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Control of the speed as well as shaping the speed transient response of a surface-mounted permanent magnet synchronous motor (PMSM) is achieved using the method of feedback linearization and extended high-gain observer. To recover the performance of feedback linearization, an extended high-gain observer is utilized to estimate both the speed of the motor and the disturbance present in the system. The observer is designed based on a reduced model of the PMSM, which is realized through the application of singular perturbation theory. The motor parameters are assumed uncertain and we only assume knowledge of their nominal values. The external load torque is also assumed to be unknown and time-varying, but bounded. Stability analysis of the output feedback system is given. Experimental results confirm the performance and robustness of the proposed controller and compare it to the cascaded proportional integral (PI) speed controller.

Permanent magnet synchronous machines work with controllers and controller parameters affect the machine's voltages and currents and, thus, the diagnosis of stator winding fault. One such parameter is the current controller bandwidth that affects the harmonic content in these signals. In the literature, the second harmonics in both $dq$ -axis currents and voltages have been used for fault detection, and the main advantage is that interturn short-circuit (ITSC) winding fault with a few shorted turns, specially one turn, can be detected. One indicator that combines the fault information in voltages and currents is the instantaneous reactive power (IRP). However, it has been shown that IRP does not perform robustly with respect to current controller bandwidth. The main contribution of this article is that it proposes and validates a new mathematical function for ITSCs detection, Rayleigh quotient, which combines the fault information present in voltages and currents to make ITSCs detection robust to current controller bandwidth. The validations from both cosimulation and experiment show that the proposed method is robust to the bandwidth and can detect ITSC faults faster than IRP.

In this article, an incremental inductance approach is used for static eccentricity detection under off-line condition. This method uses the DC values of the $q$ -axis voltage, which makes it independent of the bandwidth of the controller. In this work, a new feature, the height of hump of the incremental inductance curve, along with the known feature, saturation current in the $d$ -axis, was used for fault detection. It is shown that this new feature is independent of the machine operating temperature, which makes the method robust with respect to machine operating temperature. It is also shown that the proposed method is robust to the rotor position misalignment. A new controller for off-line testing was designed, which controls both the speed and saturation of the machine. Using this controller, the hardware requirements for constant rotation of the machine are reduced while keeping the method independent of the bandwidth of the controller. Finally, a MATLAB-based computer program was developed to calculate the features: saturation current in the $d$ -axis and height of hump of the incremental inductance curve. Six different machines, combinations of two stators and three rotors, were used to validate the proposed method through experiments.

The limitations of the thermal, vibration, or electrical monitoring of electric machines such as false indications, low sensitivity, and difficulty of fault interpretation have recently been exposed. This has led to a shift in the direction in research toward applying new techniques for improving the reliability of condition monitoring. With the changing environment, the purpose of this article is to provide an overview of the recent trends in the industrial demand and research activity in condition monitoring technology. The new developments in insulation testing, electrical testing, flux analysis, transient analysis, and fault prognostics are summarized. The challenges and recommendations for future work for the new technologies are also explored to help support target research and development efforts according to industrial needs.

Electrification of transportation systems continues to increase both to reduce the negative effect of petroleum-based transportation on the climate and the quality of life and to allow for enhanced safety and comfort of transportation at large. These developments are often subject to tight constraints on cost, mass, and volume. At the same time, the requirements on the reliability of the systems in these applications are becoming more demanding. Significant literature is available on power electronic systems. Yet, the specifics of the analysis and prevention of failures of different components, subsystems, and systems as they apply in automotive, aerospace, and other transportation systems have, at large still, not yet been fully addressed, and will remain open as the demands of overall cost and performance continuously increase.

Oriented steel has higher permeability and lower losses in the direction of orientation (the rolling direction) than non-oriented steel. However, in the transverse direction, oriented steel typically has lower permeability and higher losses. The strategic use of oriented steel in a modular Permanent Magnet Synchronous Machine (PMSM) stator can improve machine performance, particularly when compared to a machine designed with non-oriented steel, by increasing both torque and efficiency. Typically, steel manufacturers provide magnetic properties only in the rolling and transverse directions. Furthermore, in modern Finite Element Analysis (FEA) software, the magnetic properties between the rolling and transverse directions are interpolated using an intrinsic mathematical model. However, this interpolation method has proven to be inaccurate; to resolve this issue, an improved model was proposed in the literature. This model requires the magnetic properties of the oriented steel in between the rolling and transverse directions. Therefore, a procedure for extracting the magnetic properties of oriented steel is required. The objective of this work is to propose a method of determining the magnetic properties of oriented steel beyond just the oriented and transverse directions. In this method, flux-injecting probes, also known as sensors, are used to inject and control the flux density in an oriented steel segmented stator in order to extract the properties of the oriented steel. These extracted properties are then used to model an oriented steel modular stator PMSM. The machine’s average torque and core losses are compared with conventional, non-modular, non-oriented steel stator PMSM, and modular, non-oriented steel stator PMSM. It is shown that both the average torque and the core loss of the oriented steel modular stator PMSM have better performance at the selected number of segments than either of the two non-oriented steel stators.

A computationally efficient design of interior permanent magnet (IPM) motor rotor features is investigated utilizing analytical methods. Over the broad operating range of IPM machines, interactions of MMF sources, permeances, and currents result in torque harmonics. The placement of traditional rotor features along with sculpt features are utilized to minimize torque ripple and maximize average torque. We extend the winding function theory to include the IPM rotor’s primary and secondary reluctance paths and the non-homogeneous airgap of the rotor sculpt features. A new analytical winding function model of the single-V IPM machine is introduced, which considers the sculpted rotor and how this model can be used in the design approach of machines. Results are validated with finite elements. Rotor feature trends are established and utilized to increase design intuition and reduce dependency upon the lengthy design of experiment optimization processes.

The interest in reliable operation of electrical drives has increased in recent years. recently an AC electrical machine was typically a synchronous generator or a three-phase uncontrolled motor that would operate connected directly to the power grid, or if a DC machine, its speed would be controlled through a rectifier. Although these applications have been augmented by many others. Many developments have led to this explosion of applications. The ubiquitous use of power electronics and microcontrollers, DSPs, etc., have allowed control of speed, torque etc., and the introduction of new motor types: permanent magnet AC, switched and synchronous reluctance etc. with increased versatility, higher torque and power density. These new power electronics-controlled machines have been finding uses in applications in manufacturing, robotics, vehicle traction and operation, airplane propulsion, wind and wave generators, but also in medical, commercial and consumer electronics that are becoming vital in health and other necessary devices. Fault diagnosis in electrical drives covers the faults in the power electronics, the DC link capacitor, batteries if present, and electrical machines. In power electronics in particular, the faults can be open or short circuit of switches, and they can be identified from current and voltage measurements. In electrical machines the faults can be in the windings, with either incipient in precipitous degradation, and can be identified and their severity determined using either model- or signal-based techniques. Mechanical faults in bearings are usually detected through the measurement of vibrations, while eccentricity can be detected through the change of flux and inductances. Most of these faults can be identified accurately, and their development predicted. They can lead then to the estimation of the remaining useful life, and together with partial or full redundancies, can result in increased reliability on the drive.

Using segmented-cores for the production of electric machines provides several advantages like simplified winding process, ease of transportation, assembling the machine, ability to use different materials for stator and rotor, including oriented steel, while reducing the scrap or increase in reluctance torque. In literature different types of segmented stator designs were used for different operations, for example some operations may require better cooling of the machine, some require lighter weight machine and in some cases higher slot fill factors are desired. There are also some possible disadvantages of using segmented stators, like increase in cogging torque, increase in acoustic noise, decrease of average torque, higher saturation in the machine or increase in cut edges as compared to conventional whole stator. Punching leads to changes in the magnetic and loss characteristics of the region close to the cut edge of the steel. Accurate modelling of segmented stators, using FEA is challenging as segmentation leads to more cut edges as compared to whole motor. This paper reviews the information presented in literature for different types of segmentation in the permanent magnet synchronous machine (PMSM) or switched reluctance machine (SRM), effects of segmentation on the torque ripple and core losses, design modifications in segmented machines for improving the performance of the machine and modeling of segmented machine using FEA. This provides a stepping stone information to the machine designer for the design of segmented stators.

Single switch open-circuit faults in three-phase ac drives lead to undesired effects and potentially to a total failure of the drive. This paper proposes a postfault operation strategy for such faults with a focus on the limitation of losses after the reconfiguration and thereby an extension of the possible range of operation. Furthermore, a method for the reduction of alternating torque components during the postfault operation of a squirrel cage induction machine drive is proposed. The performance of the postfault operation strategy and the alternating torque reduction method are shown both via simulations and experiments.

Different faults in permanent magnet synchronous machines (PMSMs) cause various and independent changes to the machine magnetic flux distribution, which affect the machine parameters and performance. These changes are reflected in the machine flux linkages and can be estimated from the machine voltages. In this paper, we continue the work of Haddad et al. , where a method was proposed to detect and separate three types of faults in PMSMs: 1) static eccentricity; 2) demagnetization; and 3) turn-to-turn short circuit. The method proposed here is based on using the change in the commanded $d$ - and $q$ -axis voltages, while the machine is operating at steady state, for fault detection and separation. Simulation tests using finite element analysis (FEA) software (MAGSOFT-Flux2D) were performed under healthy and the tested fault conditions on a three-phase ten-pole fractional-slot concentrated-winding PMSM. An analytical method is proposed to estimate the commanded voltages at any operating condition, and a classification algorithm is implemented for fault detection and classification. Experimental tests were carried out and compared with FEA. The effects of the variation in the operating speed and temperature were simulated and tested to validate the detection method under different operating conditions.

Open-switch faults in inverter-driven electric drives have recently gained increasing attention in the scientific community. Since these faults may lead to undesired effects, their fast and unambiguous detection is desirable. This paper proposes a detection algorithm for open-switch faults, which is based on the observation of the current control deviation and a subsequent test procedure. This algorithm detects the fault immediately after its occurrence within a few switching periods, even during transient operation. The proposed method is tested via simulations and experiments at different operating points of a surface permanent magnet drive.

Electric discharge machining current causes a significant amount of damage to bearings, producing pits in the rotating elements of the bearing, and ultimately leading to bearing failure. Although this relationship is well known and studied, little work has been done to relate bearing current discharge events to bearing vibrations for bearing failure prognosis. This paper proposes both experimental and computational approaches for remaining useful life (RUL) estimation of bearings by taking advantage of the relationship between current discharge events and the vibration signal. A test bed, which induces accelerated aging via applied electrical stress, is introduced to better understand the relationship between bearing currents, vibrations, and failure. Over the course of the experiments, multiple sensor data are collected from start to failure in order to correlate current data as well as vibration data to bearing failure. Finally, a computational framework that determines critical events from the current discharge events and uses the timing of these events to estimate RUL from vibration data is proposed.

This paper presents the analysis of Unbalanced Magnetic Pull (UMP) on the rotor due to static eccentricity. It has been shown in previous research that under eccentric conditions the rotor experiences UMP that constitutes of two components: constant pull and oscillating forces. This paper is divided into two parts. The first part discusses the procedure to estimate static eccentricity in Interior Permanent Magnet Synchronous Machine by analyzing the vibrations that rise due to oscillating forces. The impact of increased load and saturation on constant pull, at a fixed eccentricity, is shown. The second part discusses the aspects of machine design that can make machine more robust, in the case of static eccentricity, to vibrations.

Fast and reliable inter-turn short-circuit detection is essential for machine drive system. PMAC machines always work together with controllers and the controller parameters will affect the machine performance and the fault diagnosis in turn. The effects from the current controller bandwidth are special interested. In a closed-loop control PMSM drive system, the behaviours of the second harmonics in currents and voltages, induced by inter-turn short-circuit, along with the bandwidth are investigated theoretically. To combine the fault information both in currents and voltages, an indicator based on Rayleigh quotient, is proposed and compared with one published indicators, the second harmonics in instantaneous reactive power. Validated by Co-simulation, the presented indicator is more robust with respect to the controller bandwidth.

In this paper, we regulate the speed of a surface mount Permanent Magnet Synchronous Motor (PMSM) with only using current sensors. We use a back-Electromotive Force (back-EMF) based sensorless speed control technique. We reduce the α-β model of the PMSM using singular perturbation theory, which reveals two algebraic expressions for the estimation of the back-EMF signals. We use these expressions to drive a Quadrature Phase Locked Loop (Q-PLL) that estimates rotor position and speed and also estimates the disturbance. The rotor position estimate is used for Park transformation while the speed and disturbance estimates are used in a feedback linearization law to regulate the speed. Our development of the controller only assumes knowledge of the nominal parameters of the PMSM. In addition, we assume the external load to be time-varying and bounded but otherwise unknown. Finally, results from simulation and experiment are shown to confirm robustness, and high performance of the output feedback system.

This work proposes an offline detection method for the presence of static eccentricity in Permanent Magnet Synchronous Machines, which is noninvasive and robust to small perturbations of parameters and the conditions. This detection method relies on classifier for fault detection. The classifier was trained using data, which incorporates variation due to rotor position misalignment, small load and speed changes. This makes the detection scheme robust under offline conditions with an assumption that temperature can be controlled in an acceptable range. The machine was controlled using Field Oriented Control (FOC) using Real Time LABVIEW. Two dimensional (2-D) Finite Element Analysis (FEA) was used to model and simulate the machine under healthy and faulty conditions to validate the results obtained from experiments.

Accurate insulation failure prognosis can avoid both unexpected failures and premature removal of machines from operation. One online prognosis technique uses a feature in the insulation current to accurately estimate remaining useful life. This technique, however, assumes consistent voltage application from the switching devices, which is not always typically the case. Degradation in the gate oxide of MOSFET devices produces an effect that can mask insulation degradation. Neglecting gate oxide degradation of MOSFETS in stator insulation prognosis techniques can lead to underestimation of remaining useful life. This work proposes a second signature in the phase current measurement of an inverter-driven electric machine to distinguish between insulation and MOSFET degradation. This signature does not require additional sensors and can be detected online. This modified stator insulation prognosis technique improves confidence in the remaining useful life estimate.

This paper presents interior permanent magnet (IPM) machine designs with non-conventional alignment of the magnet and reluctance axes. Typical IPM designs align the magnet axis 90 degrees from the reluctance axis, relying on less than optimal components of reluctance and magnet torque. As the magnet is aligned away from traditional designs, up to 45 degrees, the maximum reluctance and magnet torque become coincident, maximizing machine torque capability. Difficulties exist in alignment due to both the geometry and the material nonlinearity.

In this paper, the motor current/voltage signature analysis and linear discriminant analysis (LDA) are evaluated with respect to the accuracy to detect the status of permanent magnet synchronous machines (PMSMs) whether it is healthy or faulted, determine the type of that fault, and estimate the severity in the case of static eccentricity or turn-to-turn short-circuit fault. Three types of faults are discussed: static eccentricity, turn-to-turn short circuit, and partial demagnetization fault. Two-dimensional finite element analysis (FEA) is used to model and simulate the machine under healthy and faulted conditions. Fast Fourier transform is applied to the phase voltage or current signals to obtain the frequency spectrum. A combination of the amplitude of the harmonics of the stator voltage or current signals are used as detailed features for the classifier for fault detection. LDA is chosen as a classification method for both detecting the fault and estimating its severity. Two different winding types of PMSMs are tested: a concentrated and a distributed winding machine. To validate the simulation results, experiments at different operational points are carried out and the results are compared with the sFEA.

In this article, we try to bridge the gap between the knowledge of the effects of bearing currents as they may occur with modern power electronics-based variable-speed drives and the prediction of a bearing's remaining useful life (RUL). We discuss the measurements used and the procedures and methods that have been developed. We identify what we consider to be the necessary next steps and the open questions that exist as well as what we consider to be necessary actions to establish tools and methods for the reliable estimation of the RUL of bearings using measurements of different characteristics and costs.

This paper presents a comprehensive evaluation of several direct torque control (DTC) strategies for permanent magnet synchronous machines (PMSMs), namely DTC, model predictive DTC, and duty ratio modulated DTC. Moreover, field-oriented control is also included in this study. The aforementioned control strategies are reviewed and their control performances are analyzed and compared. The comparison is carried out through simulation, finite-element analysis, and experimental results of a PMSM fed by a two-level voltage source inverter. With the intent to fully reveal the advantages and disadvantages of each control strategy, critical evaluation has been conducted on the basis of several criteria: Torque ripple, stator flux ripple, switching frequency of inverter, steady-state control performance, dynamic response, machine losses, parameter sensitivity, algorithm complexity, and stator current total harmonic distortion.

Torque ripple of PMSMs can be reduced in design, but elaborate designs can be costly to manufacture. If an optimized machine design is obtained, performance can be further improved through control. Torque pulsations, more specifically torque ripple in PMSMs, could be decreased by injecting current harmonics on top of the operating currents. With new semiconductor devices that can handle higher switching frequencies, using a technique that injects higher order harmonics is possible. These injected currents can be calculated based on different methods that look at the different sources of ripple. The purpose of this paper is to identify and describe ways to measure or estimate torque ripple, and review control methods, both old and new, that have been proposed to reduce it. The paper provides information to machine designers to be able to further optimize the performance of an otherwise already optimal machine.

Present day PMSM design methodologies often use optimization tools. Optimizing the geometry alone, may lead to designs that have high efficiency and torque density but may have high torque ripple. By injecting high frequency currents, some optimal geometries with too high torque ripple, become acceptable and optimal, even with an increase in machine and inverter losses, and a decrease in efficiency. An optimization methodology is proposed that uses an analysis of FEM sample designs and a regression model to optimize a PMSM, using a multi-objective genetic algorithm (NSGA-II) and including high frequency injection for torque ripple reduction.

The performance of an optimized PMSM machine could be improved by using a control-based torque ripple reduction technique. Optimization of PMSM performance including a torque ripple reduction current injection technique and increasing the operating current, while keeping copper losses to a minimum could lead to a larger set of possible optimal solutions. By adding a torque ripple reduction method to the previously optimized geometries that would be not acceptable, they can become acceptable and optimal, with minimum added losses. Combining cases studied through FEM and a splines regression model together, with a non-sorting genetic algorithm, solutions that have injection and no injection are found to be optimal. This allows the designer to have geometries that would otherwise be rejected become acceptable.

This study presents a method to mitigate and alleviate the effects produced by a turn-to-turn short in a fault tolerant permanent magnet synchronous motor with single-layer concentrated windings. The rotor magnets are capable of inducing a high voltage across the fault contact point; this voltage has the potential to generate a high circulating current that promotes the rapid propagation of the fault due to the thermal stress created by the increased localized fault power losses. The scope of this study is for applications where postfault operation is desired, even if it means operating at reduced power capacity and lower speeds. Upon quick detection of a fault, the proposed technique can be used to decelerate the propagation of the fault and extend the machine's postfault life span. The technique consists of a magnetic field-weakening strategy at speeds below nominal, to reduce the voltage induced in the faulted portion. The concept is validated through finite element analysis, modeling, and experimental data. It is demonstrated that the proposed technique reduces the fault current magnitude and winding temperature.

Condition-based maintenance, which includes both diagnosis and prognosis of faults, is a topic of growing interest for improving the reliability of electrical drives. Bearings constitute a large portion of failures in rotational machines. Although many techniques have been successfully applied for bearing fault diagnosis, prognosis of faults, particularly predicting the remaining useful life (RUL) of bearings, is a remaining challenge. The main reasons for this are a lack of accurate physical degradation models and limited labeled training data. In this paper, we introduce a data-driven methodology, which relies on both time and time–frequency domain features to track the evolution of bearing faults. Once features are extracted, an analytical function that best approximates the evolution of the fault is determined and used to learn the parameters of an extended Kalman filter (KF). The learned extended KF is applied to testing data to predict the RUL of bearing faults under different operating conditions. The performance of the proposed method is evaluated on PRONOSTIA experimental testbed data.

Partial Discharges, if initiated give rise to progressive deterioration of insulation material and lowers its life expectancy. If allowed to persist further, PD can even lead to the electric breakdown of insulation. However, in spite of its damaging effects on machine insulation, its application during the production phase of machines, to avoid their permanent failure has gained importance in this research field. This paper discusses a Partial Discharge detection technique developed for medium voltage stator insulation utilizing an antenna to sense the discharge currents and record PD events produced inside a stator insulation. To reduce the effect of noise on detections process, some grounding techniques incorporated and later Undecimated Discrete Wavelet Transform was used to extract the discharge events from antenna output. To extract the best out of the technique, outputs were analyzed on a repetitive basis to make a confident decision on the presence of PD. This technique of detecting PD shows high sensitivity, as the detections are independent of the impedance of test setup used for experiments.

Wide bandgap semiconductor devices in machine drive topologies are becoming more prevalent. These devices improve efficiency and can operate at higher switching frequencies. However, higher switching frequencies will increase the electrical stress applied to the insulation of the machine. Electrical stress, excessive heating, mechanical vibrations, and environmental contamination are leading factors that contribute to insulation degradation. Breakdown of the insulation will lead to a short circuit fault between two conductors. Short circuit faults can quickly propagate and lead to catastrophic failure. This project proposes an online method to accurately predict the remaining useful life (RUL) of the stator insulation by monitoring a trend in the leakage current. As the insulation degrades, the magnitude of the overshoot in the transient response of the leakage current exponentially decreases. An analog peak detection circuit is used to acquire this magnitude using low frequency sampling. An Extended Kalman Filter is applied to predict the RUL of the insulation. The proposed strategy will improve machine reliability, especially when using wide bandgap devices, while not requiring expensive or special equipment for assessing the health of the insulation.

Inverter open circuit faults (IOCFs) in AC drives lead to undesired effects and thus, the reconfiguration of the drive to a post-fault operation mode is desirable. In the past some authors have proposed drive topologies and operation strategies to keep the drives operating after IOCFs. However, increased losses and temperatures during these post-fault operation modes lead to a reduced performance of the machine. This paper analyzes the occurring losses and the thermally defined operation limits of an induction machine during the post-fault operation. The analysis is performed by means of symmetrical components, finite element analysis and lumped parameter models.

[EN] With the expansion of the use of electrical drive sys- tems to more critical applications, the issue of reliability and fault mitigation and condition-based maintenance have consequently taken an increasing importance: it has become a crucial one that cannot be neglected or dealt with in an ad-hoc way. As a result research activity has increased in this area, and new methods are used, some based on a continuation and improvement of previous accomplishments, while others are applying theory and techniques in related areas. This Special Section of the IEEE Transactions on Industrial Informatics attracted a number of papers dealing with Advanced Signal and Image Processing Techniques for Electric Machine and Drives Fault Diagnosis and Prognosis. This editorial aims to put these contributions in context, and highlight the new ideas and directions therein.

The fault diagnosis of rotating electrical machines has received an intense amount of research interest during the last 30 years. Reducing maintenance costs and preventing unscheduled downtimes, which result in losses of production and financial incomes, are the priorities of electrical drives manufacturers and operators. In fact, both correct diagnosis and early detection of incipient faults lead to fast unscheduled maintenance and short downtime for the process under consideration. They also prevent the harmful and sometimes devastating consequences of faults and failures. This topic has become far more attractive and critical as the population of electric machines has greatly increased in recent years. The total number of operating electrical machines in the world was around 16.1 billion in 2011, with a growth rate of about 50% in the last five years [1].

A new electromagnetic device to measure the electrical losses in stator lamination stacks, along with its associated test procedure, is presented. This procedure provides the ability to distinguish between stators made of different types of materials and can be employed to evaluate finished stator stacks prior to motor assembly. The design and simulation - using both ordinary differential equation solvers in the preliminary phase and detailed finite-element analyses following that - of the aforementioned device are documented, along with experimental data supporting our conclusions.

In this paper, the effectiveness of a simplified characterization method for permanent magnet machines is evaluated through performance sensitivity analysis. Performance sensitivity analysis is a novel way to evaluate the effectiveness of any identification method, as it investigates the effects of parametric errors upon the output performance of a machine. Parametric errors are due to inaccuracies during the identification process. This evaluation tool was validated using a 10-kW SmCo interior permanent magnet machine characterized using two different identification methods. A detailed identification procedure is used as the basis for evaluating a simplified method. The performance experimental data were collected using torque controllers based on the parameters extracted with both approaches. This information is used to perform the sensitivity analysis over the operating range of the machine. Finally, the results are compared and analyzed to determine the effectiveness of the simplified characterization method and its implications on the control performance.

This paper compares the detection methods of static eccentricity in Interior Permanent Magnet Synchronous Machines (IPMSM). Four methods are discussed: The first method uses shift in the voltages in d–q plane to detect fault. The second method uses shift in peak of the incremental inductance curve for fault detection. The third method uses the combined information of harmonics present both in current and voltage to detect the fault. This makes the detection robust with respect to current controller bandwidth. Finally, the fourth method used for detection includes measuring vibrations using accelerometers. It is shown that all four methods detected static eccentricity. These methods are compared on the basis of utility of fault detection under online or offline conditions and under saturated conditions. For all four methods the machine was tested at healthy, 25% and 50% static eccentricity levels. Two-dimensional (2-D) Finite element analysis was used for simulating machine under healthy and faulty cases. The experiments were performed by controlling the machine using Labview Real-time.

Fault diagnosis and its extensions to failure prognosis aim to develop methods that decrease outages and thus increase reliability. Among these methods are redundancies and changes of topology, power levels, and control algorithms. Since diagnosis methods are imperfect, false positives and negatives, as well as delayed fault diagnosis, may occur. Although the diagnosis of a fault can lead to appropriate maintenance, the estimation of the time to failure through prognosis can lead to the timely mitigation of the fault and, in turn, can extend the lifetime and reliability of the drive. In this paper, we present a new approach to the mitigation of permanent-magnet ac motors that uses a failure prognosis method to predict failures and the remaining useful life and uses the output of the prognosis algorithm to decide when to modify the system and mitigate the fault. A methodology to calculate the mean time between failures with and without mitigation is also presented. The proposed approach is illustrated through a simple example of how the prognosis of failure due to a developing intermittent open circuit in one of the phases increases the drive reliability.

Single switch open circuit faults in three-phase AC-drives lead to undesired effects and potentially to a total failure of the drive. This paper proposes a post-fault operation strategy for such faults with the focus on the limitation of losses after the reconfiguration and thereby an extension of the possible range of operation. The performance of the strategy is shown both via simulations and experiments.

Partial demagnetization is studied in detail in this paper to understand its effects and develop a robust detection method. The voltage and current harmonics can be used to indicate that a fault exists but this method cannot always differentiate demagnetization from eccentricity. The inductance characteristics of the direct rotor oriented axis are used to verify the harmonic-based detection findings. The detection of partial demagnetization is improved by determining the incremental inductance over a range of direct axis currents; this way secondary ‘knees’ caused by asymmetrical rotor saturation are found. This asymmetrical saturation can be determined with the inductance. A detailed discussion and observation of the effect of partial demagnetization is novel compared to the literature. Three types of demagnetization are discussed in this paper: uniform demagnetization, partial demagnetization of one magnet and removal of three magnets from the rotor. Finite elements analysis is used to simulate the changes in the incremental inductance waveforms under each type of demagnetization. Experimental data is introduced in this paper to validate the incremental inductance results for the removal of three magnets.