The exact nature of thermal processes occurring in an electric motor is often unknown. Thus, the estimation of temperature rise using mathematical models and computational experiments is becoming increasingly important. Thermal analysis is the key design aspect, which has become significant in the design process for electric motors. The thermal analysis of electric motors can be helpful in developing effective thermal monitoring methods. This analysis is crucial for a better understanding of the overall performance and failure prevention for these electrical motors. In this paper, laboratory investigations of thermal processes in low-voltage asynchronous motors are described. The analysis of the results leads to the conclusion that the classic single-exponential models do not match the dynamically changing thermal processes in electric motors especially in the case of intermittent motor operation.

Most of the fault wave localization methods are based on the analysis of line current transformed by current transformers and are limited to high voltage grids. Fault wave localization in medium voltage grids is still being developed. This paper presents a new real-time algorithm for the identification of travelling waves in a distribution grid using voltage signal and the short-time matrix pencil method. To obtain the secondary side voltage waveforms at substation, the model of a resistive voltage sensor based on the broadband measurements from 10 Hz to 20 MHz was developed. The tested sensor amplifies the frequencies associated with travelling waves more than utility frequency allowing for the identification. Short-circuit simulations on the IEEE 34-bus feeder was performed to test the algorithm. The developed method can detect even the waves of low amplitude.

The main objective of the research described in the article was to determine the following: Is it possible to estimate the magnetic flux linkage in the core of a voltage transformer using analogue or digital methods? Will it be possible to estimate it approximately both in the normal state and in the state of deep core saturation (ferroresonant state)? The research aimed to identify the advantages and disadvantages of both proposed estimation methods. As part of the research described in this paper, a simulation model was developed and executed in the MATLAB/Simulink environment to generate a series of secondary voltage and flux waveforms in voltage transformers. The secondary voltage and flux waveforms were modelled under ground fault conditions, initiating ferroresonance oscillations in the medium-voltage network. To determine the associated flux from the simulated secondary voltages of the voltage transformers, an analogue integration circuit, a voltage analogue input circuit and a numerical integration algorithm with offset elimination were developed and implemented in an STM32 microcontroller. The obtained reference flux waveforms were used to verify the accuracy of the estimation of flux waveforms obtained using the analogue and digital methods. As a result, it was determined that both methods allow for a relatively accurate estimation of the periodic component of the magnetic flux. It also presented how both methods respond to the presence of slowly changing (aperiodic) components. Possible applications were proposed in order to create an innovative criterion for detecting ferroresonance oscillations.