The paper recapitulates recently conducted investigations of non-proportional Luenberger observers, applied to reconstruction of state variables of induction motors. Three structures of non-proportional observers are analyzed, a proportional-integral observer, modified integral observer and observer with integrators. Criteria for gain selection of the observer are described, classical ones based on poles, as well as additional, increasing observer’s robustness. Fulfilment of the presented criteria can be ensured with the three proposed methods for gain selection, two analytical, based on dyadic transformation and one based on optimization.

A new observer of induction motor state variables is proposed in the paper. A nonlinearity of the main magnetic path is expressed as a function of a properly chosen parameter versus the position vector length. The value of the mutual inductance received n the identification algorithm is calculated exploiting the estimated values of the state variables. The coefficients appearing in the differential equations of the observer system are modified in each step of the algorithm on the basis of the calculated mutual inductance. The analysis of convergence of the identification algorithm is shown in this paper.

In this paper, an analysis of the induction motor control scheme based on the Direct Rotor Flux Oriented Control (DRFOC) for a whole speed range, including fieldweakening (FW) regions is presented. Two field-weakening algorithms have been compared and verified through simulation with a 3.0 [kW] induction motor drive.

Contemporary sensorless AC drives require the use of electromechanical quantities estimation. The skin effect occurring in AC machines with solid secondary or with solid secondary elements causes machines of this type to be represented by equivalent circuits containing distributed elements, which makes the analysis of machine electrodynamic states more complicated and hinders the construction of relatively simple and effective estimators of electromechanical quantities. The variability of rotor parameters is modelled, with a good approximation, by the machine secondary multi-loop equivalent circuit with lumped elements. In this paper the construction procedure of electromechanical state variable estimators basing on this type of equivalent circuit will be presented. The simulation investigations of the created electromechanical quantities estimators, performed for the selected states of solid iron rotor AC machine operation will be shown as well.

Disk motors are characterized by the axial direction of main magnetic flux and the variable length of the magnetic flux path along varying stator/rotor radii. This is why it is generally accepted that reliable electromagnetic calculations for such machines should be carried out using the FEM for 3D models. The 3D approach makes it possible to take into account an entire spectrum of different effects. Such computational analysis is very time-consuming, this is in particular true for machines with one magnetic axis only. An alternate computational method based on a 2D FEM model of a cylindrical motor is proposed in the paper. The obtained calculation results have been verified by means of lab test results for a physical model. The proposed method leads to a significant decrease of computational time, i.e. the decrease of iterative search for the most advantageous design.

Three phase induction motors are widely used in industrial processes and condition monitoring of these motors is especially important. Broken rotor bars, eccentricity and bearing faults are the most common types of faults of induction motors. Stator current and/or vibration signals are mostly preferred for the monitoring and detection of these faults. Fourier Transform (FT) based detection methods analyse the characteristic harmonic components of stator current and vibration signals for feature extraction. Several types of simultaneous faults of induction motors may produce characteristic harmonic components at the same frequency (with varying amplitudes). Therefore, detection of multiple faults is more difficult than detection of a single fault with FT based diagnosis methods. This paper proposes an alternative approach to detect simultaneous multiple faults including broken rotor bars, static eccentricity and outer/inner-race bearing faults by analysing stator current and vibration signals. The proposed method uses Hilbert envelope analysis with a Normalized Least Mean Square (NLSM) adaptive filter. The results are experimentally verified under 25%, 50%, 75%, 100% load conditions.

Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications.

A fault diagnostics system of three-phase induction motors was implemented. The implemented system was based on acoustic signals of three-phase induction motors. A feature extraction step was performed using SMOFS-20-EXPANDED (shortened method of frequencies selection-20-Expanded). A classification step was performed using 3 classifiers: LDA (Linear Discriminant Analysis), NBC (Naive Bayes Classifier), CT (Classification Tree). An analysis was carried out for incipient states of three-phase induction motors measured under laboratory conditions. The author measured and analysed the following states of motors: healthy motor, motor with one faulty rotor bar, motor with two faulty rotor bars, motor with faulty ring of squirrel-cage. Measured and analysed states were caused by natural degradation of parts of the machine. The efficiency of recognition of the analysed states was good. The proposed method of fault diagnostics can find application in protection of three-phase induction motors.

The paper describes high output induction motors driving large applications of heavy starting conditions. Heavy start is characterised by long accelerating time and occures in drives of hudge inertia torque, esspecially when performed at full load. The reliable operation of the motors depends on proper design and quality of rotor's cage. The aspects of thermal behaviour and electrodynamic forces have to be considered during the design of the motor for hard working conditions. In the paper the rotor with idle bars is investigated.

The article introduced some expressions for self- and mutual slot leakage inductance of phase windings for the mathematical model of an induction machine in the natural phase coordinate system and for dq0 model and in an arbitrary coordinate frame. Calculation of self- and mutual slot leakage inductance have been performed for threephase double-layer, delta and delta-modified winding connections. Introduced expressions may be useful in the design of windings and in the analysis of dynamic states of AC electrical machines.

The purpose of the paper is the investigation of possibility of utilization of a single-phase induction machine, designed and normally operating as a single-phase capacitor induction motor, as a self-excited single-phase induction generator, which can be used to generate electrical energy from non-conventional energy sources. The paper presents dq model of the self-excited single-phase induction generator for dynamic characteristics simulation and steady-state model based on double revolving field theory with two phase symmetrical components – a forward and backward revolving field for performance of the generator under resistive load. Excitation and load characteristics obtained by simulation showed considerable influence of method of capacitor configuration in the load stator winding on terminal voltage, current and output power of the generator under load. An specific construction of the stator windings together with capacitor requirements to obtain nominal output power at desired self-regulating terminal voltage over the operating range will be the aim of further research.

In this paper a comparison of numerically determined and measured electromagnetically exited noise of an induction motor is presented. The calculations are accomplished using FEM for an example motor, which is a 290 kW inverter-fed asynchronous machine. The approach starts with the electromagnetic and mechanical consideration. The focus is set on acoustic considerations, which contain the 3D-FE-model and measurement setup in the sound chamber.

This paper deals with detection of the stator windings shorted turns in an induction motor drive working under open (scalar) and closed loop (Direct Field Oriented DFO) control structures. In order to detect the early stage of stator winding fault, the analysis of symmetrical and principal components of stator voltages and currents is used. Experimental results obtained from a specially prepared induction motor are presented.

This paper describes a fault-tolerant controller (FTC) of induction motor (IM) with inter-turn short circuit in stator phase winding. The fault-tolerant controller is based on the indirect rotor field oriented control (IRFOC) and an observer to estimate the motor states, the amount of turns involved in short circuit and the current in the short circuit. The proposed fault controller switches between the control of the two components of measured stator current in the synchronously rotating reference frame and the control of the two components of estimated current in the case of faulty condition when the estimated current in the short circuit is not destructive of motor winding. This technique is used to eliminate the speed and the rotor flux harmonics and to assure the decoupling between the rotor flux and torque controls. The results of the simulation for controlling the speed and rotor flux of the IM demonstrate the applicability of the proposed FTC.

The efficiency of the solid-rotor induction machines depends on axial length of rotor (including the end-regions). Determination of the best axial length is problematic because of current density distribution in the end-regions and also because of absence of dedicated methods and models. This work proposes a method that circumvents this difficulty. It is based on the numerical determination of a dimensionless rotor-end factor using a combination of three- and two-dimensional finite element models restricted to the motor rotor. Such the end factor can be used in both analytical and numerical model of the machine in order to determine the typical performance characteristics. In this work, using this method, we determined an optimal length of the slitted solid rotor of a motor operating at 12 000 rpm, that maximizes the motor efficiency. The results of computations and measurements, carried out on the laboratory test-stand, are presented.

The pole phase modulation (PPM) technique is an effective method to extend speed range and torque capabilities for an integrated starter and hybrid electric vehicles applications. In this paper, the five pole-phase combination types of a multiphase induction motor (IM) with 36 stator slots and 36 stator conductors are presented and compared quantitatively by using the time-stepping finite element method (TS-FEM). The 36 stator conductors of the proposed multiphase IM are fed by a 36 leg inverter and the current phase angle and amplitude of each stator conductor can be controlled independently. This paper focuses on the winding connection, the PPM technique and the performance comparative analysis of each pole-phase combination types of the proposed multiphase IM. The flux distribution, air-gap flux density, output torque, core losses and efficiency of five pole-phase combination types have been investigated.

This paper investigates the application of a novel Model Predictive Control structure for the drive system with an induction motor. The proposed controller has a cascade-free structure that consists of a vector of electromagnetics (torque, flux) and mechanical (speed) states of the system. The long-horizon version of the MPC is investigated in the paper. In order to reduce the computational complexity of the algorithm, an explicit version is applied. The influence of different factors (length of the control and predictive horizon, values of weights) on the performance of the drive system is investigated. The effectiveness of the proposed approach is validated by some experimental tests.

This paper deals with the modelling of traction linear induction motors (LIMs) for public transportation. The magnetic end effect inherent to these motors causes an asymmetry of their phase impedances. Thus, if the LIM is supplied from the three-phase symmetrical voltage, its phase currents become asymmetric. This effect must be taken into consideration when simulating the LIMs’ performance. Otherwise, when the motor phase currents are assumed to be symmetric in the simulation, the simulation results are in error. This paper investigates the LIM performance, considering the end-effect induced asymmetry of the phase currents, and presents a comparative study of the LIM performance characteristics in both the voltage and the current mode.

The presence of an open-circuit fault subjects a three-phase induction motor to severely unbalanced voltages that may damage the stator windings consecutively causing total shutdown of systems. Unplanned downtime is very costly. Therefore, fault diagnosis is essential for making a predictive plan for maintenance and saving the required time and cost. This paper presents a model-based diagnosis technique for diagnosing an open-circuit fault in any phase of a three-phase induction motor. The proposed strategy requires only current signals from the faulty machine to compare them with the healthy currents from an induction motor model. Then the errors of comparison are used as an objective function for a genetic algorithm that estimates the parameters of a healthy model, which they employed to identify and localize the fault. The simulation results illustrate the behaviours of basic parameters (stator and rotor resistances, self-inductances, and mutual inductance) and the number of stator winding turn parameters with respect to the location of an open-circuit fault. The results confirm that the number of stator winding turns are the useful parameters and can be utilized as an identifier for an open-circuit fault. The originality of this work is in extracting fault diagnosis features from the variations of the number of stator winding turns.

Accurate information on Induction Motor (IM) speed is essential for robust operation of vector controlled IM drives. Simultaneous estimation of speed provides redundancy in motor drives and enables their operation in case of a speed sensor failure. Furthermore, speed estimation can replace its direct measurement for low-cost IM drives or drives operated in difficult environmental conditions. During torque transients when slip frequency is not controlled within the set range of values, the rotor electromagnetic time constant varies due to the rotor deep-bar effect. The model-based schemes for IM speed estimation are inherently more or less sensitive to variability of IM electromagnetic parameters. This paper presents the study on robustness improvement of the Model Reference Adaptive System (MRAS) based speed estimator to variability of IM electromagnetic parameters resulting from the rotor deep-bar effect. The proposed modification of the MRAS-based speed estimator builds on the use of the rotor flux voltage-current model as the adjustable model. The verification of the analyzed configurations of the MRAS-based speed estimator was performed in the slip frequency range corresponding to the IM load adjustment range up to 1.30 of the stator rated current. This was done for a rigorous and reliable assessment of estimators’ robustness to rotor electromagnetic parameter variability resulting from the rotor deep-bar effect. The theoretical reasoning is supported by the results of experimental tests which confirm the improved operation accuracy and reliability of the proposed speed estimator configuration under the considered working conditions in comparison to the classical MRAS-based speed estimator.

Vibration analysis for conditional preventive maintenance is an essential tool for the industry. The vibration signals sensored, collected and analyzed can provide information about the state of an induction motor. Appropriate processing of these vibratory signals leads to define a normal or abnormal state of the whole rotating machinery, or in particular, one of its components. The main objective of this paper is to propose a method for automatic monitoring of bearing components condition of an induction motor. The proposed method is based on two approaches with one based on signal processing using the Hilbert spectral envelope and the other approach uses machine learning based on random forests. The Hilbert spectral envelope allows the extraction of frequency characteristics that are considered as new features entering the classifier. The frequencies chosen as features are determined from a proportional variation of their amplitudes with the variation of the load torque and the fault diameter. Furthermore, a random forest-based classifier can validate the effectiveness of extracted frequency characteristics as novel features to deal with bearing fault detection while automatically locating the faulty component with a classification rate of 99.94%. The results obtained with the proposed method have been validated experimentally using a test rig.

The paper presents a sensorless control approach for a five-phase induction motor drive with third harmonic injection and inverter output filter. In the case of the third harmonic injection being utilised in the control, the physical machine has to be divided into two virtual machines that are controlled separately and independently. The control system structure is presented in conjunction with speed and rotor flux observers that are required for a speed sensorless implementation of the drive. The last section is dedicated to experimental results of the drive system in sensorless operation, and the uninterrupted drive operation for two open-phase faults

In industrial drive systems, one of the widest group of machines are induction motors. During normal operation, these machines are exposed to various types of damages, resulting in high economic losses. Electrical circuits damages are more than half of all damages appearing in induction motors. In connection with the above, the task of early detection of machine defects becomes a priority in modern drive systems. The article presents the possibility of using deep neural networks to detect stator and rotor damages. The opportunity of detecting shorted turns and the broken rotor bars with the use of an axial flux signal is presented.

This article considers the problem of the rise in temperature of the windings of an induction motor during start-up. Excessive growth of thermal stresses in the structure of a cage winding increases the probability of damage to the winding of the rotor. For the purpose of analysis of the problem, simplified mathematical relationships are given, enabling the comparison of quantities of energy released in a rotor winding during start-up by different methods. Also, laboratory tests were carried out on a specially adapted cage induction motor enabling measurement of the temperature of a rotor winding during its operation. Because there was no possibility of investigating motors in medium- and high-power drive systems, the authors decided to carry out tests on a low-power motor. The study concerned the start-up of a drive system with a 4 kW cage induction motor. Changes in the winding temperature were recorded for three cases: direct online start-up, soft starting, and the use of a variable-frequency drive (VFD). Conclusions were drawn based on the results obtained. In high-power motors, the observed phenomena occur with greater intensity, because of the use of deep bar and double cage rotors. For this reason, indication is made of the particular need for research into the energy aspects of different start-up methods for medium- and high-power cage induction motors in conditions of prolonged start-up.