This paper presents a detailed investigation into the application of transient Fourier analysis in select electrical engineering contexts. Two novel approaches for addressing transient analysis are introduced. The first approach combines the Fourier series with the Laplace–Carson ($\mathcal{L}\text{-}C$) transform in the complex domain, utilizing complex time vectors to streamline the computation of the original function. The inverse transformation back into the time domain is achieved using the Cauchy-Heaviside ($C\text{-}\mathcal{H}$) method. The second approach applies the Fourier transform ($\mathcal{F}\text{-}{\rm T}$) for the transient analysis of a power converter circuit with both passive and active loads. The method of complex conjugate amplitudes is employed for steady-state analysis. Both contributions represent innovative approaches within this study. The process begins with Fourier series expansions and the computation of Fourier coefficients, followed by solving the system’s steady-state and transient responses. The transient states are then confirmed using the Fourier transform. To validate these findings, the analytical results are verified through simulations conducted in the Matlab/Simulink R2023b environment.

This paper presents a comparative analysis of distribution transformers with varying power ratings and insulation conditions using Frequency Domain Spectroscopy (FDS). The investigation was conducted both by comparing transformers with different performance ratings (from 100 to 1000 kVA) and insulation quality at a constant ambient temperature, and by evaluating insulation properties of a transformer across varying temperatures. The FDS method allows for separate assessments of oil quality and moisture content in solid insulation. An advantage of using capacitance measured by FDS for insulation assessment is its relatively lower sensitivity to temperature variations compared to the loss factor, a finding confirmed by temperature-effect analyses. However, assessing transformer insulation via capacitance measurements is influenced by the insulation’s geometric configuration, which depends on the transformer type and power rating. Therefore, when comparing the quality of insulating parts of transformers with different powers, it is recommended to compare the capacitance ratio depending on low frequencies against the capacitance at 50 Hz.

This paper deals with the control of current phase advancing in single-leg voltage source inverters (VSI) and matrix converters with a two-phase output. The phase shift of the current in the auxiliary phase is set with the use of switched capacitors. Two distinctive control methods are used for the current phase advancing, open-loop control and closed-loop control. In addition, a new averaging method is derived for the calculation of the switched capacitance used in the open-loop control. The practical use of the designed control methods with the switched capacitor is shown in simulations and experimental verifications on a single-leg matrix converter with a passive and active load (induction motor).

This scientific paper presents a novel modified non-approximative method for instantaneously calculating state variables in a compact form. The method provides a direct solution in the discrete time domain, allowing for the specification of state variable values at any discrete time instant without requiring knowledge of previous variable values. This approach is useful for estimating voltage and current stresses of semiconductor elements and circulating energy within power electronic circuits, which is crucial for the correct design and operation of such systems. The paper utilized the z-transform with a long repetitive period to accelerate the calculation time and applies a method to solve the Steinmetz circuit using Matlab. The paper includes detailed simulations and a comparison of time consumption using both Euler implicit and the proposed direct non-approximative methods. Theoretical and simulation results were validated using Matlab/Simulink circuit simulator, demonstrating the effectiveness and efficiency of the proposed method.

This article presents a neural network-based control method for maintaining the required output voltage of a synchronous buck converter. The goal was to replace a traditional PID controller with a neural network that calculates the duty cycle based on real-time data. Several versions of the neural network were tested. The final version, which included the input voltage, reference, and output current as inputs and compensated for dead time, was successfully validated on real hardware. It was able to respond to changes in load and input voltage within a limited operating range.