Jordi-Roger Riba

Detection of Demagnetization Faults in Surface-Mounted Permanent Magnet Synchronous Motors by Means of the Zero-Sequence Voltage Component

This paper develops and analyzes an online methodology to detect demagnetization faults in surface-mounted permanent magnet synchronous motors. The proposed methodology, which takes into account the effect of the inverter that feeds the machine, is based on monitoring the zero-sequence voltage component of the stator phase voltages. The theoretical basis of the proposed method has been established. Attributes of the method presented here include simplicity, very low computational burden, and high sensibility. Since the proposed method requires access to the neutral point of the stator windings, it is especially useful when dealing with fault tolerant systems. A simple expression of the zero-sequence voltage component is deduced, which is proposed as a fault indicator parameter. Both simulation and experimental results presented in this paper show the potential of the proposed method to provide helpful and reliable data to carry out an online diagnosis of demagnetization failures in the rotor permanent magnets.

Diagnosis of Interturn Faults in PMSMs Operating Under Nonstationary Conditions by Applying Order Tracking Filtering

Interturn faults in permanent magnet synchronous machines may have very harmful effects if not early identified. This study deals with the detection of such faults when the machine operates under varying speed conditions. The performance of two methods is analyzed and compared, i.e., the analysis of the third harmonic of the stator currents and the first one of the zero-sequence voltage components. The Vold-Kalman filtering order tracking algorithm is introduced and applied to track the harmonics of interest when the machine operates under a wide speed range and different load levels. This study also presents two reliable fault indicators especially focused to detect stator winding interturn faults under nonstationary speed conditions. Experimental results endorse the methodology proposed, showing its potential to carry out a reliable fault diagnosis scheme.

A Back-emf Based Method to Detect Magnet Failures in PMSMs

Demagnetization faults are troublesome because they have a profound impact on the overall performance of permanent magnet synchronous motors (PMSMs). This work presents and verifies experimentally a system to detect such faults which is based on the measure of the zero sequence voltage component (ZSVC). The proposed method is also appropriate for inverter fed machines and is particularly useful when dealing with fault tolerant systems. A fault severity index which allows quantifying the harshness of such faults is also proposed and its behavior is analyzed from experimental data. Features of the proposed method include low computational burden, simplicity and high sensitivity. Experimental results conducted at different speed and load conditions show the potential of the proposed fault severity index for online diagnosis of demagnetization failures.

A Simple 2-D Finite-Element Geometry for Analyzing Surface-Mounted Synchronous Machines With Skewed Rotor Magnets

We present a new 2-D FEM-based system for analyzing permanent-magnet surface-mounted synchronous machines with skewed rotor magnets. The system is based on generating a geometric equivalent non-skewed permanent-magnet distribution that accounts for the skewed distribution of the practical rotor. An appealing feature of the proposed system is that it can be easily performed in any 2-D electromagnetic FEM package by performing a simple change in the geometry of the magnets. Attributes of the method presented here include simplicity, high accuracy, low computational burden, and high speed compared to 3-D and 2-D multislice FEM analysis. Experimental results with both healthy and faulty machines corroborate the effectiveness of the model proposed in this work.

Shaft Trajectory Analysis in a Partially Demagnetized Permanent-Magnet Synchronous Motor

Demagnetization faults have a negative impact on the behavior of permanent-magnet synchronous machines, thus reducing their efficiency, generating torque ripple, mechanical vibrations, and acoustic noise, among others. In this paper, the displacement of the shaft trajectory induced by demagnetization faults is studied. It is proved that such faults may increase considerably the amplitude of the rotor displacement. The direct measure of the shaft trajectory is performed by means of a noncontact self-mixing interferometric sensor. In addition, the new harmonics in the back electromotive force (EMF) and the stator current spectrum arising from the shaft displacement are analyzed by means of finite-element method (FEM) simulations and experimental tests. Since conventional finite-element electromagnetic models are unable to predict the harmonics arising from the shaft trajectory displacement, an improved finite-element model which takes into account the measured trajectory has been developed. It is shown that this improved model allows obtaining more accurate back EMF and stator current spectra than those obtained by means of conventional models. This work presents a comprehensive analysis of the effects generated by demagnetization faults, which may be useful to develop improved fault diagnosis schemes.

Influence of the Stator Windings Configuration in the Currents and Zero-Sequence Voltage Harmonics in Permanent Magnet Synchronous Motors With Demagnetization Faults

Demagnetization faults in permanent magnet synchronous motors may generate specific fault harmonic frequencies in the stator currents and the zero-sequence voltage component (ZSVC) spectra. Hence, by analyzing the stator currents or/and the ZSVC spectra it is possible to develop fault diagnosis schemes to detect such faults. In order to have a broad view of such effects, a representative set of stator windings configurations must be considered. By analyzing different stator windings configurations this paper shows that the amplitude of the harmonic frequencies of both the stator currents and the ZSVC spectrato be analyzed are significantly influenced by the stator windings configuration. It is also proved that depending on the winding configuration, new harmonic components may emerge in both spectra. The results presented in this paper may help to develop fault diagnosis schemes based on the acquisition and further analysis of the stator currents and the ZSVC harmonic components.

Runout Tracking in Electric Motors Using Self-Mixing Interferometry

In this paper, a self-mixing interferometry sensor has been used as a proximity probe to measure possible runout in permanent magnet synchronous motors, for fault diagnosis. A general procedure for the measurement of the 2-D trajectory of the motor shaft is described in detail, including procedures for the characterization of the uncertainty due to the shape of the shaft, and the management of speckle noise. The performance of the proposed sensor has been compared to that of a commercial Polytec laser vibrometer, for validation purposes. Results show inaccuracies in the order of ±6 μm, which agree well with the measured uncertainty introduced by shaft surface imperfections.

Inter-turn fault detection in five-phase pmsms. Effects of the fault severity

This paper deals with the effects of inter-turn short circuit faults in five-phase permanent magnet synchronous motors (PMSMs). For this purpose a finite-elements model (FEM) of a faulty machine with 1, 2 and 4 inter-turns in short circuit is analyzed. From the results of this model the effects of these fault severities in the stator currents and zero-sequence voltage components (ZSVC) harmonics is analyzed and the possibility of developing a fault diagnosis scheme based on the changes in their spectral content is exposed. Moreover, the effect of the fault severity on the total power losses in the machine is presented. Inter-turn faults generate large circulating currents which may lead to catastrophic failures. Therefore it is very important to know the increase in power losses in the machine due to the occurrence of such faults for applying corrective actions at the precise time once the fault has been diagnosed.

A cumulative energy demand indicator (CED), life cycle based, for industrial waste management decision making.

Life cycle thinking is a good approach to be used for environmental decision-support, although the complexity of the Life Cycle Assessment (LCA) studies sometimes prevents their wide use. The purpose of this paper is to show how LCA methodology can be simplified to be more useful for certain applications. In order to improve waste management in Catalonia (Spain), a Cumulative Energy Demand indicator (LCA-based) has been used to obtain four mathematical models to help the government in the decision of preventing or allowing a specific waste from going out of the borders. The conceptual equations and all the subsequent developments and assumptions made to obtain the simplified models are presented. One of the four models is discussed in detail, presenting the final simplified equation to be subsequently used by the government in decision making. The resulting model has been found to be scientifically robust, simple to implement and, above all, fulfilling its purpose: the limitation of waste transport out of Catalonia unless the waste recovery operations are significantly better and justify this transport.

Multi-objective optimal design of a five-phase fault-tolerant axial flux PM motor

Electric motors used for traction purposes in electric vehicles (EVs) must meet several requirements, including high efficiency, high power density and faulttolerance. Among them, permanent magnet synchronous motors (PMSMs) highlight. Especially, five-phase axial flux permanent magnet (AFPM) synchronous motors are particularly suitable for in-wheel applications with enhanced fault-tolerant capabilities. This paper is devoted to optimally design an AFPM for in-wheel applications. The main geometric, electric and mechanical parameters of the designed AFPM are calculated by applying an iterative method based on a set of analytical equations, which is assisted by means of a reduced number of three-dimensional finite element method (3D-FEM) simulations to limit the computational burden. To optimally design the AFPM, a constrained multi-objective optimization process based on a genetic algorithm is applied, in which two objective functions are considered, i.e. the power density and the efficiency. Several fault-tolerance constraints are settled during the optimization process to ensure enhanced fault-tolerance in the resulting motor design. The accuracy of the best solution attained is validated by means of 3D-FEM simulations.