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Wound Rotor Induction Machine (WRIM) connected to stator and rotor Voltage Source Converters (VSCs), known as the Double-Inverter-fed WRIM drive, can be viewed as two virtual Squirrel Cage Induction Machine (SQIM) drives, when seen from air-gap. In this article, this feature of WRIM is explored to develop an improved Dual Direct Torque Control (DDTC) technique such that, two individual and independent conventional DTC controllers can be directly employed to control the stator and rotor VSCs. The improved technique is inculcated with all the benefits of conventional DTC controller, especially the benefit of zero dependency on rotor position. Furthermore, the increased torque ripple with the conventional DTC controllers is mitigated by modifying the Switching Tables (STs) such that, the Voltage Vectors (VVs) emulated in the air-gap are equivalent to a 3-Level Neutral Point Clamped (3L-NPC) VSC. The STs are developed by analyzing the WRIM as an Open-End Winding Induction Machine (OEWIM). To demonstrate the performance of the proposed DDTC technique, the experimental results obtained from 3 kW WRIM are presented, under various transients and steady state conditions. The reduction in the torque ripple is demonstrated by estimated torque ripple waveforms, at different speeds.

This work describes a frequency-dependent bearing voltage model for squirrel-cage induction motors. Previous researches related to bearing voltages commonly considered the bearing voltage ratio (BVR) as a constant. However, it is important to analyze the frequency-dependent behavior of BVR when dealing with systems excited by high switching frequency PWM voltages. First, we measured the BVR characteristic for a 1.5-kW test motor. The measurement data shows that, in the mid-frequency range (100 kHz to 6 MHz), the BVR values are smaller than the conventional low-frequency constant value, and at higher frequencies, the BVR value increases above the low-frequency value. Considering this BVR characteristic, an equivalent circuit has been built and analyzed from the perspective of BVR. The proposed equivalent circuit has been verified by comparing simulation data with measurement data. Based on the analysis results of the equivalent circuit, a parametric study was done to examine the effects of motor system parameters on bearing voltage. For the study, variations of the bearing voltage on the changes of the input voltage waveforms and the winding-to-stator capacitance are analyzed by using measurement and simulation data.

A novel squirrel cage eddy current coupling with adjustable radial air gap was presented, which can change the output speed by changing the air gap thickness in radial direction between the copper strips and the permanent magnet. It has the advantages of no axial force in speed regulation and less eccentric force in axisymmetric structure. The 2-D electromagnetic torque model of the rotor was established, and the influence of the air gap thickness on the electromagnetic torque was also studied by finite element method. Further, a novel method to solve the dynamic equation of the eddy current coupling was proposed based on the effect of air gap thickness and relative speed on torque characteristics, and was applied to the speed regulation performance analysis. In addition, the influence of the relative magnetic permeability of the permanent magnet back yoke and the internal rotor on the speed regulation performance was studied.

This article presents an electromagnetic compatibility (EMC) aware motor design method based on the prediction of the impedances of a stator winding structure. The stator structure is divided into several two-dimensional parts, and their network parameters are extracted by electromagnetic (EM) simulations. Through conversion and synthesis of the multiport network parameters, the input impedance can be found for the full-winding structure. The calculated input impedance approximately follows the measured impedance of tested induction motors. The impedance calculation method has been realized in a parametric analysis platform to enable the EMC-aware design of induction motors. By using the platform, the variations of the input impedances by different design parameters can be analyzed along with consideration of loss and torque ripple. To verify the proposed method, prototype motors were assembled and the common-mode (CM) currents were measured under driving operation. The results show that the CM current can be reduced up to 10 dB in the frequency range of interest when the number of parallel circuit is reduced, as estimated from the calculated input impedances.

Currently, asynchronous cage motors are among the most commonly requested machines accentuated by their extension to the field of electric vehicles. Therefore, the development of robust and sophisticated controls for this machine is of significant interest. Artificial intelligence control techniques, such as fuzzy logic, are at the forefront of recent research. However, their design becomes much more complicated for a motor via a multilevel inverter. The main purpose of this paper is to show that it is possible to achieve fuzzy logic control of a squirrel cage asynchronous motor supplied via the usual two-level inverter. This is achieved, by adopting a DTC strategy based on a sinusoidal PWM with multilevel inverter. It employs a feedback information estimator with dual structure between the sliding mode observer at low speed and the model reference adaptive system in sliding mode at high speed. For both installations, speed is regulated using a sliding mode controller.

The accurate calculation of stray load loss has an important contribution to increasing motor efficiency. The stray load loss can be regarded as the difference of the total iron losses and harmonic rotor cage losses between the no load and load conditions. A method combining the general airgap field modulation theory (GAFMT) and 2D finite element analysis (FEA) is proposed for calculating the stray load loss of the squirrel cage induction motor (SCIM). Firstly, the amplitudes and rotation speeds of the main space harmonics of the airgap magnetic flux density are calculated based on the GAFMT. And the relationships between these space harmonics and stray load loss are analyzed. Secondly, these space harmonics are synthesized by the equivalent current layers in the airgap and then are substituted into the 2D FEA models to calculate the losses. At last, the stray load loss calculated by the proposed method is compared with that obtained by practical motor tests.

This study focused, the stator and rotor slot permeance coefficient values of an induction motor with a 3-phase squirrel cage are optimized using the Average Differential Evolution (ADE) algorithm and it is aimed to maximize the torque values (starting, maximum, and nominal) of the motor. In this context, the stator and rotor slot parameters of the motor (slot heights, widths, etc.) are optimized to give the minimum stator / rotor inductance and leakage reactance values. Thanks to obtained the new stator and rotor slot geometries, an improvement of 12.07% at the starting torque, an improvement of 5.40% at maximum torque and an increase of 1.13% at nominal torque value were achieved. In addition, total permeance, inductance and leakage reactance values and convergence curves for different slip conditions are given comparatively. © 2021 Faculty of Engineering, Ain Shams University

This article deals with the determination of the rotor time-constant of an induction machine by performing a flux-decay test in generic load conditions. The flux-decay transient occurs when the supply stator voltage is turned off suddenly. In this way, from the decay envelope of stator back-electromotive forces and, in the case of the wound rotor machine, from that of the rotor currents, the rotor time-constant can be extrapolated with a high level of accuracy. In this article, an in-depth analysis of this methodology is reported, whose validation has been carried out on both the squirrel cage and wound rotor motors. The estimated value of rotor time-constant can be used for the machine torque regulation, using the well-known control schemes presented in the literature and whose performance in the low-speed operation is affected by the detuning of this parameter. Since the inverter-fed motors nowadays characterize most of the share in the market of adjustable speed drives, experimental results concerning the flux decay test performed under the pulsewidth modulation supply are also presented.

Brushless structure is beneficial for air-core compensated pulsed alternator (ACPA) because its field current and rotation speed are too large for the slip rings and carbon brushes. To achieve the brushless structure, a cascaded brushless self-excited ACPA (CBSACPA), which consists of an exciter and a generator in cascade, is proposed, in this article. The exciter and generator have a common rotor. A novel squirrel-cage rotor winding (SCRW), which can eliminate the end winding compared with conventional wound rotor winding (WRW), is proposed to simplify the rotor structure and improve the performance. First, the structure of the CBSACPA with the SCRW is introduced. Second, the operation principles of the machine are elaborated. Third, the dynamic mathematical model is presented. Fourth, the operation principles are demonstrated by the finite-element method. In addition, the performance of the SCRW is compared with the WRW as well. Finally, a prototype of CBSACPA is developed and tested to validate the analyses and simulations. In conclusion, this study gives detailed introduction, analyses, and validation about the CBSACPA, which provides a new solution to achieve a brushless structure for the ACPA.

The article describes a method for active reduction of magnetic noise generated by a magnetic field that exists in the airgap of an induction motor. In this article a mathematical model of the process of magnetic noise excitation in a stators is presented. The model take into account that magnetic field waves, radial magnetic force waves (so-called Maxwell forces) and stator deformation waves (magnetic noise) are characterized by their own values of amplitude, mode number, frequency and phase shift. By comparing the equations for calculating the stator mechanical impedance, the amplitude of the radial magnetic force and the simplified magnetic noise equation, the relationships between these variables were established. The method of active reduction of magnetic noise proposed in the article is based on the use of these relationships. The novelty of the proposed method lies in the use of the filtered spectrum of output signal of the accelerometer installed on the stator to determine the most intense harmonics of the magnetic field in the motor airgap in order to further suppress them. The compensation signal generated by a special device adapts not only in frequency, but also in phase and amplitude of each vibration-disturbing harmonic.

Deep learning-based fault detection approach for squirrel cage induction motors (SCIMs) fault detection can provide a reliable solution to the industries. This paper encapsulates the idea of transfer learning-based knowledge transfer approach and deep convolutional neural network (dCNN) to develop a novel fault detection framework for multiple and simultaneous fault detection in SCIM. In comparison with the existing techniques, transfer learning-based deep CNN (TL-dCNN) method facilitates faster training and higher accuracy. The current signals acquired with the help of hall sensors and converted to an image for input to the TL-dCNN model. This approach provides autonomous learning of features and decision-making with minimum human intervention. The developed method is also compared to the existing state-of-the-art techniques, and it outperforms them and has an accuracy of 99.40%. The dataset for the TL-dCNN model is generated from the experimental setup and programming is done in python with the help of Keras and TensorFlow packages.

The rotor slot geometry of a squirrel cage induction motor plays the most important role in defining the torque-speed characteristic when the power supply is directly provided by the main grid. In this article it is shown how the rotor slot geometry can be optimised to satisfy different electromechanical requirements, depending on specific applications. This work, the second of two companion papers, briefly recalls the novel systematic approach, proposed in Part I, to perform the optimization of squirrel cage induction motors. Here, the optimization results achieved satisfying a wide spectrum of requirements are analysed in depth. Furthermore, the trade-off among the several performance indexes, and their correlation with the geometrical parameters is discussed. The possible advantages, and disadvantages of adopting a copper cage is also quantified for all possible performance requirements. The influence of the motor thermal behaviour, and harmonic losses on the overall performance are also discussed allowing to validate the proposed design optimization procedure, and its results. The outcomes of this work are opening to new design approaches that enable to optimise the performance of one of the most popular electrical machines adopted in industry, the squirrel cage induction motor.

Squirrel cage induction motor is the most widely adopted electrical machine in applications directly fed by the main grid. The analysis, design, and optimization of this machine topology has been addressed by a considerable amount of literature over the last century. Although its wide adoption, the induction motor design, especially when carried out in an automatic fashion, still presents significant challenges because the accurate prediction of the performance requires time-consuming finite element analysis. This work proposes a systematic approach to perform the design optimization of a squirrel cage induction motor focusing on the rotor slot geometry, being this the major player in defining the torque-speed characteristic. Structured as a two-parts companion papers, this first part presents an innovative performance evaluation methodology which allows a very fast estimation of the torque, and efficiency behaviour preserving the results’ accuracy. The proposed performance estimation technique is assessed against experimental tests carried out on an off-the-shelf induction motor. The selection of the performance indexes to be optimized is justified in detail along with the description of a generalized rotor parametrization which allows a comprehensive exploration of the research space. The presented optimization procedure is then applied to a case study, and the preliminary results are commented, highlighting benefits, and drawbacks of the proposed methodology.

Motor current signature analysis (MCSA) has been accepted in the field as a reliable means of detecting faults in the rotor cage of induction motors. However, there are many limitations to MCSA-based detection for other types of faults including rotor eccentricity and load defects. Recently, there has been increasing interest in airgap or leakage flux monitoring as an alternative to replace or complement MCSA. Flux monitoring can provide a reliable means of detecting rotor faults since anomalies in the rotor magnetomotive force or airgap can be directly observed. In this article, a new method based on monitoring the attenuation of rotor rotational frequency sidebands in the flux spectra is proposed for reliable detection and classification of rotor cage and eccentricity faults. It is also shown that flux monitoring can provide detection of rotor faults that is insensitive to the load defects. An experimental study under controlled broken bar, eccentricity, misalignment, and load unbalance conditions are given to support the claims. The results show that rotor cage, eccentricity, and load defects can be detected and distinguished for cases where MCSA alone is ineffective. A comparative evaluation between the proposed flux monitoring method and existing methods (MCSA, vibration analysis) is also given.

Early fault detection in squirrel cage induction motor (SCIM) can minimize the downtime and maximize production. This paper presents an adaptive gradient optimizer based deep convolutional neural network (ADG-dCNN) technique for bearing and rotor faults detection in squirrel cage induction motor. Multiple MEMS accelerometers have been used for vibration data collection, and sensor data fusion is employed in the model training and testing. ADG-dCNN allows the automatic feature extraction from the vibration data and minimizes the need for human expertise and reduces human intervention. It eliminates the error caused by manual feature extraction and selection, which is dependent on prior knowledge of fault types. This paper presents an end-to-end learning fault detection system based on deep CNN. The dataset for training and testing of the proposed method is generated from the test set-up. The proposed classifier attained an average accuracy of 99.70%. This paper also presents the recently developed SHapley Additive exPlanations (SHAP) methodology for evaluation of fault classification from the proposed model. The proposed technique can also be extended to other machinery with multiple sensors owing to its end-to-end learning abilities.

Interturn fault (ITF), a common fault type of induction motors, can impact the safe and stable operation of the motor. Variations of magnetic field distribution and short circuit (SC) current were analyzed, and a diagnosis method of ITF was proposed based on the stator current complex component. First, a 1.1 kW squirrel cage induction motor whose stator winding coils were rewound was taken as a prototype. The distributions of magnetic fields before and after the fault were obtained by calculating the finite element model. Based on the simulation and experimental results under no-load, light load, and rated load conditions, the phase current and SC loop current variations were obtained under different fault degrees. Then, the variations of current amplitudes in the faulty phase, nonfaulty phases, and SC loop were analyzed to determine the impact on the operation of the motor caused by the fault. Finally, a diagnosis method of ITF, which uses the current complex component to represent the current variation, was proposed based on the calculation and analysis of faulty-motor current. The results show that this method can diagnose and locate faults effectively, verify the robustness of load variations, and provide a reference for the research on ITF of induction motors.

Nowadays, finite element analysis represents the most accurate tool to analyse electrical machines. However, the time domain resolution of electromagnetic problem, in some cases, requires long simulation time due to the induced nature of the currents. The computational burden increases when the machine features a skewed layout on the stator or rotor structures, since this requires 2D multi-slices approximated analysis or even a full 3D model. In this paper, a general analytical method to model electromagnetic devices is applied to a squirrel cage induction motor featuring a skewed rotor structure. The modelling approach is wisely implemented and adapted to pursue a fair balance between accuracy of the analysis and computational burden, taking advantage of all the symmetries existing in the rotor cage of the machine, aiming to minimize the model complexity. A comparative analysis in term of the inductances between analytical and finite element is proposed. The results provided by the model developed are compared with respect to the corresponding values provided by both finite element and experimental test performed on the reference machine. Such comparisons show that the proposed model is actually able to achieve a pretty good balance between accuracy and computational efficiency.

In the supersynchronous mode of double-inverter-fed wound rotor induction machine (DI-WRIM) drive, torque ripple is dependent on the sum of the quadrature ( $q$ ) axis stator and rotor flux ripples (termed as overall flux ripple). Therefore, in the existing method, the torque ripple is reduced by merely changing the slope of one of the flux ripples such that their sum is reduced. However, the torque ripple can be further reduced, as the overall flux ripple in DI-WRIM resembles the $q$ -axis stator flux ripple of a double-inverter-fed open-end winding induction machine which is generally analyzed as a three-level neutral-point-clamped inverter fed squirrel cage induction machine (SQIM) (3L-SQIM) drive. Thus, in this article, the stator and rotor voltage source inverters are switched together and the resemblance is explored to develop stator–rotor pulsewidth modulation (PWM) combinations, such that the overall flux ripple is equivalent to the $q$ -axis flux ripple of 3L-SQIM. The effect of phase shift between the stator and rotor voltage vectors on torque ripple is analyzed and a hybrid PWM combination is also proposed to minimize the same. The reduction in torque ripple, with the proposed combinations, is validated in terms of the estimated instantaneous and RMS torque ripples. The simulation and experimental results further validate this reduction.

Three-phase line-start synchronous reluctance motor (LS-SynRM) is started by asynchronous torque generated by the rotor conductor bars, and runs synchronously by reluctance torque generated by the inductance difference. In this article, the rotor structure of an LS-SynRM is designed and optimized, based on the theory and characteristics of LS-SynRMs during starting and steady-state operation. First, the influence of the number of rotor flux barriers and the flux barriers ratio on the dq -axis inductance is simulated, and a better structure of rotor flux barriers is obtained. Second, according to the transient theory, a method of separating each torque during the starting process of LS-SynRMs is proposed, and the main reason for the poor starting ability of the initial LS-SynRM is analyzed. Based on the optimized structure of rotor flux barriers, the influence of the area and distribution of the rotor conductor bars on the starting ability of the LS-SynRM is studied, and the structure of rotor conductor bars under the condition of starting with heavy load (constant load) is determined. Finally, through the prototype test, the rated efficiency of the LS-SynRM is 2.8% higher than that of the SCIM is replaced by three phase squirrel cage induction motor (SCIM), which verifies the accuracy of the simulated results. At the same time, the starting current and the pull-in torque under a specific inertia are tested, and the improved effect of the synchronization ability of the improved LS-SynRM was verified.

Flux estimation of single winding induction machines (SWIMs) operating in a zero-speed region is challenging, since in this operation region, the voltage drop on the stator resistance value, which varies with the operating point, is not negligible. Furthermore, in this operation region, because of the interference between higher band frequencies of a dc-rejection filter with low-pass filter of the stator currents, the dc-offset of measured currents may distort the true values of the stator current. Dual stator winding induction machines (DSWIMs), which have two sets of three-phase windings with different number of pole pairs and adapt a standard squirrel cage rotor, have overcame the associated problems of SWIMs in the zero-speed region. Nevertheless, DWSIMs have lower power rating than SWIMs if they use the same stator and rotor frames. In this article, an optimal design procedure is proposed for DSWIMs, which benefits the advantages of DSWIMs and surmounts the rate reduction problem as much as possible. In this regard, the optimal flux levels ratio of winding sets and the best pole pair ratio are determined first. Afterward, the winding specifications are designated to have maximum output power, while the DSWIM advantages, especially the zero-speed region operation capability, remain valid. A DSWIM is designed, simulated in ANSYS/MAXWELL and fabricated based on the proposed method and utilizing commercially available standard stator and rotor frames. Experimental assessments verify that the DSWIM prototype has improved the rate-reduction problem up to 19% in comparison to similar proposed DSWIMs.

Two main features provided by electric motor manufacturers are power factor and efficiency. However, the values reported are often different from the measured values. Thus, this work presents the results obtained from testing 435 Three-phase Induction Electric Motors with Squirrel Cage Rotor from 38 different manufacturers tested between 2015 and 2016. The data were collected through standardized tests performed at the Laboratory of Electrical Machines of the Institute of Energy and Environment of the University of Sao Paulo. The values reported by the manufacturers were compared with the values measured in the laboratory. The results indicate that 58% of the values measured for the power factor of the motors were lower than those reported by the manufacturer. Similarly, 55% of the measured values for the performance were lower than the values reported by the manufacturer.

Single-phase, outer-rotor squirrel cage induction motors are widely used in ceiling fan applications. Furthermore, they can be employed for pumps, and in-wheel hub drives. In this article, an analytical model based on magnetic equivalent circuit is proposed to evaluate the performance of the motor. The influence of rotor slots’ skewing, stator end windings, slots’ leakage inductance, and core saturation are included in the model. Furthermore, the windings’ copper losses and the core's iron losses are calculated using the proposed model. The results of the presented model are compared with those of time variant finite element analysis (TVFEA) and experimental measurements close agreement between the results confirms the success of the proposed model from accuracy point of view. Furthermore, the computation time required for the proposed model considering the linear and nonlinear cores are 1 min and 11 min., respectively. However, those of TVFEA considering 64 000 mesh elements for linear and nonlinear cores are 21 h and 28 h, respectively.

The classical Direct Torque Control has been elaborated to achieve advanced performance of asynchronous motor, especially in speed behaviours. Due to its high level of ripples and variable frequency, several modifications have been proposed to improve it. In this paper, two modified strategies of the direct torque control dedicated to asynchronous motors are presented, the first method is based on the sinusoidal pulse width modulation and PI regulators for regulating torque, speed and stator flux. The second is based on sliding mode control where the principal purpose is to force the system’s trajectory to slide along the switching surface by a well-defined control law. Furthermore, this paper aims to design two observers; the first will be evaluated by the direct calculation method and the second will be formed by sliding mode. These observers can improve control performance while eliminating mechanical sensors and thereby increasing the overall system’s reliability.

In this article, we propose a single-vibration sensor-based method for detecting incipient faults in squirrel cage induction motors (SCIMs). We consider defects in different parts of the bearing (inner raceway, outer raceway, cage train, and rolling element) and in a single bar of the rotor. The vibration signal is dominated by the fundamental rotational frequency and its harmonics. The dominant components result in numerical errors while estimating the relatively indistinct fault-specific spectral components. In this article, we precondition the vibration signal by suppressing multiple dominant components using an extended Kalman filter-based method. The suppression of the dominant components reduces the spectral leakage, exposes minute fault components, and improves the overall amplitude estimation. Subsequently, we estimate the fault frequency and amplitude using an accurate and low-complexity Rayleigh-quotient-based spectral estimator. The thresholds for fault detection are determined from a small number of healthy data, and an adaptive minimum distance-based detector is used for hypothesis testing. The proposed test improves detection and reduces false alarms under noisy conditions. We test the complete algorithm using data from a 22-kW SCIM laboratory setup. The proposed method has achieved 100% accuracy with the publicly available 12-kHz drive-end bearing data from Case Western Reserve University, Cleveland, OH, USA.

In this study, the unique reverse-flow around the inlet nozzle of a squirrel-cage fan was numerically studied by computational fluid dynamics (CFD), and a non-axisymmetric D-type inlet nozzle was proposed to inhibit it. It is shown that serious back flow develops at the volute tongue when the fan operates at a low flow coefficient that is lower than the best efficiency point. The airflow passing the blade passages in reverse further crosses the impeller, mixing the clearance leakage airflow, and finally blows into the intake chamber near the circumferential position of $ 150^{\circ } $ . By installing the inlet nozzle along this direction, D-type inlet nozzle schemes with different blockage extent were calculated by CFD. The scheme with a cut distance of 70% of its exit-section radius was chosen as the best design by comprehensively comparing the back flow ratio and fan performance of different working conditions. CFD results illustrated that reverse blowing at the fan entrance was significantly constrained by this D-type inlet nozzle, and the vortex in the inlet chamber correspondingly disappeared. Experimental data illustrated that the new nozzle increased the fan pressure rise under low-flow conditions by about 6% and barely reduced performance at other working points.

The demand for electricity is growing very fast; as a result, the entire power sector is facing a real problem of meeting the additional demand. Rigorous energy audit suggests the replacement of energy-efficient devices from standard one, operating with poor efficiency and consumes large power. 3-phase induction motor is widely used as driving power in most of the industries and it consumes almost 65% of the total power. The energy-efficient design of such motors saves a considerable amount of energy and reduces the cost of operation. In this paper, an attempt has been made to design energy-efficient induction motor from different perspective of using design and optimization without high-quality material. In this paper, the cost of yearly energy losses is considered as objective function and it is optimized to save energy and money as well. The design problem is a nonlinear constraint optimization problem, which involves many variables and constraints. Water Cycle Algorithm (WCA) is one of the most recently developed metaheuristic algorithm is taken for the optimization for the case study of 5 HP and 10 HP, 3- phase, Squirrel cage induction motor. The objective function is optimized by WCA and Genetic Algorithm and their result is compared for accuracy from cost and performance point of view. WCA found to be the most efficient tool to optimize the problem and helps to design an energy-efficient motor.

LC filters are used in between a pulsewidth modulated three-phase voltage source inverter and a squirrel cage induction motor (SQIM) to reduce the losses in the motor and the high dv/dt at the motor terminals by feeding the motor with three-phase sinusoidal voltages. However, it affects the rotor-flux oriented control (RFOC) of the SQIM drive because of the sustained resonant frequency oscillations. It also destabilizes the drive at some operating points if proper control action is not taken. This article proposes a simple feedforward (FF) technique where the FF terms are subtracted from the d- and q- axis stator-current references to damp out the resonant frequency oscillations. Additional sensors and controllers are not required except the sensors and controllers used in RFOC of SQIM without filter. It does not depend on the tedious calculation of damping gain like in any active damping method. The stability of the drive has been analyzed and verified through simulation as well as experimental results at different test conditions. It ensures good steady-state and dynamic performances of the SQIM with filter. There is no need to change the parameters of four proportional–integral controllers previously designed for the RFOC of SQIM without filter.

The excellent specifications of the isolated squirrel cage self-excited induction generator (SEIG) make it the first choice for use with renewable energy sources. However, poor voltage and frequency regulation (under load and speed perturbations) are the main problems with isolated SEIGs. Wide dependence on the SEIG requires prior knowledge of its behaviour with regard to variations in the input of mechanical power and output of electrical power to develop a control system that is capable of maintaining the voltage and frequency at rated values, as far as possible, with any change in the input or output power of the SEIG. In this paper, a mathematical model of a wind energy conversion system (WECS) based on a squirrel cage SEIG with a generalized impedance control (GIC) was built using the Matlab/Simulink environment in a d-q stationary reference frame. A fuzzy logic controller (FLC) was used to control the parameters of the GIC. The training of the FLC was conducted by a neural network through Matlab's Neuro-Fuzzy designer. The results of this paper showed that the trained FLC succeeded in controlling the real and reactive power flow between the SEIG and the GIC system, in which the maximum variation for both magnitude and frequency of the generated voltage with any load or wind speed perturbation will not exceed (0.2%) for the frequency and (3%) for the voltage magnitude in both directions. The SEIG model was validated by comparing the results obtained with those of well-known studies with the same rating and operating conditions

This article presents the theoretical aspects of developing a control system for the processing of frozen raw meat by cutters in automatic mode. The method for analytical calculation of the productivity rate of meat cutting by a cutter with a screw tooth provides an accuracy for which relative error does not exceed 6%. The authors show automatic process control in minced meat production using a control system computer (CSC), with the aim of building an automatic control system (ACS) for chopping raw materials frozen in the form of blocks. The task of ACS synthesis was solved: the system structure and its elements were chosen, the topology of their cause-and-effect relationships and an algorithm of control devices were developed, and their parameters were determined. The ACS’s control loop scheme for raw material cutting speed was realized, where an assembly of devices was chosen as the object of management (OM): the squirrel cage induction motor (SCIM) of the cutting mechanism drive; the frequency converter (FC) of the supply voltage, which changes the rotation speed of the SCIM (the rotation speed of the milling cutter); and the milling cutter of the chopper. The shaping filter method was used, to predict the size of the meat chips produced, to modulate the perturbation acting on the system from the load side. Based on the single-stage chopping of raw meat, an automatic line is created for producing meat products, with a minced meat quality management system based on artificial intelligence on the principle of ‘unmanned technology’.

Detection of rotor cage faults in induction motors based on motor current signature analysis (MCSA) is being extensively applied in the field for preventing forced outage of the motor and industrial process. Although MCSA is very effective for detecting broken bars that are adjacent to each other, it can fail if the broken bars are nonadjacent, which is common for applications with frequent starts. If multiple broken bars are spread out at locations where the rotor “electrical” asymmetry is canceled, the presence of broken bars is difficult to detect with MCSA. A false indication can lead to a catastrophic-forced outage, but the only known means of detecting this type of fault in the field is through rotor visual inspection. In this article, the feasibility of detecting nonadjacent broken rotor bars from the rotor rotational frequency sideband components in the internal and external search coil measurements during steady state and motor starting is evaluated. Experimental testing on a 7.5-hp induction motor shows that nonadjacent broken bars can be reliably detected from the analysis of flux measurements for cases where MCSA and all other electrical tests fail.

This article presents a novel approach for detecting broken rotor bars in squirrel-cage induction motors, using a time-domain current analysis. More particularly, this solution proposes a new use of histogram of oriented gradients since this method is usually applied in computer vision and image processing applications. Fully broken rotor bars have been detected when the motor was running at a very low slip since this operational condition is very difficult to identify using the traditional motor-current signature analysis. In addition, only one phase of the stator current of the machine was applied to extract the intensity gradients and edge directions of each current time window, for both healthy and damaged rotors. It is important to highlight that the present method does not require the slip measurement for fault detection, as demand for other techniques and often related to false negative indications. The features extracted from the histograms have been applied as inputs for a neural network classifier. This method has been validated using some experimental data from a 7.5-kW squirrel-cage induction machine running at distinct load levels (slip conditions) and also for oscillatory loads.

This paper presents an efficient technique for early diagnosis of simultaneous faults in different phases of stator winding of a three-phase induction motor due to turn-to-turn short circuit. A rea...

The model of an engine has been constructed assuming that the rotor “squirrel cage” is replaced by the closed frames formed by its opposite rods. The method of engine control is proposed ensuring its operation in the closed system of rotation speed regulation with constant frequency of rotor currents corresponding to the torque extremum.

This study presents the modelling and simulation of a squirrel cage induction motor using a modified winding function-based method. The aim of the model is to compute the motor's performance parameters, which are similar to the results obtained using the finite element method (FEM) with a considerably reduced simulation time. This fact can make this model good for iterations based optimisation and fault diagnostic algorithms. For this purpose, the actual stator and rotor winding functions and the air gap, with the inclusion of rotor and stator slots, are defined as conditional expressions. The resistances and various inductances are calculated with stepping rotor, saved in lookup tables and are used to calculate speed, torque, and currents of the motor. For the validation of the model, the frequency spectrum of stator current is compared with the one calculated using FEM and measurements taken in the laboratory setup under healthy and broken rotor bar conditions.

Dual stator winding induction machines (DSWIMs), which have two sets of three-phase windings with unequal pole pairs in their stator and a standard squirrel cage rotor, have overcame the narrow speed operation region and circulating current problems exists in other types of dual winding machines. These advantages are resulted from the independent operation of their winding sets. The independent operation of winding sets will be guaranteed if the flux saturation is avoided. This letter proposes a novel reference frame angle determination technique that not only guarantees the flux saturation avoidance but also results in flux optimization in DSWIMs. Despite pervious methods, the proposed method does not require position or speed sensor and it is easily applicable in various control schemes and in different reference frames. This method is implemented in a flux and torque vector control system for driving a 3.3 kW DSWIM. The experimental results confirm the effectiveness of the proposed method. Moreover, by implementing the proposed method, the torque sharing between the two winding sets is properly done according to the power rating of each of them.

The active–reactive induction motor (ARIM) has been introduced in the literature as a low-cost and high-efficiency alternative to the synchronous motor in load commutated inverter (LCI) fed drives. ARIM is a squirrel cage machine with two sets of dissimilar three-phase stator windings. While one winding is rated for high voltage and power, the other winding is rated for a lower voltage and power. The low-voltage winding fed from a voltage source inverter (VSI) supplies only reactive power to the machine such that a leading power factor appears at the high-voltage terminals, enabling LCI-fed operation at this winding. Since the ARIM is fundamentally an induction motor, the conventional induction machine design process is applicable. However, due to the nonconventional arrangement of stator windings and being intended specifically for an LCI-fed topology, this new class of induction machines requires some critical design considerations. It is shown in this article that the leakage inductances play a pivotal role in determining the ratings of the low-voltage windings and the VSI. Therefore, an iterative design procedure to obtain the correct ratings for the flux winding and the low-voltage components is proposed. It is also required to know the correct value of the leakage inductance in order to design the control loops for reliable operation. This article proposes experimental methods to determine these leakage inductances. The proposed methods are validated by designing a 3.3-kV, 75-kW prototype and experimental results are presented.

Schering bridge network can be used to measure the loss angle of an insulating material of electrical machines and its winding capacitance. But, this type of bridge measurement technique suffers from error due to the effect of stray capacitances in both between the bridge output nodal points and also between bridge output nodal points and the ground. These errors can be minimized by using the Wagner earth technique. The limitation of this method is the repetition of bridge balance and Wagner earth balance that is required in every observation. In this paper, a modified Schering bridge network has been developed using operational-amplifier (op-amp) to minimize the stray capacitances. A potentiometer has been used to adjust the sensitivity of the bridge. The experiment has been performed on a 3.3-kV, 130-kW, three-phase squirrel cage induction motor in a process plant. An additional electronic measurement circuit has been incorporated to measure the dissipation factor tan $({\delta)}$ directly in terms of voltage ratio. For a particular value of the bridge sensitivity factor, the change of dissipation factor with the variation of voltage at line frequency has been observed and found satisfactory.