In this paper, the behavior of a doubly fed induction generator (DFIG) is studied under unbalanced grid voltage conditions. It is shown that if no special control efforts are employed, the behavior of the generator is deteriorated, basically due to two reasons: electromagnetic torque oscillations and nonsinusoidal current exchange with the grid. These phenomena are first analyzed theoretically as a function of the stator active and reactive instantaneous power exchange by the stator of the DFIG and the grid-side converter (GSC). This analysis provides the main ideas for generation of the active and reactive power references for the rotor-side converter (RSC) and the GSC, controlled by means of direct power control techniques. Therefore, this paper proposes a new algorithm that generates the RSC power references, without the necessity of a sequence component extraction, in order to eliminate torque oscillations and achieve sinusoidal stator currents exchange. On the contrary, the GSC power references are provided by means of voltage and current sequence extraction. Finally, simulation and experimental results successfully validate the proposed power reference generation methods.

In this paper, a new predictive direct torque control (DTC) strategy of the doubly fed induction machine (DFIM) is presented. It is especially designed to operate at a considerably low constant switching frequency, reducing the electromagnetic torque and rotor flux ripples, in order to provide good steady-state and fast dynamic performances. This control is convenient for high power drive and generator applications, with restricted switching frequency. The DFIM is connected to the grid by the stator and the rotor is fed by a two level voltage source converter. In addition, this control method allows to implement a technique that reduces the switching power losses of the converter. Finally, experimental results show that the proposed DTC method effectively reduces the torque and flux ripples at low switching frequency, even under variable speed operation conditions.

The need to manufacture more competitive equipment, together with the emergence of the digital technologies from the so-called Industry 4.0, have changed many paradigms of the industrial sector. Presently, the trend has shifted to massively acquire operational data, which can be processed to extract really valuable information with the help of Machine Learning or Deep Learning techniques. As a result, classical Condition Monitoring methodologies, such as model- and signal-based ones are being overcome by data-driven approaches. Therefore, the current paper provides a review of these data-driven active supervision strategies implemented in electric drives for fault detection and diagnosis (FDD). Hence, first, an overview of the main FDD methods is presented. Then, some basic guidelines to implement the Machine Learning workflow on which most data-driven strategies are based, are explained. In addition, finally, the review of scientific articles related to the topic is provided, together with a discussion which tries to identify the main research gaps and opportunities.

A new vector control algorithm for the brushless doubly fed machine (BDFM) has been developed. The goal of BDFM control is to achieve a similar dynamic performance to the doubly fed induction machine (DFIM), exploiting the well-known induction motor vector control philosophy. For this purpose, a recently developed unified reference-frame model has been used to develop the vector control strategy. The theoretical considerations for the vector control design, control loops tuning and limits are shown. In addition, practical considerations for the experimental implementation of vector control for the BDFM are shown. Experimental results in a machine prototype confirm the good dynamic performances of this type of control.

In this paper, a new predictive direct power control (DPC) technique is presented for the doubly fed induction machine (DFIM). Based on this predictive control, the strategy is able to operate at considerably low constant switching frequencies and allows it to perform a power ripple minimization technique, in order to improve the steady-state and transient response behaviors of the machine. In addition to the control technique definition, this paper includes a conceptual analysis of DPC. On the other hand, to validate the control strategy, it will be experimentally compared to the well-known voltage frequency control, the vector control, and the nonpredictive DPC strategy. The comparison will be carried out in terms of the steady-state behavior and transient response capacity, and it will be shown that the proposed predictive DPC technique allows to obtain the combination of the quick dynamic response of direct control techniques, and the benefits of constant switching-frequency-based control techniques.