Technology and design in electronic equipment

Distribution of eddy electric currents in an anisotropic electrically conductive transformer

Anatoly Ashcheulov — 2025-12-30

This paper investigates the formation and spatial distribution of eddy electric currents (EEC) within the structure of an anisotropic electrically conductive transformer (AECT), which represents a promising functional component for modern infocommunication systems. The research is based on a mathematical formulation that accounts for the tensor nature of the material’s electrical conductivity and the dependence of current distribution on the anisotropy coefficient K and the rotation angle of the crystallographic axes relative to the laboratory coordinate system γ.

A differential-form equation describing the behavior of eddy currents in a rectangular plate composed of an anisotropic material has been derived. It is shown that this equation exhibits an elliptic character, which significantly influences both the configuration and density of the eddy current distribution. Numerical modeling of current patterns has been performed, followed by visualization in the form of vector field maps for various values of K and angles γ.

Analysis of the simulation results reveals that the anisotropy coefficient governs the geometry of the eddy current loops: for K > 1, the elongation of the elliptical contours occurs along the axis with higher conductivity, while for K < 1, it occurs along the orthogonal axis. The angle γ determines the orientation of the principal axes within the laboratory plane and, consequently, the direction of elongation of the eddy structures. Meanwhile, the rotation direction of the eddy electric currents (CW/CCW) remains constant and is determined by the polarity of the applied voltage.

The practical significance of this study lies in establishing the relationship between anisotropy parameters and thermal losses within the transformer’s volume. It has been found that at higher K values, local losses decrease due to a more uniform current distribution along the major axis, whereas for 0 < K < 1, a more concentrated distribution is formed with intense local heating zones. These findings enable consideration of the anisotropic electrically conductive transformers operational characteristics in the design of telecommunication system components, particularly in power supply and coupling units.

Thus, this work presents, for the first time, a Laplacian-type equation for the distribution of eddy electric currents that incorporates material anisotropy, provides its classification, and demonstrates numerical implementation. The obtained results are of both scientific and practical interest for the development of new high-efficiency components in infocommunication technologies.

Film heterojunction with nanocluster subsystem for new type of photocells

Volodymyr Kovalchuk — 2025-12-30

The paper describes the manufacturing technology and presents the results of studies of a pCu₂S–nSi heterojunction (HJ) and an HJ based on it, containing a nanocluster (NC) subsystem. It is shown that the presence of an NC subsystem at the interface between the p-type Cu₂S film and the n-type Si substrate significantly increases the overall sensitivity of the samples under high illumination conditions. The operating mode of such an HJ as a highly sensitive valve photocell has been determined. It has also been demonstrated that these transitions are photoelectrically active in different spectral regions. The observed effects are extensive in nature, being largely determined by the geometry and morphology of the nanocluster centers rather than by the type of atoms from which they are formed.

Development of a mathematical model for a CdS-based photosensitive Hall sensor

Viktor Sergiichuk — 2025-12-30

The paper proposes a mathematical model of a photosensitive Hall sensor based on a CdS single crystal which uses the internal photoelectric effect. The model describes the change in the concentration and mobility of charge carriers under the influence of irradiation and allows us to estimate the increase in the sensitivity of the sensor to a magnetic field. The mathematical model accurately describes the increase in Hall voltage when the sensor current exceeds 40 mA (error margin of less than 5%). Experiments showed a 2.8-fold increase in sensor sensitivity in the low-current sensor mode, which is partially explained by noise and additional effects in the crystal. The authors propose the materials and sensor topology that will maximize Hall voltage to obtain maximum sensor sensitivity. The comparison of theoretical results and experimental data confirmed a twofold increase in the Hall voltage under illumination. The developed approach can be used to optimize planar sensors in systems that require high accuracy and energy efficiency.

Detector of asynchronous pulse noise in conditions of additive mixture of uncorrelated and discrete in range correlated gaussian noise

Igor Tsevukh — 2025-12-30

One of the main requirements for radio engineering systems is their ability to withstand high levels of noise in complex, changing and a priori unknown noise environments. Improving the noise immunity of radar systems and the means of radio electronic warfare requires the development of effective noise protection systems with high information content that can operate in the presence of complex, heterogeneous interference. To identify a range-resolution element affected by non-synchronous pulsed noise, an algorithm for detecting pulsed noise has been developed. The algorithm can function effectively in conditions involving an additive mixture of uncorrelated and powerful, discrete in range correlated noise in the presence of restrictions on the dynamic range of the receiving path of the radar system. A structural diagram of a pulsed noise detector has been developed, which additionally includes a block for determining this noise at the output of a single-shot system of over-periodic compensation. To confirm the performance of the developed detector of non-synchronous pulsed interference in the conditions of an additive mixture of uncorrelated and discrete-range correlated Gaussian interference, a simulation model was developed in the Matlab&Simulink software package. The study confirmed the performance of the developed algorithm within the constraints of the dynamic range, and determined the parameters of the additive mixture of pulsed, uncorrelated and correlated interference for which the efficiency of the proposed detector exceeds that of existing detectors. The results obtained can be used to design of coherent-pulsed radar systems for detecting signals from moving targets in complex interference environments.

Comparative analysis of digital modulation classification methods based on deep neural networks

Ivan Horbatyi — 2025-12-30

Automatic classification of digital modulation formats (AMC) is a critical component of modern radio monitoring systems, cognitive communication platforms, and interference-resilient wireless communication systems. The rapid expansion of wideband and dynamically varying radio environments creates the need for classifiers that remain reliable across a broad range of signal-to-noise ratios (SNR). Recent advances in deep learning have significantly improved digital modulation classification performance, yet the impact of training strategies and neural-network architectures under low-SNR conditions remains insufficiently studied. This work addresses this gap by performing a comparative evaluation of two deep neural architectures — a 1D Convolutional Neural Network (CNN) and a complex-valued Residual Network — trained and tested on a large-scale dataset of digitally modulated I/Q signals.
The research aimed to construct a mapping from raw time-domain I/Q sequences to discrete digital modulation labels while ensuring stability of the classifier with respect to SNR variations. Four training strategies are investigated: training at a single low SNR, training at a single high SNR, training over the full SNR range, and curriculum learning with gradually decreasing SNR. Both models are evaluated across the entire SNR interval using accuracy curves, Top-2 accuracy, and confusion matrices.
The experimental results demonstrate that the complex-valued Residual Network consistently outperforms the CNN, particularly in low-SNR scenarios, and benefits most from curriculum learning. The CNN provides competitive performance at moderate and high SNR but exhibits reduced robustness in noisy conditions. The findings highlight the practical relevance of selecting appropriate architectures and training schemes for reliable modulation classification in non-ideal radio environments. The presented framework enables reproducible benchmarking and can be applied to the design of noise-resilient AMC modules in real communication systems.

Development and simulation of a high-precision MPPT controller for thin-film solar cells

Vitalii Fedenko — 2025-12-30

The paper presents circuit implementations of a high-precision MPPT (maximum power point tracking) controller adapted to operate with small samples of thin-film solar cells based on cadmium telluride (CdTe). The implemented circuit showed high stability during experimental studies and can operate with currents from 1 μA to 3 A. The effectiveness of the selected maximum power point tracking algorithm was evaluated using a simulation model based on the pvlib library, which operates on the basis of the five-parameter De Soto model and the MPP incremental conductance tracking algorithm with specified parameters. The simulation results show a tracking efficiency of 97.88% over the year and 99.83% over the day, which ensures high efficiency considering the very low output power levels of thin-film photovoltaic cells.

Application prospects of active balancing in multi-module battery packs

Dmytro Lipko — 2025-12-30

In modern batteries, particularly those used in electric vehicles, one of the key factors determining efficiency, reliability, and durability is the imbalance of charge levels (state of charge, SoC) between cells. This imbalance arises due to technological heterogeneity of cells, differences in internal resistance, degradation levels (state of health, SoH), temperature gradients, measurement errors in control channels, and unequal cooling conditions. The imbalance leads to reduced usable capacity, increased thermal loads, and uneven current distribution during charging and discharging, which ultimately lowers efficiency and shortens battery lifetime. Previous studies highlight the potential of active balancing to mitigate charge-level imbalance in multi‑module batteries.
The aim of this work is to experimentally verify the effectiveness of active balancing, determine its impact on imbalance levels and energy efficiency indicators of multi‑module lithium‑ion batteries, and formulate practical recommendations for the use of active balancers in electric transport systems. The study showed that applying an active balancer to a module with degraded cells reduced the maximum imbalance from 220 mV to 45 mV, increased usable capacity from 33 Ah to 43 Ah, improved the estimated SoH from 69% to 81%, and extended the real driving range of the electric vehicle by 56% (from 82 km to 128 km when discharged from 100% to 10% SoC).
The experimental data confirm that local active balancing is an effective and economically feasible approach to restoring usable capacity, improving energy efficiency, and extending the service life of traction batteries without requiring full‑scale balancing of all modules. This approach is promising for practical implementation in electric transport systems and stationary energy storage, particularly for operational restoration of batteries with heterogeneous degradation levels.