The issues of monitoring and fault diagnosis of drives with permanent magnet synchronous motors (PMSMs) are currently very relevant because of the increasing use of these drives in safety-critical devices. Every year, more and more articles are published on this subject. Therefore, the objective of this article is to update the overview of diagnostic methods and techniques for PMSM drives. Each of the main chapters of the article focuses on a specific element of the drive system (motor, power converter, measuring sensors), with particular emphasis on the components of the motor (stator windings, magnets, bearings, and rotor). The main sections on PMSM fault diagnosis are divided according to the type of methods used to obtain the symptoms of the damage. In addition, a review of methods that use the analysis of signals of the control structure for the diagnosis of damage to a vector-controlled motor is presented, as well as the latest achievements of researchers in the field of shallow and deep neural networks for the detection and classification of failures of PMSM drives. Based on the analyses presented in the literature, some development trends and challenges related to the development of diagnostics and fault-tolerant control of PMSM drives are discussed in the conclusion part.

This paper deals with monitoring of interturn short circuits of induction-motor (IM) stator windings operating under the direct field-oriented control (DFOC). Time transients are presented to illustrate the performance of the field-oriented speed control under the stator-winding damage. Novel detection algorithm is introduced, based on an analysis of the internal signals from the control structure: controller outputs and control path decoupling variables. The spectral analysis of these signals is used to detect the stator-winding incipient damages. Significant changes of the constant component f _dc and the double-fundamental harmonic component 2f _s observed in these signals' spectra under the stator-winding failure become the basis for the failure diagnostics in various operating conditions of the DFOC IM drive. The superiority of the proposed detection algorithm over the classical motor current signature analysis (MCSA) method is described. The online monitoring process is shown. Simulation and experimental results are presented to validate the proposed detection algorithm.

This paper deals with the stability problem of selected induction motor speed estimators in the case of the regenerating mode operation. Two effective solutions are taken into consideration: adaptive full-order observer and model reference adaptive system-type estimator based on the current flux model and stator current estimation. The two estimation algorithms are compared in detail, namely their mathematical models, theoretical stability analysis, unstable operation areas, and stability improvement methods. The speed adaptation mechanism is extended with an additional shift angle in both cases. The theoretical analysis and simulation test results are validated by wide experimental tests.

In this paper the stability problem of the stator current error based Model Reference Adaptive System (MRAS) speed estimator for induction motor (IM) drive is discussed. The MRASCC that is analyzed in this paper is created with a rotor flux simulator based on the stator current (first superscript C) and the stator current estimator (second superscript C), both adapted with the estimated rotor speed. As the original estimator is unstable in the regenerating mode, a simple stability extension solution is proposed based on the introduction of an auxiliary variable in the mathematical model of this estimator. The new adaptation rule is derived using the Lyapunov theory and stability range of a modified speed estimator is determined. This modification is compared with the existing solutions and analyzed in simulation and experimental tests under motoring and regenerating modes of the drive system, in open and closed-loop operation. It has been shown that the modified speed estimator with an additional variable adapted on-line is stable in the whole regenerating mode, contrary to the classical solution and does not require any modifications during the change from the regenerating to motoring mode and vice versa, as it is required in the existing solutions.

The paper presents a new speed estimator designed for sensorless induction motor drives. The proposed sliding-mode estimation algorithm is a model reference adaptive system-type estimator. Its reference model is the induction motor, while both the stator current and rotor flux estimators create the adaptive system. The estimator uses a sliding mode technique in order to ensure robustness and simple implementation. The algorithm is based on the equivalent signal technique which allows us to significantly decrease chattering, while simultaneously retaining the properties of the sliding mode estimator. Additionally, the estimator is extended with an auxiliary variable which allows us to improve the stability of the estimation in regenerating mode operation. The proposed estimator is verified using extended simulation and experimental tests.