Finite control set-model predictive torque control (FCS-MPTC) has fast dynamic response because this algorithm directly selects the optimal voltage vector by its cost function for induction machine drives fed by voltage source inverter (VSI). However, belonging to open-loop control paradigm, FCS-MPTC has torque tracking error due to inevitable load disturbance and mismatched model parameters in reality. In traditional FCS-MPTC, the outer loop, i.e. speed loop, adopts classic proportional integral (PI) controller, abbreviated as PI-MPTC. The lumped disturbance is only suppressed by PI controller. However, pole placement of PI controller is usually designed by cut-and-trial, which is difficult to simultaneously achieve optimal dynamic performance and optimal suppression of lumped disturbance. In this paper, FCS-MPTC with mismatched parameters is firstly analyzed. Secondly, the deficiencies of traditional PI controller are introduced. Thirdly, disturbance feedforward compensation based-model predictive torque control (DFCB-MPTC) of induction machine is proposed to compensate lumped disturbance and improve the performance of system. Furthermore, an simplified stator flux observer is proposed, which gain matrix is independent of rotor speed. Experimental results verify the feasibility of the proposed DFCB-MPTC. Compared with traditional PI-MPTC, The proposed DFCB-MPTC has better dynamic performance, steady performance and stronger robustness.

Traditional loss-minimization strategies of model-based control, copper loss minimization (CLM) and finite-element-based control suffer from respective problems of iron loss mismatch with a physical view, pseudo minimization and amounts of efforts when they are applied to permanent magnet synchronous motor with non-sinusoidal back EMF (NS-PMSM). This paper combines theories of multiple synchronous reference frames and iron loss resistance to develop a new model of NS-PMSM, based on which the stator iron loss is evaluated to match well with the physical view. Then a current strategy is proposed to minimize the total stator loss under constraints of ripple-free torque and finite DC supply. The optimal current solution is solved in closed form and implemented effortlessly. A good robustness to phase resistance variation is also achieved. Compared to CLM, the proposed strategy realizes a true minimization with the stator loss reduced by 9% and the motor efficiency enhanced by 0.7% at rated operation of a 3.8 kW NS-PMSM. Precision of the iron loss evaluation and performances of the strategy are validated experimentally on the 3.8 kW motor setup.

Traditional stator iron loss models lack of precision when they are used for loss optimization of permanent-magnet synchronous motor (PMSM), because non-uniform distribution and non-sinusoidal waveform of the flux density in stator core is not fully considered. In this paper, a new model is developed with a higher precision, in which the non-uniform flux density in stator core is observed through two virtual coils wounded on the yoke and tooth of a finite-element model. Then the stator iron loss is calculated depending on induced voltages of the coils. Moreover, non-sinusoidal waveform of the flux density is considered in the development. Based on this model, a loss-optimization method is proposed, in which the optimal current reference is determined by minimizing the stator loss under a constraint of ripple-free torque. Limitations of DC voltage supply and current amplitude are also considered to improve robustness of the method. Finally, precision of the iron loss model and performance of the loss-optimization method are validated experimentally on a 3.8 kW PMSM setup.

In Finite control set-predictive torque control (FCSPTC), mismatched parameters will lead to the electromagnetic torque prediction error. To solve the aforementioned problem, this paper proposes feedback correction-based dual reference frame predictive torque control for induction machines, which is abbreviated as DRF-PTC. Firstly, a dual reference frame flux observer is proposed, which abandons traditional model reference adaptive observer with rotor speed as adaptive variable. The proposed flux observer decouples the flux observation and the speed estimation, and improves the estimation accuracy of flux linkage and rotor speed. Secondly, a dual reference frame predictive torque control is proposed to eliminate the effect of speed estimation error on torque prediction. For the influence of mismatched parameters, a correction term is incorporated in double reference frame torque prediction equations, which correction term is derived from the correction term of the proposed flux observer. Finally, the proposed DRF-PTC in this paper is verified on the experimental platform of induction machine. Experimental results show that the proposed DRF-PTC has excellent performance in speed estimation and electromagnetic torque prediction, compared with traditional FCS-PTC.

Copper-loss-minimizing torque control (CLMTC) method has been widely studied to reduce electromagnetic torque ripple and minimize copper loss of brushless dc motor (BLDCM), but still suffers challenges to improve its performance. This paper presents a quantitative analysis of stator iron loss and current-loop delay effects on CLMTC. In the analysis the iron-loss-included torque equation that only suits for sinusoidal back-EMF is modified to cover the case of non-sinusoidal back-EMF. It is concluded that the iron loss effect brings about significant torque generation error and the delay effect leads to torque ripple that increases linearly with delay angle. Two im-provements are proposed, one of which redefines the condition of optimal motor current vector to compensate for the iron loss effect. The other one aims to suppress the delay effect by preshaping current reference based on delay characteristic of the loop. The improvements can be performed effectively on microprocessor to realize a better CLMTC method with reduced torque generation error and torque ripple. Both the analysis and improvements are experimentally validated on a 0.95 kW BLDCM setup

In this paper, a novel current solution is proposed to suppress the electromagnetic torque ripple of brushless dc motor (BLDCM), and simultaneously minimize the rotor eddy-current loss to prevent thermal demagnetization of the permanent magnets. To determine the current solution, an optimizing problem of the rotor loss is developed, subjecting to the constraints of average torque and the 6th harmonic torque. Finite DC supply is also considered. In addition, an improved model of the rotor loss is proposed with a simpler expression of quadratic form, so that the problem can be solved analytically. A comparison with the square-wave and minimal-copper-loss current solutions is studied based on a 3.77 kW, 12000 rpm BLDCM, which indicates that the proposed solution performs as well as the two solutions in suppressing the torque ripple and producing stator losses, but the rotor loss can be significantly reduced by at least 86% and 35% respectively. Precision of the rotor loss model and performance of the proposed solution are validated experimentally on the 3.77 kW BLDCM setup.