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        <title>Power Electronics and Drives Feed</title>
        <link>https://reference-global.com/journal/PEAD</link>
        <description>Reference Global RSS Feed for Power Electronics and Drives</description>
        <lastBuildDate>Mon, 26 Oct 2026 09:30:18 GMT</lastBuildDate>
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            <title>Power Electronics and Drives Feed</title>
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        <copyright>All rights reserved 2026, Wroclaw University of Science and Technology</copyright>
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        <item>
            <title><![CDATA[Consolidated SVPWM for Single-Phase Fault-Tolerant Control of CFNI-Based Inverter]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0029</link>
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            <pubDate>Wed, 14 Oct 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Fault-tolerant control is essential for traction drive systems, which are pivotal components in electric vehicles and high-dependability applications. These systems face significant challenges, particularly under single-phase faulty conditions at either the machine or the inverter level, which can lead to performance degradation or system failure if not properly managed. This paper presents a fault-tolerant approach based on a consolidated space vector pulse width modulation (SVPWM) to enable the traction drive system to operate under single-phase faults. The proposed method leverages the capacitor-based four-leg neutral-point-connected inverter (CFNI) topology and integrates a remedial approach grounded in field-oriented control (FOC) to drive a permanent magnet synchronous motor (PMSM). The simulation results validate the effectiveness of the proposed method in maintaining reliable operation under fault conditions, preserving accurate speed and torque tracking with minimal deviations. Nevertheless, the elevated current stress observed during fault scenarios requires oversized inverter ratings. These findings demonstrate the robustness of the proposed SVPWM strategy implemented on the CFNI topology, confirming its viability for single-phase fault-tolerant traction drive applications.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Erratum to Short-Horizon Finite-State Voltage Control of Bidirectional DC–DC Converter with Non-Minimum Phase Dynamics]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0030</link>
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            <pubDate>Mon, 12 Oct 2026 00:00:00 GMT</pubDate>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Tests of Novel Permanent Magnet Cogging Motor]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0028</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0028</guid>
            <pubDate>Sun, 20 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper provides a detailed description of the process of developing a prototype of a novel permanent magnet machine. The machine operates based on the principle of transverse-flux machines (TFMs). The proposed solution employs a core that is typically used in radial-flux machines, which significantly simplifies the construction of the TFM. This innovative approach not only minimises flux leakage but also increases the generated electromagnetic torque. The paper presents the assumptions adopted at the design stage, the selection of materials used to build the prototype, and the geometry of its individual components. Laboratory tests were carried out on the permanent magnet cogging motor (PMCM) prototype, and the paper presents the measured torque characteristics, the torque constant, the motor losses, the temperature effect, the noise level, and the efficiency. The torque constant was 3 Nm/A for an air-cooled 10 kW prototype with stable temperature below 130°C.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Design and Development of Boost PFC Converter for Medium-Power High-Voltage Power Supply]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0027</link>
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            <pubDate>Sat, 12 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper presents the design, modelling, and control of a front-end boost power factor correction (PFC) converter for a medium-power, high-voltage (HV) power supply intended for non-thermal plasma (NTP)-based electrostatic precipitator (ESP) and indoor air purifier. In such systems, the front-end PFC supplies a downstream inverter, HV transformer, and dielectric barrier discharge (DBD), together forming a non-linear and time-varying load. The load behaves as a capacitor in series with a non-linear resistor once plasma discharge is initiated. These abrupt transitions in load impedance impose stringent limitations on the control bandwidth and system stability. To ensure robust operation and tight DC bus regulation under these conditions, a deliberately slow outer voltage loop is required. Therefore, a frequency-differentiated modelling (FDM) approach is proposed, in which a conventional state space averaged small-signal model represents the fast inner current loop, whereas the slow outer voltage loop is modelled using a capacitor charge transfer (CCT) model that captures low-frequency energy dynamics. In addition, a grid-aligned resonance tuning (GART) method is proposed to select the DC-link capacitor by aligning the plant resonance with the grid frequency. This enables improved current shaping and reduced harmonic distortion using a simple proportional integral (PI) control. In addition, a generalised PI tuning algorithm is derived from the passive component values of the converter and desired crossover frequencies, eliminating the need for plant transfer function (TF) derivation, Bode plot analysis, or iterative frequency-domain tuning. The proposed methodology is well suited for application-driven PFC designs that require simplicity, robustness, and compliance with power quality standards.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Design Aspects for Efficiency Improvement of Switched Reluctance Motor]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0026</link>
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            <pubDate>Sat, 15 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[A 10-kW switched reluctance motor is investigated with respect to key design parameters, including the number of winding turns, the stator and rotor pole-arc–to–pole-pitch ratios and the machine axial length. The analysis is carried out by systematically varying these four parameters within predefined bounds and identifying the optimal combination that maximises efficiency. The accuracy of the optimised motor model is validated using manufacturer catalogue data. The results illustrate the influence of each design parameter on the motor’s efficiency. Finally, the transient performance is evaluated, emphasising the importance of appropriate motor control strategies, particularly the selection of turn-on and turn-off angles and proper DC-link size to achieve the desired operating behaviour.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Erratum to A Reduced Switch Single-Source Multilevel Inverter with GA-Based Selective Harmonic Elimination]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0025</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0025</guid>
            <pubDate>Thu, 30 Jul 2026 00:00:00 GMT</pubDate>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Optimal Tuning of PD-Type Iterative Learning Control for DC Gear Motors Using Bayesian Neural Networks]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0024</link>
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            <pubDate>Thu, 30 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper presents an efficient data-driven method to obtain the optimal parameters of a proportional-derivative (PD)-type iterative learning control (ILC) system for direct current gear motors. The proposed method aims at improving the convergence speed, tracking performance, robustness and reliability of the control system under different working conditions. Bayesian neural networks (BNN) embed probabilistic inference in the learning process, in contrast to conventional neural networks, which produce only deterministic outputs. This enables the proposed controller to better cope with uncertainties, noise and variations in the system dynamics. First, an approximate mathematical model of the DC gear motor is derived from the electrical and mechanical features of the motor-drive system. The model is then used to generate a large data set under different operating conditions with variations in system parameters and control responses. Then, the BNN is trained with these data to estimate the optimal proportional and derivative learning gains accurately to minimise the settling time and overshoot in the iterative learning process. The experimental results show that the proposed BNN-based ILC (BNN-ILC) controller significantly outperforms the conventional proportional-integral (PI) controller.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Comparative Study of Fuzzy Logic and Neural Network Control for Battery Power Management in Smart Microgrids]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0023</link>
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            <pubDate>Thu, 30 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This work presents a comparative study of two intelligent control strategies, fuzzy logic (FL) and artificial neural network (ANN), for a battery management system (BMS) within a grid-connected hybrid microgrid. The implementation and the evaluation of these intelligent controls were carried out using a real-world dataset under distribution grid instability constraints. The simulation results demonstrate that, while the fuzzy controller offers a faster dynamic response with high instantaneous power, it induces intensive battery loading characterised by frequent micro-cycling. On the other hand, the ANN-based control makes the power regulation smoother, thus minimising stress on the storage system and promoting energy efficiency. The economic analysis confirms the superiority of the neural approach, revealing a 17% reduction in energy costs compared to FL. These results highlight the crucial trade-off between response time and battery life preservation, positioning neural networks as a robust and cost-effective solution for the short-term management of smart microgrids.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Experimental Comparison of Single-Tier and Multi-Tier Switched-Capacitor Active Cell-Balancing Topologies]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0022</link>
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            <pubDate>Thu, 30 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper presents an experimental comparison of capacitor-based active cell-balancing topologies implemented on a 12S1P lithium-ion battery pack. The study focuses on evaluating the balancing performance of single-tier switched-capacitor (SC), double-tiered switched-capacitor (DTSC), and extended double-tiered switched-capacitor with an additional capacitor (DTSCAC) configurations under identical initial conditions. A modular hardware platform was developed to enable controlled and repeatable experiments. The balancing process was evaluated based on voltage equalisation of individual cells, with completion defined as a maximum voltage difference of 50 mV between the highest and lowest cell. Experimental results show that the DTSC topology generally achieves shorter balancing times compared to the SC configuration, particularly for moderate cell distances. In contrast, the DTSCAC topology does not provide consistent improvement and may result in longer balancing times. In addition to balancing time analysis, current waveforms were measured at multiple nodes within the battery pack to provide insight into charge transfer behaviour. The results highlight the influence of topology and cell posit ion on balancing performance.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Detection of Rotor Unbalance in Multi-Mass Systems Using FFT and Bispectrum]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0019</link>
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            <pubDate>Mon, 22 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Unbalance of rotating components is a highly destructive phenomenon that adversely affects the operation of a machine. Vibrations generated by an unbalanced rotor are transmitted through the bearing assembly to the machine housing, accelerating the ageing process of the bearings and, over time, leading to their premature failure. Unfortunately, there are no instruments that allow unbalance to be detected directly during machine operation, which makes it necessary to monitor its secondary effects. An additional factor that complicates the detection of unbalance is the coupling of the motor with the driven machine. The method of connecting the two machines is also significant. The article discusses selected methods for detecting rotor unbalance in single-mass and two-mass systems with elastic coupling. The adopted mathematical models based on gravitational force and centrifugal force are presented. The laboratory test stand and research methodology are also described. To model the unbalance, a test mass is added to the disc rotating on the motor shaft. The added mass constituted less than 0.5% of the mass of the rotating components. Tests were conducted in steady-state conditions at a speed below 20% of the motor’s rated speed. The study analysed mechanical vibrations and the reference current from the control system. Fast Fourier transform and higher-order bispectrum analysis were used to obtain diagnostic symptoms.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Diode Rectifier with Improved Quality Indicators for Electrical Energy]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0020</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0020</guid>
            <pubDate>Mon, 22 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[In this work, we present a three-phase diode bridge rectifier with a power line current close to a sinusoidal shape. To benefit from this approach, a solution called ‘current modulation’ is used in the DC link of the rectifier. The main advantage of this system is that the power supplied to the current modulation stage is only a small percentage of the entire power system, meaning that this solution is especially attractive in the case of high-output power systems, for example, for supplying electrical traction. The essential aspect of the current modulation stage is a wide-pass band power electronics controlled current source (VCCS), which is based on a dual-channel (interleaved) topology. The control algorithm for the current modulation stage also takes into consideration the impact of aliasing phenomena on the stability of the system, and uses a control method proposed by the authors. This work contains a general description of the operation of this rectifier and presents basics of operation for the current modulation stage. Selected results from both a simulation of the rectifier and an experimental model are included.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Digital Twins in Electric Drives: A Review and Proposed Framework]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0021</link>
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            <pubDate>Fri, 19 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Digital twin (DT) technology has become a core enabler of Industry 4.0 by providing a dynamic virtual representation of physical systems for real-time monitoring, simulation optimisation, supported by Internet of Things (IoT) sensing and connectivity. Electric drives (ED) can particularly benefit from DTs because they enable condition monitoring, fault diagnosis remaining useful life (RUL) estimation. The reviewed literature is analysed in terms of application, model type, integration level, strengths limitations. The proposed six-layer framework separates offline commissioning and validation from online synchronisation and decision support. Additionally, an induction motor drive use case is presented to demonstrate how the proposed framework can be applied in practice. The use case comprises a V/f-controlled induction motor supplied by an inverter, together with isolated voltage and current measurements, speed acquisition, signal preprocessing, virtual model synchronisation using an extended Kalman filter (EKF) supervisory control for improving drive operation. The proposed framework provides criteria for designing and validating DTs for electric drive monitoring, fault diagnosis, predictive maintenance supervisory control.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Deep Learning-Based MPPT for PV Systems: LSTM Forecasting and Adaptive TSMC via PPO Agent]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0018</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0018</guid>
            <pubDate>Fri, 19 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Maximum power point tracking (MPPT) is a crucial technique for maximising the efficiency of photovoltaic (PV) systems by continuously adjusting the operating point of the PV array to extract the maximum possible power under varying environmental conditions. Conventional MPPT methods are often simple to implement but suffer from slow response times, oscillations, and reduced efficiency under rapidly changing irradiance and temperature conditions. Advanced control strategies like sliding mode control (SMC) offer improved robustness but can still exhibit chattering effects and may not be optimal for the dynamic, non-linear behaviour of PV systems. The growing complexity of PV systems, particularly those operating under partial shading, necessitates a more intelligent and adaptive approach that can predict optimal operating points and adjust control parameters in real time to overcome these limitations. This paper proposes an innovative hybrid approach for MPPT in PV systems, combining a long short-term memory (LSTM) neural network for dynamic voltage prediction, a Terminal Sliding Mode Control (TSMC) control for robust tracking, and a proximal policy optimisation (PPO) reinforcement learning (RL) agent to optimise TSMC parameters in real-time. This synergy combines LSTM’s predictive capability with deep reinforcement learning (DRL)’s adaptive optimisation creating a more efficient and robust MPPT system than conventional methods. Simulations under various environmental conditions show that the proposed hybrid controller significantly outperforms a conventional sliding mode controller and a standalone TSMC system. Notably, the integrated deep learning (DL) and RL approach enhances overall energy efficiency. The proposed method achieves a superior efficiency of 97.4%, a lower average error of 0.25, and a faster response time of 65 ms compared to the conventional methods. This integration of DL allows for dynamic adaptation to irradiance and temperature variations, improving the overall energy efficiency of the PV system.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Short-Horizon Finite-State Voltage Control of Bidirectional DC–DC Converter with Non-Minimum Phase Dynamics]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0015</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0015</guid>
            <pubDate>Fri, 12 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Bidirectional DC–DC converters play a critical role in DC microgrids by enabling regulated voltage conversion and bidirectional power flow between energy sources, storage systems and loads. However, achieving fast and robust voltage regulation in such converters remains challenging due to non-minimum phase (NMP) dynamics, digital implementation delays and model uncertainty. In the literature, short-horizon finite-state voltage control strategies are presented as desired methods for controlling these converters. In this paper, a systematic comparison of recent short-horizon finite-state control strategies—including single-horizon finite-set model predictive control (FS-MPC), compensated bang-bang (BB) control and BB control with doubled sampling frequency (DSF-BB)—is first presented. Subsequently, a novel model-free bang-bang (MF-BB) control strategy is proposed. The proposed model-free approach eliminates reliance on an explicit system model by generating the desired inductor-current reference directly from measured current signals, while preserving short-horizon operation and low computational complexity. The performance of the proposed method is then compared with existing approaches through comprehensive simulation studies under non-minimum phase operation and digital implementation delays. Additional evaluations consider parameter variations and conduction-mode transitions. The simulation and experimental results demonstrate that the proposed MF-BB strategy achieves transient response, settling time and steady-state voltage regulation comparable to the model-based methods while eliminating dependence on converter parameter accuracy. These findings highlight the effectiveness and practical suitability of the proposed approach for digitally controlled bidirectional DC–DC converters in DC microgrid applications.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[FPGA-Based Custom Hardware-in-the-Loop Emulation of High-Power Induction Motor Drives with Sub-Microsecond Resolution Using NI LabVIEW FPGA]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0016</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0016</guid>
            <pubDate>Tue, 09 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper presents the development and experimental validation of a custom Field-Programmable Gate Array (FPGA)-based hardware-in-the-loop (HIL) emulator for high-power induction motor drives. The proposed system enables real-time emulation of a variable-frequency drive consisting of a diode rectifier, a two-level voltage source inverter (VSI), and a 215 HP induction machine. The emulator is implemented on an NI PCIe-7857R FPGA platform using LabVIEW FPGA and fixed-point arithmetic optimised for Kintex-7 resources. A key contribution of this work is the achievement of a 100 ns real-time simulation time step for the converter and machine models, enabling accurate representation of fast switching dynamics while avoiding aliasing effects typically encountered in HIL systems. A multi-rate architecture is adopted to allocate appropriate sampling frequencies to different subsystems, improving computational efficiency and stability. Experimental results obtained from a closed-loop setup with an sbRIO-based controller demonstrate accurate emulation of inverter operation, induction machine dynamics, and controller interactions. The developed platform also enables detailed investigation of switching phenomena, such as voltage spikes, dead-time effects, and current ripple. Comparative validation with a Typhoon HIL 602+ platform confirms similar dynamic behaviour and harmonic performance, demonstrating that the proposed low-cost FPGA-based solution provides a flexible and high-fidelity alternative for real-time power electronics research and controller development.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Instantaneous Power Signal in Short-Circuit Diagnosis of Induction Motors Using a FEM Model]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0017</link>
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            <pubDate>Mon, 08 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The paper presents a diagnostic approach for detecting interturn short circuits in induction motors through instantaneous power analysis, supported by a field-circuit finite element model (FEM). The study focuses on developing and validating a numerical model of an Indukta Sh90L-4 motor, which enables accurate simulation of electromagnetic phenomena that occur during stator winding failures. The proposed method uses the triple Park transformation to extract characteristic harmonics from instantaneous power signals, particularly components at 2fs, which strongly correlate with the asymmetry caused by winding faults. Experimental tests were carried out on a laboratory test stand, allowing controlled introduction of short circuits. Comparison between simulations and measurements showed high consistency, demonstrating that the instantaneous power spectrum provides sensitive indicators of both fault presence and severity. The presented technique is computationally efficient, suitable for real-time implementation, and offers a promising tool for industrial motor condition monitoring and early fault detection.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Newton–Raphson Method-based Power Flow Decoupling for Five-port Modular Multi-Active Bridge Converters]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0013</link>
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            <pubDate>Mon, 25 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Modern energy systems require efficient power management, making multi-active bridge (MAB) converters ideal for electric vehicle (EV) charging and DC microgrids. However, higher port counts lead to magnetic coupling and non-linear dynamics, complicating independent control. This paper proposes a generalised power flow decoupling strategy for a five-port modular multi-active bridge (MMAB) converter using the Newton–Raphson (NR) method. Unlike traditional reduced-order models, a current-based model is employed to maintain modularity. A key contribution is the integration of the Moore–Penrose pseudoinverse into the NR solver to mitigate Jacobian singularities and ensure numerical stability. The algorithm is implemented on a dual-core central processing unit (CPU), achieving a deterministic 40 μs execution time. Furthermore, this study identifies performance degradation caused by parasitic inductances in the modular AC bus and proposes an optimised design using magnetic flux cancellation. Modelling precision is further refined through offline fast Fourier transform (FFT)-based parameter identification. Experimental validation on a five-port MMAB prototype confirms that the proposed method provides superior steady-state accuracy and robust dynamic decoupling during rapid transient load transitions.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[A Comparative Study of Control Schemes Based on PI Controllers and State-Feedback Control for Grid-Connected Converters]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0014</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0014</guid>
            <pubDate>Mon, 25 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper provides a comparative analysis of two classical control strategies applied to a grid-connected voltage-source converter (VSC) with an L-type filter. The first method employs a cascade control structure with proportional–integral controllers, while the second uses a full-state feedback controller designed via the linear quadratic regulator method. A linearised state-space model of the converter, including controller and modulation delays, is developed and consistently used for both control schemes to enable a fair comparison. The control approaches are evaluated through detailed numerical simulations under identical operating conditions, including grid voltage disturbances, load changes and reference variations. Performance is assessed based on transient response, disturbance rejection, control effort, robustness to parameter changes and stability margins. Disk margin (DM) analysis offers a conservative, comprehensive evaluation of closed-loop stability. The results show that, although both strategies attain similar settling times, the full-state feedback controller offers superior disturbance rejection, reduced peak currents and notably larger stability margins. The paper aims to provide practical insights and guidelines for selecting suitable control strategies for power electronic systems.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Detection of Voltage Asymmetry Based on DC Link Ripple and Analysis of Its Impact on Diagnostic Processes in Complex Electric Drives]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0012</link>
            <guid isPermaLink="false">/article/10.2478/pead-2026-0012</guid>
            <pubDate>Thu, 14 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Voltage imbalance can adversely impact electric motors and other equipment interfaced with a three-phase grid. This phenomenon is prevalent in both industrial power systems and various hybrid vehicle architectures. Faults within the voltage generation system may lead to distortions in the direct current link (DC-link) voltage, thereby compromising the efficacy of fault detection and compensation algorithms in electric drives. Consequently, power supply conditions must be accounted for when developing comprehensive diagnostic frameworks for alternating current (AC) machines. As the voltage asymmetry signatures manifest as specific ripples in the DC-link voltage of systems with an uncontrolled rectifier, detection can be achieved using a single sensor instead of the conventional three-sensor approach. This methodology was proposed and validated through both numerical simulations and experimental testing. Furthermore, the study investigated how variations in DC-link capacitance influence the resulting ripple-based asymmetry factor.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Optimisation of the Synchronous Rectifier in Phase Shift Full Bridge Converters for High-Frequency Applications]]></title>
            <link>https://reference-global.com/article/10.2478/pead-2026-0011</link>
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            <pubDate>Tue, 05 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Efforts to minimise the size and material usage of power converters are reflected in efforts to increase the switching frequency. The problem is that semiconductor switching losses are proportional to the switching frequency, so it is necessary to find ways to keep efficiency high at higher switching frequencies. Gallium nitride (GaN) transistors have made it possible to improve the parameters of many topologies due to a better figure of merit (FOM). Thanks to GaN technology, it is possible to increase the soft switching range in the inverter of phase-shift full-bridge (PSFB) converter and thus reduce switching losses. This paper addresses the selection of semiconductor transistors for a synchronous rectifier (SR) operating at 500 kHz. Based on mathematical calculations and simulation results in the programme PLECS, the converter was designed and measured under laboratory conditions. The paper highlights the advantages and challenges of using GaN transistors in SRs, which, when properly applied, enable lower losses and thus higher efficiency at a switching frequency of 500 kHz.]]></description>
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