698 research outputs found

    A New Method for Determining the Leakage Inductances of a Nine-Phase Synchronous Machine From No-Load and Short-Circuit Tests

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    The accurate determination of stator leakage inductances is presently an open issue in the analysis and testing of multi- phase electric machines. Calculation methods are available, which involve complicated and often poorly precise three-dimensional (3-D) analyses. Experimental determination techniques, using measurements on the wound stator with the rotor removed, are also possible, but quite impractical, as they need to be performed during machine manufacturing or require rotor withdrawal. In this paper, a new approach is proposed to determine all the stator self- and mutual leakage inductances of a nine-phase synchronous machine based on a minimal set (a couple) of magnetostatic finite- element (FE) simulations, and on the measurements taken during no-load and short-circuit routine tests. The procedure is applied to a wound-field salient pole nine-phase synchronous generator for validation, showing good accordance with the results obtained from measurements on the machine with the rotor removed. A discussion is also proposed on the possibility to extend the presented procedure to other multiphase topologie

    Identification of the Induction Motor Parameters at Standstill Including the Magnetic Saturation Characteristics

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    Identification of the induction motor parameters at standstill is studied in this thesis. The main goal of this work is to search for the feasible and applicable speed sensorless self-commissioning schemes. The magnetic saturation of the magnetizing inductance is taken into account. The magnetizing inductance is modeled as a function of the stator flux. Two different identification schemes are chosen based on the literature review. First method uses the single-axis sinusoidal excitation as the test signal. Second method uses the DC-decay test for the magnetizing inductance estimation and DC-biased sinusoidal excitation for the leakage inductance and rotor resistance identification. The DC-decay test is found to be a suitable method for identification of the magnetizing inductance. The single-axis sinusoidal excitation is found to be problematic in the saturation region. The source of the inaccuracy in the single-axis sinusoidal excitation is studied and the reasons are explained. The sensitivity of the schemes to the stator resistance and stator voltage errors is evaluated. Both methods show a very high sensitivity to the stator voltage errors in the case of the magnetizing inductance estimation. However, the DC-decay test shows a lower estimation error in the presence of the stator resistance errors. The estimation of the leakage inductance is robust against the stator voltage errors when the method based on the single-axis sinusoidal excitation is used. The estimation of the rotor resistance using the DC-biased excitation depends on the DC offset current in the presence of both the stator resistance and stator voltage errors

    Parameter Estimation of Asymmetrical Six-phase Induction Machines using Modified Standard Tests

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    In multiphase machine drives, accuracy of the estimated machine parameters is crucial for effective performance prediction and/or control. While a great amount of work has been done on parameter estimation for three-phase machines, corresponding discussions for six-phase machine remain scarce. It has been proven in the literature that the effect of mutual leakage inductance between different winding layers has a significant impact on the equivalent machine reactance, which challenges the standard separation method of stator and rotor leakage inductances from the measured locked-rotor impedance. In this paper, parameter identification of an asymmetrical six-phase induction machine using six-phase no-load and locked-rotor tests is discussed. A zero-sequence test using an improved equivalent circuit is proposed to improve the accuracy of the estimated parameters. The concept is verified using experimental results obtained from a low-power prototype asymmetrical six-phase machine

    Improved field oriented control for stand alone dual star induction generator used in wind energy conversion

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    This paper presents a novel direct rotor flux oriented control with online estimation of magnetizing current and magnetizing inductance applied to self-excited dual star induction generator equipping a wind turbine in remote sites. The induction generator is connected to nonlinear load through two PWM rectifiers. The fuzzy logic controller is used to ensure the DC bus voltage a constant value when changes in speed and load conditions. In this study, a performance comparison between the conventional approach and the novel approach is made. The proposed control strategy is validated by simulation in Matlab/Simulink

    Modeling induction machine winding faults for diagnosis

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    International audienceMonitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives. This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit. Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is performed with a large variety of techniques: parameter estimation, state observation, Kalman filtering, spectral analysis, neural networks, fuzzy logic, artificial intelligence, etc. Particular emphasis in this book is put on the modeling of the electrical machine in faulty situations. Electrical Machines Diagnosis presents original results obtained mainly by French researchers in different domains. It will be useful as a guideline for the conception of more robust electrical machines and indeed for engineers who have to monitor and maintain electrical drives. As the monitoring and diagnosis of electrical machines is still an open domain, this book will also be very useful to researchers

    Diagnosis of induction machines by parameter estimation

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    International audienceThe type of control system used for electrical machines depends on the use (nature of the load, operating states, etc.) to which the machine will be put. The precise type of use determines the control laws which apply. Mechanics are also very important because they affect performance. Another factor of essential importance in industrial applications is operating safety. Finally, the problem of how to control a number of different machines, whose interactions and outputs must be coordinated, is addressed and solutions are presented. These and other issues are addressed here by a range of expert contributors, each of whom are specialists in their particular field. This book is primarily aimed at those involved in complex systems design, but engineers in a range of related fields such as electrical engineering, instrumentation and control, and industrial engineering, will also find this a useful source of information

    Numerical estimation and experimental verification of optimal parameter identification based on modern optimization of a three phase induction motor

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    The parameters of electric machines play a substantial role in the control system which, in turn, has a great impact on machine performance. In this paper, a proposed optimal estimation method for the electrical parameters of induction motors is presented. The proposed method uses the particle swarm optimization (PSO) technique. Further, it also considers the influence of temperature on the stator resistance. A complete experimental setup was constructed to validate the proposed method. The estimated electrical parameters of a 3.8-hp induction motor are compared with the measured values. A heat run test was performed to compare the effect of temperature on the stator resistance based on the proposed estimation method and the experimental measurements at the same conditions. It is shown that acceptable accuracy between the simulated results and the experimental measurements has been achieved

    Investigation on SVM-Backstepping sensorless control of five-phase open-end winding induction motor based on model reference adaptive system and parameter estimation

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    This paper deals with a new control technique applied to five-phase induction motor under open-end stator winding (FPIM-OESW) topology using the backstepping nonlinear control. The main objective is to improve the dynamics of this kind of machine, which is intended to be used in high power industrial application, where the maintenance is difficult and the fault tolerant is needed to ensure the continuous motor operating mode with minimized number of interruption. This control technique is combined with the Space Vector Pulse Width Modulation (SVPWM) to maintain a fixed switching frequency. In addition, the Model Reference Adaptive System (MRAS) concept is used for the estimation of the load torque, the rotor flux and the rotor speed to overcome the main drawbacks presented with the previous sensorless systems concepts. However, the great sensitivity to the changes of the motor internal parameters and it operating instability problems, especially in low-speed operating region, that causes an estimation error of the rotor speed, is the most disadvantage of the MRAS technique. Therefore, to solve this problem, an estimation method of the motor internal parameters such as the rotor resistance, the stator resistance and the magnetizing inductance, is proposed in this paper. Where, the main aim is to improve furthermore the control performance, to reduce the computational complexity and to minimize the rotor speed estimation error. The obtained simulation results confirm the enhanced performance and the clear efficacy of the proposed control technique under a variety of cases of different operating conditions. - 2019 Karabuk UniversityScopu

    Advanced wound-rotor machine model with saturation and high-frequency effects

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    Nowadays, the doubly–fed induction generator (DFIG) is perhaps the most common type of generator used in onshore wind turbines. With the thriving development of wind energy, there is a high demand for precisely predicting the dynamic performance of the DFIG. Due to the involvement of power electronics, massive high–frequency harmonics are injected into the machine leading to high–frequency effects such as parasitic currents. As the core of DFIGs, the wound–rotor induction machine must be well modeled to capture these significant phenomena in the operation of wind turbines. However, the T–equivalent model, which is currently the most widely used model in machine dynamic studies and controller designs, is incapable to simulate machine behaviors in the high–frequency range. The aim of this research is to develop a novel model of a wound–rotor induction machine, which incorporates magnetic saturation of the main flux path and high–frequency effects. The model’s experimental parameterization procedure is described in detail. This consists of standstill frequency response tests, and a test for determining the machine’s magnetizing characteristic and turns ratio. Time–domain simulations are used to highlight the capabilities of the proposed model, and to compare its predictions with those of a classical model at both transient and steady states. The results show that the proposed model can better capture the dynamic performance with the consideration of magnetic saturation. What is more, the high–frequency current ripples, which are caused by common–mode ground currents can also be simulated in the proposed model
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