918 research outputs found

    Healthy and open phase PMaSynRM model based on virtual reluctance concept

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    © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The trend in the industrial power electronics electrical drives is to reach high power density and high efficiency in variable load conditions at cost-effective unwasteful designs. Currently, motors with permanent magnets (such as IPMSM and PMaSynRM) are of great interest because of compactness, low losses, and high torque capability. The performance of a drive system can be predicted with a motor electromagnetic authentic nonlinear model. In this paper, a novel, fast, and precise motor model of PMaSynRM based on virtual reluctance (VR) is proposed. It takes into account the cross saturation, winding distribution, space harmonics, slotting effect, and stepped skewing. The virtual reluctances are identified by finite element analysis (FEA) and implemented in the time-stepping simulation. The flux inversion is not required. The proposed concept is useful in the rotating field or phase quantities (for open phase simulation). The model is also discretized for SiL and HiL applications. Finally, the validation in FEA and experimental setup was performed.This work was supported in part by Spanish Ministry of Economy and Competitiveness under TRA2016-80472-R Research Project and Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya under 2017SGR967.Peer ReviewedPostprint (author's final draft

    Electrical and magnetic faults diagnosis in permanent magnet synchronous motors

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    Permanent magnet synchronous motors (PMSMs) are an alternative in critical applications where high-speed operation, compactness and high efficiency are required. In these applications it is highly desired to dispose of an on-line, reliable and cost-effective fault diagnosis method. Fault prediction and diagnosis allows increasing electric machines performance and raising their lifespan, thus reducing maintenance costs, while ensuring optimum reliability, safe operation and timely maintenance. Consequently this thesis is dedicated to the diagnosis of magnetic and electrical faults in PMSMs. As a first step, the behavior of a healthy machine is studied, and with this aim a new 2D finite element method (FEM) modelbased system for analyzing surface-mounted PSMSs with skewed rotor magnets is proposed. It is based on generating a geometric equivalent non-skewed permanent magnet distribution which accounts for the skewed distribution of the practical rotor, thus avoiding 3D geometries and greatly reducing the computational burden of the problem. To diagnose demagnetization faults, this thesis proposes an on-line methodology based on monitoring the zero-sequence voltage component (ZSVC). Attributes of the proposed method include simplicity, very low computational burden and high sensibility when compared with the well known stator currents analysis method. A simple expression of the ZSVC is deduced, which can be used as a fault indicator parameter. Furthermore, mechanical effects arising from demagnetization faults are studied. These effects are analyzed by means of FEM simulations and experimental tests based on direct measurements of the shaft trajectory through self-mixing interferometry. For that purpose two perpendicular laser diodes are used to measure displacements in both X and Y axes. Laser measurements proved that demagnetization faults may induce a quantifiable deviation of the rotor trajectory. In the case of electrical faults, this thesis studies the effects of resistive unbalance and stator winding inter-turn short-circuits in PMSMs and compares two methods for detecting and discriminating both faults. These methods are based on monitoring and analyzing the third harmonic component of the stator currents and the first harmonic of the ZSVC. Finally, the Vold-Kalman filtering order tracking algorithm is introduced and applied to extract selected harmonics related to magnetic and electrical faults when the machine operates under variable speed and different load levels. Furthermore, different fault indicators are proposed and their behavior is validated by means of experimental data. Both simulation and experimental results show the potential of the proposed methods to provide helpful and reliable data to carry out a simultaneous diagnosis of resistive unbalance and stator winding inter-turn faults

    Design and fabrication of a long-life Stirling cycle cooler for space application. Phase 3: Prototype model

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    A second-generation, Stirling-cycle cryocooler (cryogenic refrigerator) for space applications, with a cooling capacity of 5 watts at 65 K, was recently completed. The refrigerator, called the Prototype Model, was designed with a goal of 5 year life with no degradation in cooling performance. The free displacer and free piston of the refrigerator are driven directly by moving-magnet linear motors with the moving elements supported by active magnetic bearings. The use of clearance seals and the absence of outgassing material in the working volume of the refrigerator enable long-life operation with no deterioration in performance. Fiber-optic sensors detect the radial position of the shafts and provide a control signal for the magnetic bearings. The frequency, phase, stroke, and offset of the compressor and expander are controlled by signals from precision linear position sensors (LVDTs). The vibration generated by the compressor and expander is cancelled by an active counter balance which also uses a moving-magnet linear motor and magnetic bearings. The driving signal for the counter balance is derived from the compressor and expander position sensors which have wide bandwidth for suppression of harmonic vibrations. The efficiency of the three active members, which operate in a resonant mode, is enhanced by a magnetic spring in the expander and by gas springs in the compressor and counterbalance. The cooling was achieved with a total motor input power of 139 watts. The magnetic-bearing stiffness was significantly increased from the first-generation cooler to accommodate shuttle launch vibrations

    Modelling, Fault Detection and Control of Fault Tolerant Permanent Magnet Machine Drives

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    On-line Condition Monitoring, Fault Detection and Diagnosis in Electrical Machines and Power Electronic Converters

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    The objective of this PhD research is to develop robust, and non-intrusive condition monitoring methods for induction motors fed by closed-loop inverters. The flexible energy forms synthesized by these connected power electronic converters greatly enhance the performance and expand the operating region of induction motors. They also significantly alter the fault behavior of these electric machines and complicate the fault detection and protection. The current state of the art in condition monitoring of power-converter-fed electric machines is underdeveloped as compared to the maturing condition monitoring techniques for grid-connected electric machines. This dissertation first investigates the stator turn-to-turn fault modelling for induction motors (IM) fed by a grid directly. A novel and more meaningful model of the motor itself was developed and a comprehensive study of the closed-loop inverter drives was conducted. A direct torque control (DTC) method was selected for controlling IM’s electromagnetic torque and stator flux-linkage amplitude in industrial applications. Additionally, a new driver based on DTC rules, predictive control theory and fuzzy logic inference system for the IM was developed. This novel controller improves the performance of the torque control on the IM as it reduces most of the disadvantages of the classical and predictive DTC drivers. An analytical investigation of the impacts of the stator inter-turn short-circuit of the machine in the controller and its reaction was performed. This research sets a based knowledge and clear foundations of the events happening inside the IM and internally in the DTC when the machine is damaged by a turn fault in the stator. This dissertation also develops a technique for the health monitoring of the induction machine under stator turn failure. The developed technique was based on the monitoring of the off-diagonal term of the sequence component impedance matrix. Its advantages are that it is independent of the IM parameters, it is immune to the sensors’ errors, it requires a small learning stage, compared with NN, and it is not intrusive, robust and online. The research developed in this dissertation represents a significant advance that can be utilized in fault detection and condition monitoring in industrial applications, transportation electrification as well as the utilization of renewable energy microgrids. To conclude, this PhD research focuses on the development of condition monitoring techniques, modelling, and insightful analyses of a specific type of electric machine system. The fundamental ideas behind the proposed condition monitoring technique, model and analysis are quite universal and appeals to a much wider variety of electric machines connected to power electronic converters or drivers. To sum up, this PhD research has a broad beneficial impact on a wide spectrum of power-converter-fed electric machines and is thus of practical importance
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