This paper analyses symmetrical and unsymmetrical voltage sag effects on the torque and speed deviation in direct torque controlled (DTC) induction motors (IMs) for adjustable speed drives (ASDs). The capability of an ASD for continuous normal operation in case of short supply disturbances is essential for high performance drives. In this paper, an updated scheme is proposed for boosting ASD performances during supply disturbances with voltage reduction. Flux weakening is an effective method to overcome the torque-decreasing problem in case of DC-link voltage diminishing. It is also shown that speed reduction is an efficient procedure to obtain the voltage sag insensitivity of an ASD, which is appropriate for the existing industrial applications. Extensive laboratory testing has been conducted to verify the performances and effectiveness of the proposed control algorithm. The suggested method requires only a modification of converter control software or operating speed change without any additional hardware components. Extended tests under various voltage sags events were carried out on a 1.5 kW laboratory drive, and the obtained results have been compared with an industrial DTC drive.

The task of the whole microgrid state-space matrix creation is usually done in a preferred textual programming language, and it presents a complicated, time-consuming, and error-prone job for a researcher without good coding practices. To ease the modeling task, contribute to the adaptation of new microgrid structures, control algorithms, and devices, and to improve the flexibility of the model, a graphical element building block method is proposed in this paper. With the proposed approach model creation of the whole microgrid is reduced to the creation of the individual element state-space model that is linked with other elements in a logical way with a graphical connection. Elements are then grouped into meaningful wholes and encapsulated with the appropriate graphical user interface that enables easy parameter modification and model complexity change. More detailed DC/DC and DC/AC models of converters than those in the literature concerning microgrid stability are presented in this paper. Those converters are incorporated in a microgrid, whose model is created using the proposed approach in MATLAB/Simulink. The dynamic response examination of the model remains easy, just as with all Simulink models, while for the linear system analysis, a specialized toolbox is used.

This paper proposes the enhancement of a synchronous reference frame phase-locked loop in terms of its dynamic response and disturbance rejection capability. The improvements were undertaken in order to upgrade the converter grid support capability required by modern grid codes during grid faults. The proposed repetitive control-based filter is inserted in the loop filter structure of the phase-locked loop. For the initially proposed structure, the necessity of the phase angle error correction term was derived and added at the output of the loop filter. On a set of tests that included (i) phase jump; (ii) voltage sag; (iii) voltage harmonics; (iv) DC offset; (v) random noise and; (vi) frequency change, the synchronization algorithm with the proposed modification showed two desirable characteristics: (i) a high attenuation of oscillations on specific frequencies; and (ii) the instant compensation of the portion of the phase angle jump. Along with the benefits, drawbacks of the proposed synchronization method were noted, the most important being the high dependency of the oscillation attenuation capability on the fundamental frequency drift and susceptibility to high-frequency noise. With the proposed modification, the synchronization algorithm manages to achieve a phase angle settling time not longer than one fundamental frequency period in all of the conducted tests.

This paper presents a novel, non-invasive methodology for creating a high-fidelity digital twin using only steady-state operational data. The proposed approach employs a fourstep workflow with two-stage parameter identification algorithm. First, a grid-based sensitivity analysis is conducted to establish robust and constrained search boundaries. Subsequently, a genetic algorithm performs a precise search within these boundaries to identify the final T-equivalent circuit parameters. The methodology was validated on a 1.5 kW induction motor. All but core loss identified parameters demonstrated similarity with those obtained from standard offline tests, and the resulting digital twin accurately reproduced the machine?s behaviour when compared to experimental measurements.

In this paper, experimental verification of the numerical optimization method two-stage PSO algorithm (TSPSO) for parameter identification of a cage induction motor using nominal motor data related to direct grid supply was performed. The TSPSO algorithm consists of two stages: the first stage estimates parameters for the rated operating mode, while the second stage estimates rotor parameters during motor startup. The TSPSO algorithm indirectly applies an approximation of the rotor parameter change as a function of speed to consider the influence of the skin effect at motor start-up and achieves the connection between the two stages. For the proper operation of control algorithms in frequency converters, knowledge of the parameters of the induction motor is necessary. Regulated electric drives use induction motors and frequency converters from various manufacturers. For this reason, different procedures for motor parameter identification are applied, which are integrated into the frequency converters. In this study, an experimental method was used for parameter identification of the cage induction motor based on the application of an offline procedure in a frequency converter for the identification of parameters of the cage induction motor in a standstill state. In this paper, independent parameter identification of the cage induction motor with the same nominal data was performed using two different methods. The results obtained show a certain level of agreement in the parameter values of the equivalent circuit, thereby experimentally verifying the numerical TSPSO algorithm.

The accurate estimation of speed in three-phase induction motors is crucial for their efficient control, operation or diagnostics. Traditional methods often rely on tachometers or encoders, which can be expensive and prone to mechanical wear and tear and can present overkill for applications where knowledge of only the static speed point is of interest. This paper explores an innovative, non-intrusive technique for estimating the speed of three-phase induction motors using sound analysis. By capturing and analyzing the acoustic signals emitted by the motor during operation, it is possible to extract characteristic frequencies corresponding to the rotational speed. Experimental results demonstrate the viability of this method, showing a high correlation between the estimated speed from sound analysis and the actual motor speed measured using conventional methods. This approach offers a cost-effective, reliable, maintenance-free and highly mobile alternative for speed estimation in industrial and educational applications, contributing to the advancement of smart motor control systems. This method is suitable for good estimation of static speed points during laboratory exercises where static characteristics are of interest.