
In this article a new DTC-3V control method of PMSM with new predictive controller is presented. The method is based on torque and flux error vector minimization criteria. The proposed method was optimized for both static and dynamic states. In static states it ensures high performance, reduction of the torque ripples and constant switching frequency. In dynamic states DTC-3V method provides the fastest torque response, similar to non linear methods. The correctness of the analysis and main assumptions as well as the expected final results have been verified in simulation and laboratory investigation.
3
Content available remote Predictive torque and flux control for the synchronous reluctance machine
EN
This paper presents a predictive torque and flux control algorithm for the synchronous reluctance machine. The algorithm performs a voltage space phasor preselection, followed by the computation of the switching instants for the optimum switching space pha-sors, with the advantages of inherently constant switching frequency and time equidistant implementation on a DSP based system. The criteria used to choose the appropriate voltage space phasor depend on the state of the machine and the deviations of torque and flux at the end of the cycle. The model of the machine has been developed on a d-q frame of coordinates attached to the rotor and takes into account the magnetic saturation in both d-q axes and the cross saturation phenomenon between both axes. Therefore, a very good approximation of this effect is achieved and the performance of the machine is improved. Several simulations and experimental results using a DSP and a commercially available machine show the validity of the proposed control scheme.
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