This paper is focused on the on-load back-electromotive force (EMF) assessment in a permanent magnet synchronous machine (PMSM) using Maxwell stress tensor along with the frozen permeability method (FPM). Although the back EMF is only measured at open-circuit condition, it is known that the on-load back EMF is heavily affected by electric loading and magnetic saturation. Since the main torque component of the PMSM is the mutual torque and it is based on the interaction between the back EMF and stator current, any distortion in the on-load back EMF will affect the electromagnetic torque and increase the torque ripple. A misleading on-load back-EMF waveform with some spikes around the commutation points is found if the on-load back EMF is assessed by means of differentiating the on-load PM flux linkage. This way, this paper proposes a new numerical method to assess the on-load back EMF in order to avoid all the shortcomings of the existing method. First of all, a quick review on the results achieved by other researchers is shown. Next, a review on the FPM is done in order to clarify the points where this method will be changed to overcome the drawbacks highlighted previously. Furthermore, a new method is introduced and explained in small details. Finally, the results for different rotor configurations and different electrical loads are presented in order to validate the proposed method's accuracy against experiments and other numerical techniques.

Interior permanent magnet synchronous motors (IPMSMs) with nonsinusoidal flux develop undesirable torque ripple under conventional control strategies, leading to vibration and increase of mechanical stress. To overcome this problem, active torque ripple compensation based on harmonic stator current injection is widely investigated in the literature. However, the combination of the torque ripple minimization strategy with the maximum torque per Ampère (MTPA) operation is a challenge to the field. In this paper, a control strategy based on genetic algorithm (GA) and artificial neural network (ANN) is proposed to achieve low torque ripple with MTPA operation of a three-phase IPMSM with significant magnitude of zero sequence back-electromotive force (back-EMF) component. Investigations have found that the consideration of back-EMF zero sequence in torque prodution can increase the torque per Ampère ratio. Further, the results shows that the proposed strategy effectively reduces the torque ripple in real time operation, including steady state and transient torque performances.

This paper proposes a novel Vector Control topology for stator current harmonic mitigation, due to the grid voltage harmonic content, focusing on mitigating the torque undulations in the Doubly Fed Induction Generator. The Proposed Controller referred here as to HVC - Harmonic Vector Control, is capable of mitigating any desired current harmonic. Voltage grid fifth, seventh, eleventh and thirteenth harmonic components causes current harmonic components of the same order (5th, 7th, 11th and 13th) in the generator but of higher relative amplitudes, due to the low stator series impedance. Therefore, the HVC has been tested for the control of such current harmonic components. As an advantage, the proposed control does not require a harmonic filter to estimate the harmonic content present in the stator current due to the power grid, which are the main disadvantages found in literature for the existing controllers. Firstly, the control topology is described and explained in detail. Next, simulation and experimental data are shown and compared to prove the suitability and efficacy of the proposed control. In the cases studied, the steady state error of the proposed controller is close to zero. Furthermore, the HVC can be used as a harmonic filter in DFIG and the harmonics can be chosen according to the application requirements.

The present work aims to optimize the magnetomotive force and the end-winding leakage inductance from a discrete distribution of conductors in electrical machines through multi-objective particle swarm heuristics. From the development of an application capable of generating the conductor distribution for different machine configurations (single or poly-phase, single or double layer, integral or fractional slots, full or shortened pitch, with the presence of empty slots, etc.) the curves of magnetomotive force and the end-winding leakage inductance associated with the winding are computed. Taking as an optimal winding the one that presents, simultaneously, less harmonic distortion of the magnetomotive force and less leakage inductance, optimization by multi-objective particle swarm was used to obtain the optimal electrical machine configuration and the results are presented.

The present work aims to promote a comparative analysis between the most cited and recent methods in the scientific world associated to the Frozen Permeability Method combined with the Finite Element Method for on-load cogging torque evaluation in permanent magnet synchronous machines (PMSM) and determine which is the most appropriate. Numerous researches have been carried throughout the years in order to accomplish the task of segregating the torque components and figure out the origins of torque oscillations. However, most of them have failed as they usually attribute the torque ripple only to the cogging torque and taking general conclusions based only in one type of PMSM. Here, in the present text, the investigation is carried out basing on different PMSM topologies and different current waveforms for motor drive. The results show that the most suitable methodology is not based on electromagnetic energy neither based on the electromagnetic coenergy but based on flux distribution. All simulations are performed with FEMM (Finite Element Method Magnetics) software.