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Recently, model-based predictive current control (MB-PCC) has been presented as a good alternative to classical control algorithms in terms of simplicity and performance reliability. However, MB-PCC suffers from the high dependence on system parameters, which may deteriorate its performance under parameters variations. On the other hand, synchronous reluctance motors (SynRMs) are susceptible to suffer from inductances variations due to the magnetic saturation. Accordingly, in this article a new model-free predictive current control of SynRMs based on a recurrent neural network (RNN-PCC) is developed and proposed. The proposed RNN-PCC relies on the identification of the SynRM currents without considering any parameters. Simulation and experimental results show that both RNN-PCC and MB-PCC have similarly excellent dynamics, while better control performance and tracking errors can be achieved thanks to the proposed RNN-PCC. [ABSTRACT FROM AUTHOR]

Interturn short-circuit faults are one of the most (if not the most) harmful electrical machine failures, that if not detected and mitigated at a very incipient stage of development may involve serious consequences, both in terms of repair costs and safety. This article proposes a novel interturn fault diagnostic technique for synchronous reluctance machines based on the Luenberger state observer and current's second-order harmonic. The superiority of the proposed approach over the conventional model-based techniques is the ability to evaluate the severity of the fault as well as the efficiency in detecting faults in early stages and under various operating conditions. The effectiveness of the proposed method is demonstrated and validated through several experimental tests. [ABSTRACT FROM AUTHOR]

In recent years, multiphase machines have been presented as a good alternative to the classical three-phase machines due to their ability to operate under fault-tolerant conditions. However, the transition from pre- to post-fault control needs a reliable fault diagnostics algorithm. Accordingly, this article presents a reliable diagnostics approach that allows the detection and identification of multiple open-switches and open-phase faults in power converters fed six-phase induction motors, including adjacent and nonadjacent phases. The proposed method provides normalized numerical signatures from the measured output currents without requiring either tuning effort or detection thresholds. The reliability and robustness of the proposed algorithm are proven through experimental tests. [ABSTRACT FROM AUTHOR]

Direct model predictive control (DMPC) of permanent magnet synchronous generators with full-scale back-to-back (BTB) converters plays an important role in improving the power quality injected to the grid and to comply with grid codes. However, DMPC suffers from the excessive computational burden since all the feasible voltage vectors (VVs) of the BTB converter are used for the prediction and evaluation. Moreover, the weighting factor in the cost function may affect the control performance and tuning it is a complex process. Accordingly, benefiting from the simplicity of the direct control techniques, new direct model predictive flux and power control are proposed in this article, in combination with the direct torque and power control (DTC and DPC), respectively. By defining new DTC and DPC switching tables, only three out of the eight predictions are required to select the best VV for each converter of the BTB topology, which significantly reduces the algorithm computations. To avoid the weighting factor, the electromagnetic torque is simply converted into an equivalent stator flux and only the latter one is considered in the cost function. Experimental results prove that the execution time can be reduced by 26.9%, while the best control performance can be achieved. [ABSTRACT FROM AUTHOR]

Fault detection and fault accommodation, as well as fault tolerance, are important issues in closed-loop controlled three-phase converters. For such systems, power semiconductors and sensors are the most affected components by the occurrence of failures. Therefore, fault diagnosis and remedial operating strategies involving such components are highly required. In this paper, a new reliable approach is proposed, which aims to diagnose current sensor faults and power semiconductor open-circuit faults in permanent magnet synchronous motor drives. The proposed fault diagnosis scheme uses only the measured currents, which makes it suitable for real-time implementation. The performance of the proposed technique is analyzed through experiments. [ABSTRACT FROM AUTHOR]

Fault tolerance in wind turbines is considered crucial to increase their reliability and availability levels. This paper presents a fault-tolerant direct-drive permanent magnet synchronous generator (PMSG) using new direct control techniques, with the ability to handle power semiconductor open-circuit faults in the full-scale back-to-back converter. The fault-tolerant topology consists of a five-leg converter, with a shared leg connected to a generator phase and to its corresponding grid phase, through a triode for alternating current (TRIAC). The main contribution of this paper consists of the development of an alternative direct torque control and direct power control schemes for both machine-side converter and grid-side converter, respectively. Moreover, a reliable fault diagnostics algorithm without requiring additional sensors is also integrated, providing the information required to instantaneously trigger fault-tolerant remedial strategies. Simulation and experimental results are presented to validate the effectiveness of the proposed fault-tolerant PMSG drive. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motors (PMSMs) drives using three-phase voltage-source inverters (VSIs) are currently used in many industrial applications. The reliability of VSIs is one of the most important factors to improve the reliability and availability levels of the drive. Accordingly, this paper presents a robust fault diagnostic method for multiple insulated gate bipolar transistors (IGBTs) open-circuit faults and current sensor faults in three-phase PMSM drives. The proposed observer-based algorithm relies on an adaptive threshold for fault diagnosis. Current sensor and open-circuit faults can be distinguished and the faulty sensors and/or power semiconductors are effectively isolated. The proposed technique is robust to machine parameters and load variations. Several simulation and experimental results using a vector-controlled PMSM drive are presented, showing the diagnostic algorithm robustness against false alarms and its effectiveness in both IGBTs and current sensors fault diagnosis. [ABSTRACT FROM PUBLISHER]

In order to increase the reliability and availability of wind turbines, condition monitoring and fault diagnosis are considered crucial means to achieve these goals. In this context, direct drives wind turbines based on permanent-magnet synchronous generators (PMSGs) with full-scale power converters are an emerging and promising technology. However, several statistical studies point out that power converters are a significant contributor to the overall failure rate of modern wind turbines. Accordingly, this paper presents a new algorithm for multiple open-circuit faults diagnosis in full-scale back-to-back converters, applied in PMSG drives used for wind turbine systems. The proposed method is based on a Luenberger observer and on an adaptive threshold, which can guarantee a reliable diagnosis independently of the drive operating conditions. Several simulation and experimental results using a PMSG drive with a full-scale converter are presented, showing the diagnostic algorithm effectiveness and robustness against false alarms for both generator- and grid-side converters. [ABSTRACT FROM AUTHOR]