Model Of Induction Machine Research Articles

Time-harmonic finite element model for brushless doubly-fed induction machine in natural operating mode

The natural mode of operation for the brushless doubly-fed induction machine is a particular instance of synchronism at a so-called natural rotor velocity when one stator winding is powered by an AC and the other by a DC voltage source. Consequently, in addition to the rotating magnetic field, there exists a magnetic field that is fixed to the stator frame of reference. Analysis in this specific mode is essential as the natural velocity arises from the choice of pole numbers, thereby determining machine efficiency. However, this presents a significant challenge when it comes to mathematical modeling using complex-valued steady-state models through either equivalent-circuit or finite element analysis. This paper presents a study on the extension of the recently-proposed steady-state complex-valued finite element model for the brushless doubly-fed induction machine to enable its application in the natural operating mode. A high correlation with the data obtained from a time-stepping model is obtained for the extended model when subjected to both low and high levels of saturation of the magnetic circuit. This extension makes the whole approach applicable in all operating conditions and modes of the brushless doubly-fed induction machine. Considering the nearly two orders of magnitude lower computational costs associated with analysis via the proposed model compared to time-stepping analysis, it is particularly useful in scenarios that involve extensive computations and require multiple cases to be considered such as design sensitivity analysis, topology optimization or a connection with machine learning techniques.

A Mathematical Review Study on Dynamical Models of Symmetrical Three-Phase Induction Machine in Various Reference Frames

This paper presents dynamic models of a three-phase induction machine in various reference frames widely employed in alternating-current (ac) machine analysis. The main objective is to derive and explain the machine model in relatively basic terms by using the idea of rotating reference frame theory. Many matrix manipulations and complex frame-to-frame transformations performed to obtain an advanced model from primitive dynamical equations are presented in a more compact and easy-to-understand way. Therefore, this paper reviews a detailed, yet simple and understandable mathematical background on the dynamic models of the induction machine. Furthermore, a unified and broadly applicable simulation model is proposed for simulating the dynamic behavior of the machine in any desired reference frame. The simulation model has also a modular and user-friendly structure. For the simulation studies, Matlab/Simulink environment is preferred due to its popularity. A Simulink machine model with several subsystems is explicitly given. The simulation study is realized for a small power induction machine operating under both load and no-load conditions. The variations of three-phase currents, electromagnetic torque, and rotor mechanical speed as well as the rotor flux-linkage components are shown. The key features of each reference frame are discussed, especially through the measured rotor flux-linkage components.

Early artificial neural networks diagnosis using admittance model of a three-phase induction machine with inter-turn short-circuit fault

Early artificial neural networks diagnosis using admittance model of a three-phase induction machine with inter-turn short-circuit fault

Analysis of power system frequency and active power based on wind-storage combined frequency modulation system

Abstract To solve the problem of frequency and active power regulation of power systems, this paper proposes a wind-storage combined frequency modulation strategy. The mathematical models of doubly-fed induction machines, pump turbines, and wind turbines are established. Based on wind power frequency modulation, the doubly-fed variable-speed pumped storage unit is added to establish a combined frequency modulation system, and a simulation model on Simulink to analyze the participation of different parts of the combined system in frequency modulation and the active power output of the unit when the load changes. The simulation results show that when the load increases or decreases, the addition of a doubly-fed variable speed pumped storage unit can effectively improve the frequency modulation performance of the system, reduce the fluctuation numbers and amplitude, and reduce the deviation after stabilization. By changing its active power output, a new balance of the system power can be reached, which is conducive to the secure and steady functioning of the power system.

Thermal finite element modeling and simulation of a squirrel-cage induction machine

Finite element models of electrical machines allow insights in electrothermal stresses which endanger the insulation system of the machine. This paper presents a thermal finite element model of a 3.7 kW squirrel-cage induction machine. The model resolves the conductors and the surrounding insulation materials in the stator slots. A set of transient thermal scenarios is defined and measured in the machine laboratory. These data are used to assess the finite element model.

An optimization-aided approach to parametrize scalable models of induction machines in speed variable drives

The accurate and time-saving prediction of essential machine variables (output power, torque, and efficiency) is crucial for manufacturers offering a wide power range of induction machines. Many motor variants are typically produced by axially scaling and rewinding the machine. Rescaling procedures of electromagnetic models of induction machines are in everyday use and well known. However, while a high accuracy can be achieved by rescaling in theory, more significant deviations between simulated and measured output parameters of the realized scaled device occur in praxis. These deviations can mainly be attributed to the faulty separation of effects in the distinct machine components, such as the rotor, stator, and bearings. This paper introduces an optimization-aided modeling approach based on the induction machine’s simple equivalent circuit representation. The method is validated by measurement data obtained from many induction machines with various axial lengths and winding configurations.

Tensor Product Alternatives for Nonlinear Field-Oriented Control of Induction Machines

The paper presents a nonlinear field-oriented control technique based on the tensor product representation of the nonlinear induction machine model and the solvability of linear matrix inequalities. The nonlinear model has 32 quasi linear parameter-varying equivalent variants, and it is shown that only half of the models result in feasible controller. Two control goals are realized: torque control and speed control. The controller is a nonlinear state feedback controller completed by integral action. A new block diagram is investigated for speed control. The controller gains are designed by the solution of linear matrix inequalities to solve the Lyapunov inequality to obtain a stable and fast response and constraints on the control signal. The presented methods are verified and compared by simulations.

An Enhanced Path Finder Algorithm for the estimation of the stator current envelope to detect rotor bar breakage in an induction motor

The Enhanced Path Finder Algorithm (EPFA) is used in this research to present an innovative approach for examining the state of the rotor bars in an induction motor, employing a hybrid metaheuristic algorithm. Compared to current optimization techniques, the suggested approach permits more balanced exploration and exploitation. The method addresses the drawbacks of traditional analysis of fault related frequencies, such as short data length, spectrum leakages, and inadequate sampling frequency. The primary goal of this research is to identify the twice-slip frequency component and its harmonics in the current envelope that correlates with the fault. The A signal model of the stator current envelope and the residual error function have been used to define a nonlinear least-squares problem. An induction machine model has been developed in 2D ANSYS Maxwell software where faults have been implemented and studied. Finally, the efficiency of the fault detection scheme has been verified with a practical data set.

Field-Oriented Control of a Nine-Phase Cage Induction Generator with Large Speed Changes and Variable Load

This paper presents a voltage control system for multiphase squirrel-cage induction generators operating at a high variability of speed and variable load. Field-oriented vector control was used with a change in the sequence of the stator phase currents what changes the number of poles of the magnetic field produced by nine-phase stator winding. At low speeds, the current sequence is changed so that the number of poles increases allowing for the desired voltage to be obtained with greater efficiency. The task of the automatic control system was to control the DC voltage to a desired value at the output of the multiphase PWM converter. This is an alternative control method to the scalar control of voltage and frequency presented in a previous work. The control method and parameters of the automatic control system result from the mathematical model of the multiphase induction machine. The results of the laboratory tests were compared with the effects of the operation of the same nine-phase scalar controlled generator.

On Accurate Discrete-Time Dynamic Models of an Induction Machine

Induction machines have become the standard for highly demanding industrial applications. This has led to the utilization of modern discrete-time control techniques (such as model predictive control) that require the estimation of internal variables that are not subject to measurement (such as the rotational velocity in sensorless applications). From this point of view, it is fundamental to have accurate discrete-time models of induction machines, particularly given their nonlinear nature, so that control techniques perform according to design requirements. In spite of the above, the modeling of induction machines has not received much attention in the literature, even though more powerful machines and faster microcontrollers are currently being used. To better understand induction machine models for control, in this paper, we develop and compare various discrete-time models of induction machines based on Euler, Taylor, and Runge–Kutta methods. In addition, we compare the Extended Kalman Filter and Unscented Kalman Filter for state estimation in terms of accuracy and computational burden. The models are derived and compared through extensive Monte Carlo simulations and the state estimation techniques are compared in terms of root mean squared error, execution time, and maximum absolute error. Our simulations show that, in general, the Taylor method yields more accurate models than both the Runge–Kutta and Euler methods. In particular, the Taylor method results in a root mean square error that is one order of magnitude smaller than the Euler method for stator current and rotor flux linkages. For rotor angular speed, the Runge–Kutta methods are more accurate than both the Taylor and Euler methods, resulting in a root mean square error that is two orders of magnitude smaller than the Euler method. On the other hand, the Extended Kalman Filter results in smaller execution time than the Unscented Kalman Filter, up to two orders of magnitude. In terms of root mean squared error and maximum absolute error, both filtering algorithms perform similarly.

Semianalytical modeling of squirrel-cage induction machines with consideration of iron permeability and eddy-currents using elementary subdomain technique

PurposeThis paper aims to propose a semianalytical model of a squirrel-cage induction machine (SCIM), considering local magnetic saturation and eddy-currents induced in the rotor bars.Design/methodology/approachThe regions of the rotor and stator are divided into elementary subdomains (E-SDs) characterized by general solutions at the first harmonic of the magneto-harmonic Maxwell’s equations. These E-SDs are connected in both directions (i.e., along the r- and θ-edges).FindingsThe calculation of the magnetic field has been validated for various values of slip and iron permeability. All electromagnetic quantities were compared with those obtained using a two-dimensional finite-element method. The semianalytical results are satisfactory compared with the numerical results, considering both the amplitude and waveform.Originality/valueExpansion of the recent analytical model (E-SD technique) for the full prediction of the magnetic field in SCIMs, considering the local saturation effect and the eddy-currents induced in the rotor bars.

Generalized High-Fidelity Reduced-Order Model of Doubly-Fed Machines and Induction Machines

Generalized High-Fidelity Reduced-Order Model of Doubly-Fed Machines and Induction Machines

Multiple Frequency Shifting and Its Application to Accurate Multi-Scale Modeling of Induction Machine

Multiple Frequency Shifting and Its Application to Accurate Multi-Scale Modeling of Induction Machine

Magnetic Field-Based Induction Machine Modeling Incorporating Space and Time Harmonic Effects

Magnetic Field-Based Induction Machine Modeling Incorporating Space and Time Harmonic Effects

FEM and CFD thermal modeling of an axial-flux induction machine with experimental validation

Axial-flux electrical machines are ideal candidates as in-wheel motors for electrical vehicles (EVs). Due to their characteristics of high power density and compact structure, thermal management is vital for them. Lowering the temperature of the stator windings can protect the insulation material from rapid degradation and reduce the extra copper losses by decreasing their electrical resistance. Contrary to the widely reported axial-flux permanent magnet synchronous machines, thermal modeling methods of axial-flux induction machines are rarely seen in previous literature. Hence, the present work aims at investigating their thermal response based on both the finite element method (FEM) and computational fluid dynamics (CFD) techniques. In addition, a test rig is built to validate the computed results of these two thermal models with the experimental measurement. The CFD conjugate heat transfer analysis is found to be more accurate than the FEM thermal analysis in predicting the temperature distribution of different components in the machine and the temperature rise of the airflow, with lower than 5 ∘C average errors deviating from the corresponding measured data at three rotation speeds. Additionally, the CFD simulation is able to capture the backflow occurring near the outlets of the casing that has been found during the experiments.

Saturable Voltage-Behind-Reactance Models of Induction Machines Including Air-Gap Flux Harmonics

Accurate and numerically efficient models of induction machines are of critical importance for reliable analysis and simulation of large-scale power systems. Specifically, modeling magnetic saturation that causes air-gap flux harmonics, which can significantly affect machine dynamics, has been the focus of many research efforts. In this paper, two voltage-behind-reactance (VBR) models are proposed for induction machines which formulate the air-gap flux harmonics caused by the main flux saturation. Specifically, the proposed constant-parameter VBR (CPVBR) model can be conveniently interfaced with the external network using constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RL</i> branches and controlled voltage sources. The numerical performance of the two proposed VBR models is validated and benchmarked against the state-of-the-art models of induction machines with saturation and air-gap flux harmonics. It is shown that the proposed models offer superior numerical performance (i.e., higher accuracy and simulation speed) compared to the existing models, which would be beneficial for offline and/or real-time simulations of power systems.

Data-Driven-Based Vector Space Decomposition Modeling of Multiphase Induction Machines

For contemporary variable-speed electric drives, the accuracy of the machine's mathematical model is critical for optimal control performance. Basically, phase variables of multiphase machines are preferably decomposed into multiple orthogonal subspaces based on vector space decomposition (VSD). In the available literature, identifying the correlation between states governed by the dynamic equations and the parameter estimate of different subspaces of multiphase IM remains scarce, especially under unbalanced conditions, where the effect of secondary subspaces sounds influential. Most available literature has relied on simple RL circuit representation to model these secondary subspaces. To this end, this paper presents an effective data-driven-based space harmonic model for n-phase IMs using sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover the IM governing equations. Moreover, the proposed approach is computationally efficient, and it precisely identifies both the electrical and mechanical dynamics of all subspaces of an IM using a single transient startup run. Additionally, the derived model can be reformulated into the standard canonical form of the induction machine model to easily extract the parameters of all subspaces based on online measurements. Eventually, the proposed modeling approach is experimentally validated using a 1.5 Hp asymmetrical six-phase induction machine.

Comparative Study of Two Nonlinear Control Strategies of Induction Motors considering Heating and Magnetic Saturation

Feedback linearization technique (FLT) linearizes the model of induction machine (IM). This actuator suffers from the variation of its inductances due to saturation and resistances due to joule and skin effects. Sliding-mode control (SMC) is widely recognized as a robust technique against parametric variations of IM. This control strategy has the advantage of being simple to implement and requires only a simple flux observer. This explains the use of FLT and SMC in this work to control an IM while taking into account the magnetic saturation and heating of the IM. Simulation results, conducted in a MATLAB/Simulink environment, demonstrate the relevance and efficiency of the proposed control schemes.

Induction Machine Emulation for Variable Frequency Drive Converter Faults

Voltage in current out (VICO) models are commonly used for induction machine (IM) emulation. This model does not provide the information of back-emf and hence cannot be used for open circuit fault emulation. A current in voltage out model (CIVO) is an alternate IM model where it provides back-emf information. However, the CIVO model cannot be used directly with the conventional emulator configuration. Hence, in this paper, a new emulator configuration has been proposed to accommodate the CIVO model. The model is used in a new emulator configuration by incorporating physical emulator parameters. The paper further discusses the upgrade of the model considering saturation nonlinearities. The emulator employing such a model mimics the real induction machine back-emf with high accuracy. The proposed emulator is tested for different gate driver faults such as single switch and multiple switch open faults, starting and speed changing conditions. The experimental results are validated with a 5 hp machine. Different fault signatures are also identified with the help of the emulator to help with fault diagnosis and localization.

Transient thermal models of induction machines under Inter‐turn short‐circuit fault conditions

AbstractInduction machines are the working horses in a lot of industries. Inter‐turn short‐circuit (ITSC) fault is one of the most common failure modes taking place in them. It can generate large fault currents that lead to a local temperature rise in the faulty stator slot, which deteriorates the working performance of the machine or even cascades to a complete machine breakdown. This article focuses on developing transient thermal models for an induction machine under ITSC faults. The aim of these thermal models is to understand the thermal behaviour of the induction machine at different ITSC fault propagation stages. The first thermal model is based on finite element method (FEM) simulation that includes a physics‐based model for the thermal contact resistance. The second thermal model is a lumped parameter thermal network that models the stator as inter‐connected slot‐number parts. They are both capable of modelling the characteristic of non‐uniform temperature along the circumferential direction for the induction machine operating under ITSC fault conditions. After area‐weighted averaging the results of the FEM simulation, it is found they are quantitatively consistent, with an average relative error magnitude of 5%, as well.