Search Results (376)

The rapid electrification of transportation has accelerated the demand for high-power electric vehicle (EV)-charging systems with high efficiency, compact size, galvanic isolation, and flexible scalability. Conventional isolated EV chargers typically adopt cascaded AC–DC and DC–DC conversion stages, which require additional semiconductor devices, passive components, and bulky dc-link capacitors, thereby increasing system complexity and limiting power density. This paper proposes a scalable three-phase modular parallel quasi-single-stage isolated single-ended primary-inductor converter (SEPIC) for high-power EV fast-charging applications. The proposed converter integrates power factor correction, voltage regulation, and high-frequency isolation within a unified SEPIC-based conversion cell, eliminating the intermediate dc-link capacitor while reducing the number of magnetic components and power conversion stages. By employing a Δ-connected three-phase input and input/output-parallel modular configuration, the proposed architecture provides a flexible power expansion approach based on a 9 kW basic module, with the potential to extend to higher power levels, such as 54 kW, through paralleling multiple identical modules. The operating principle, steady-state characteristics, continuous conduction mode (CCM)/discontinuous conduction mode (DCM) transition mechanism, current-sharing behavior, and control strategy are systematically investigated. An 18 kW prototype consisting of two parallel modules is experimentally validated under 380 V three-phase AC input and 400 V DC output conditions. The experimental results demonstrate a peak efficiency of 97.5%, a rated efficiency of 97.3%, a power factor (PF) of 0.999, and an input current total harmonic distortion (THD) of 2.55%, confirming the effectiveness and scalability of the proposed converter for high-power EV fast-charging applications. Full article

This article presents a review and comparative analysis of converter architectures for electrolyzer systems, covering alternating current (AC) -grid-connected, direct-current (DC) -grid-connected, and renewable-energy-connected systems, as well as isolated and non-isolated configurations. The study classifies and compares key converter topologies based on engineering criteria, including voltage gain, efficiency, device count, control complexity, and implementation feasibility. Furthermore, the relationships among converter structures, power-source characteristics, and electrolyzer-system requirements are analyzed to reveal system-level engineering trade-offs. The analysis demonstrates that converter suitability depends on the combined requirements of the power source, galvanic isolation, electrolyzer characteristics, operating conditions, and application-specific engineering priorities. In addition, wide-bandgap semiconductor devices and electrolyzer operating characteristics are discussed as important factors in converter selection, particularly for improving converter efficiency, reducing current ripple, increasing power density, and supporting dynamic operation. This article therefore provides a systematic framework for converter classification and selection according to power-source characteristics, electrolyzer requirements, and application power levels. Full article

The growing research interest in diode rectifier unit-based modular multilevel converter (DRU-MMC) configurations has made it imperative to analyze their potential impact on the short-circuit current characteristics of future AC grids. Most existing short-circuit current calculation approaches are oriented toward DC-side fault scenarios, while systematic research on AC-side fault analysis remains incomplete. To address this limitation, this work first illustrates the operating mechanism of the MMC. The short-circuit current at the fault point is decomposed into two independent components based on the superposition theorem. These components are: the current injected by the MMC and the current originating from the AC system. This work further explores the regulatory mechanism by which dq-axis limiting and fault-ride-through current limiting shape the MMC’s output current and derives an analytical equation for its amplitude. Furthermore, the phase correlation between the MMC-injected current and the AC system current under symmetrical fault conditions is clarified, and the computational formula for the aggregate short-circuit current is established. Then, considering the influence of transition resistance, the proposed method is verified to be applicable to both symmetrical metallic and non-metallic faults. Then, the symmetrical component method is used to analyze the sequence component of asymmetric fault short-circuit current, and a negative-sequence suppression (NSS) strategy is introduced. At the same time, considering the influence of transition resistance, the calculation formula of asymmetric metal and non-metal fault short-circuit current is derived. At the final stage of the study, a two-terminal simulation model is constructed in the PSCAD/EMTDC simulation environment. Comparative verification confirms that the results derived from theoretical calculation are in strong agreement with the simulation outcomes. The approach introduced here offers a favorable combination of simplicity and precision, rendering it highly suitable for practical engineering use. It reliably determines the short-circuit current under various fault conditions, thereby supporting fault-current analysis and the coordination of protective relays on the AC side of the receiving-end MMC in a DRU-MMC system. Full article

Proton exchange membrane fuel cell (PEMFC) systems typically generate low-voltage and high-current DC power, requiring a step-up converter interface for electric vehicle (EV) and DC microgrid applications. In addition, excessive current ripple and rapid transient loading conditions may increase electrical and thermal stress within the fuel cell stack. Consequently, both converter topology and control strategy play important roles in maintaining stable system operation and favorable PEMFC operating conditions. This paper presents a differential flatness-based nonlinear control strategy for a PEMFC-fed multiphase interleaved boost converter. The proposed control structure combines inner-loop inductor current regulation with outer-loop DC bus energy regulation. This configuration achieves stable voltage control, balanced phase-current sharing, and reduced fuel cell current ripple during transient operating conditions. A two-phase interleaved boost converter prototype was experimentally implemented using a 2.5 kW PEMFC platform and a dSPACE DS1202 MicroLabBox real-time controller. Experimental tests under steady-state and dynamic loading conditions were conducted to evaluate DC bus voltage regulation, transient response, current-sharing capability, and robustness against load disturbances. The experimental results demonstrated that the proposed nonlinear controller achieved faster transient voltage recovery and smaller DC bus voltage deviation compared with a conventional PI-based control approach. In addition, the interleaved converter structure reduced input current ripple at the PEMFC output terminals during dynamic operation. Overall, the results indicate that the proposed control strategy is suitable for PEMFC-powered EV and DC microgrid applications requiring stable DC bus regulation and fast dynamic power control. Experimental results demonstrate that the proposed controller reduces the DC bus voltage recovery time from approximately 150 ms to 50 ms, corresponding to a 66.7% improvement over a conventionally tuned PI controller. In addition, the maximum DC bus voltage deviation is reduced from approximately 1.0 V to 0.5 V while maintaining balanced phase-current sharing with less than 3% mismatch throughout the tested operating conditions. Full article

The electrical drive and the electrical motor share the same housing in Integrated Motor Drives (IMDs), which directly affects the reliability of failure-prone components in such a system. Existing studies are often conducted without considering system-level electrothermal reliability interactions in IMDs. This paper proposes a framework for electrothermal modeling for reliability analysis of IMDs during the early design phase. The framework is based on a back-to-back converter as an emulation platform adaptable to different high-speed electrical machines through software reconfiguration alone. It follows two stages: first, it converts the real-world mission profile, including high-speed operation, into load current commands and motor power loss. Secondly, the thermal network modeling accounts for thermal coupling between the components and the motor, which affects the junction temperature and the hot-spot temperature of the DC link capacitor. The parameters of the thermal network of the electrical motor can be the result of a multiphysics simulation or a real available motor. This framework enables reliability assessment considering motor thermal effects in the early design phase without requiring a physical motor prototype, while providing a fast and cost-effective approach for reliability evaluation. The experimental tests are performed to validate an electrothermal modeling framework capable of thermal modeling and reliability analysis. In addition, the reliability analysis of the power device is carried out by doing the simulation results using data from a real motor, selected for integrated power converter applications. The results demonstrate that the thermal interaction between the motor and the electrical drive causes an $11.5\%$ reduction in the predicted $B_{10}$ lifetime compared with the non-integrated configuration. The non-integrated configuration exhibits approximately 20,000$\mathrm{km}$ longer lifetime than the integrated configuration, highlighting the importance of considering motor-drive thermal coupling in IMD reliability assessment. Full article

The rapid electrification of marine transportation has increased the number of hybrid marine microgrids with the addition of renewables and energy storage. The continuously varying propulsion loads, fluctuating sea states, and renewable intermittency introduce significant challenges in bidirectional power transfer and power quality enhancement in marine vessels. This work presents a power-oriented operational strategy for a hybrid Roll-on/Roll-off (Ro-Ro) ferry-based marine microgrid (FMG) integrating diesel generators (DGs), Solar Photovoltaic (PV) arrays, and battery energy storage systems as the primary power sources. The proposed FMG adopts a hybrid AC/DC bus configuration linked through a bidirectional voltage source interlinking converter (ILC). The ILC facilitates multiple functionalities, including effective load compensation, mitigation of Total Harmonic Distortion (THD), continuous power support through bidirectional energy exchange, maintenance of balanced sinusoidal currents, and unity power factor (UPF) operation, thereby providing an integrated solution for improved power quality and reliable microgrid performance. A supervisory control (SC) is devised to operate the FMG seamlessly under islanded modes depending on the availability of power sources. To achieve the above-mentioned objectives, a power-optimized Dual Power-based Instantaneous Power Theory (DP_IPT) is employed and it involves a Sequential Delay Signal Cancelation (SDSC)-based Phase-Locked Loop (PLL) for the effective extraction of sequence components, so as to address the unbalance and nonlinearities in an effective manner with reduced oscillations. The proposed control strategy reduces diesel generator utilization through the effective integration of Solar PV and battery support during anchoring operation. The integration of renewable energy sources substantially enhances clean energy utilization, resulting in the reduction of overall carbon emissions, accounting for a near-40% decrease in emissions compared with the conventional diesel generator (DG)-based operating mode. The proposed FMG and control framework are validated through the Hardware-in-the-Loop (HiL) approach employing an OPAL-RT (OP4512) real-time controller. The HiL investigations demonstrate the efficacious working of the proposed control in achieving less carbonized and enhanced power quality operation for next-generation electrified hybrid maritime microgrids. Full article

To meet the demand for large-capacity and long-distance transmission of deep-sea offshore wind power and coordinated export of multiple energy sources in coastal clean-energy bases, this paper investigates the topology configuration and operating characteristics of a multi-energy DC collection system for offshore wind power integration. Based on the characteristics of offshore wind power, nuclear power, onshore photovoltaic generation and pumped storage, a source-type–converter-topology–control-function matching relationship is established. A ±800 kV true-bipolar DC large-bus system is then constructed, in which the four sources are configured as a lightweight offshore wind export branch, a stable power-export branch, a fast controllable renewable-energy branch and a system regulation resource, respectively. A polarity-interface conversion link is introduced to match the local offshore wind export structure with the main true-bipolar DC system, and the power-balance relationship among sending-end injection, receiving-end absorption and DC-bus voltage is formulated. PSCAD/EMTDC simulations are performed under steady-state operation, wind-speed step disturbance, a sending-end AC three-phase metallic grounding fault and a submarine-cable pole-to-ground fault. The results confirm that the proposed differentiated topology can support multi-energy collection, true-bipolar voltage coordination and continuous stable operation under typical disturbances. Full article

We formulate and analyze a 26-dimensional nonlinear dynamical system governing a doubly-fed induction generator (DFIG) wind energy conversion system coupled to an infinite bus through a dynamic transmission line. Seven interacting subsystems—aerodynamics, a two-mass drivetrain, a fourth-order machine, rotor- and grid-side converter controllers, a phase-locked loop, and a pitch regulator—are assembled into a single vector field $\dot{\mathbf{x}}=\mathbf{f}(\mathbf{x},\mathbf{u})$ on ${\mathbb{R}}^{26}$, derived in dimensionless coordinates. Strict positivity of the determinant $\mathrm{\Delta }=L_s{L}_r-L_m^2=\sigma L_s{L}_r$ for every physically admissible machine renders the flux–current map invertible, so the right-hand side is well defined; the nodal Kirchhoff constraint forms a semi-explicit differential-algebraic relation that we eliminate to obtain an explicit ordinary differential equation. The central contribution is a constructive scheme for the equilibria: the 26 stationarity conditions $\mathbf{f}({\mathbf{x}}^{\star },\mathbf{u})=\mathbf{0}$ are solved by an iterative voltage-matching procedure converging to a residual below ${10}^{-11}$ per unit—essentially machine precision—which removes the spurious start-up transients common in reported simulations. Analytically chosen feedback gains induce a hierarchy of well-separated time scales, placing the closed loop in the multiple-time-scale class; the separation is made quantitative through explicit small parameters ${\epsilon }_i$ formed from the ratios of subsystem time constants. Numerical integration of a GE $3.6$ MW configuration confirms the construction: under stationary forcing, the rotor speed stays within $1.32\times {10}^{-5}$ pu of the equilibrium, and under a large-amplitude wind program ($11\to 14\to 9$ m/s) spanning the full operating envelope, it is regulated to within $0.065\%$, while the DC-link voltage deviation remains below $2.4\times {10}^{-5}$ pu and the power balance closes with residual below ${10}^{-3}$ pu, the ≈2% mechanical–electrical gap being the modeled losses. Linearization about the computed equilibrium yields a Jacobian whose spectrum lies entirely in the open left half-plane, establishing local asymptotic stability and exposing the individual electromagnetic, torsional, and control modes. The model furnishes a rigorously initialized, analytically transparent basis for linearization, spectral stability analysis, and bifurcation study. Its practical value is that a consistent equilibrium and a certified spectrum remove the start-up transients and undocumented tuning that otherwise let initialization artifacts masquerade as genuine dynamics, so that the model can serve as a trustworthy building block for weak-grid and wind-farm stability studies. Full article

This paper proposes a new hybrid switched inductor and switched capacitor (HSISC) buck–boost DC–DC converter. For the duty ratio above 28%, the proposed converter operates as a boost converter; otherwise, it acts as a buck converter. Compared with conventional buck–boost converters, incorporating the hybrid switched inductor and switched capacitor (HSISC), the network yields a substantial voltage gain at lower duty ratios. Being a non-isolated topology, high-frequency transformers and the associated issues are absent. Additionally, the proposed topology has the merits of continuous input current, making it suitable for renewable energy integration and vehicle-to-grid (V2G) applications, a wide range of duty ratio for boost operation, and ease of control as there are only two modes of operation with switches operating in a complementary manner. Operational analysis for the two modes, necessary mathematical derivations for component design, and a steady-state analysis of the converter are reported. The experimental findings for the converter, which were conducted at a duty ratio of 0.05 to 0.5 at a switching frequency of 10 kHz, are reported. The presented results provide proof-of-concept validation based on analytical and simulation studies, demonstrating the feasibility and operational characteristics of the proposed converter. Full article

Hybrid energy storage systems combining LiFePO₄ batteries and supercapacitors can reduce high-rate battery loading in battery electric mining dump trucks operating under intensive regenerative braking conditions. This study proposes a constrained multi-objective sizing methodology for a semi-active battery–supercapacitor hybrid energy storage system applied to a 65 t payload-class mining electric dump truck. The model combines segment-level mining duty cycles, longitudinal vehicle dynamics, a first-order Thevenin battery representation, a usable supercapacitor energy window, bidirectional DC/DC converter limits, and constrained supervisory power splitting. Three mining duty cycles are considered: production haulage, reclamation/backfill operation, and mixed operation. The final sizing result is reported using a dimensionless usable energy buffer ratio rather than a direct comparison between supercapacitor capacitance and battery energy capacity. The results show that the required supercapacitor buffer is strongly duty cycle-dependent. For the regenerative-dominant backfill cycle, the hybrid configuration reduced peak battery charging current from approximately −950 A to −180 … −280 A and reduced battery root mean square (RMS) current by 52–64% relative to the pure battery configuration. The constrained stored fraction of regenerative energy also increased when the supercapacitor branch was included, while non-accepted braking power was assigned to the residual braking channel. The proposed approach provides a physically consistent basis for preliminary hybrid energy storage system (HESS) sizing and clarifies that battery current reduction should be interpreted as a degradation-relevant stress indicator rather than as a direct quantified lifetime prediction. Full article

Maximum power point tracking (MPPT) is essential for photovoltaic (PV) efficiency under dynamic environments. This paper presents a comparative analysis of three MPPT algorithms: incremental conductance (INC), Q-Learning (QL) reinforcement learning, and Transformer-inspired Machine Learning (TML) applied to a photovoltaic (PV) array configured in a 1S×3P with a DC-DC boost converter designed for a 48 V DC output. Simulations were performed under four scenarios in MATLAB/Simulink: standard test conditions (STC), irradiance variation, temperature variation, and combined wide-range variations. At STC, all three exceed 99% tracking efficiency, with QL achieving the highest efficiency, 99.914%; TML having the best output voltage regulation (48.071 V); and INC converging fastest (5.4 ms). Under dynamic irradiance variations, QL attained the highest average tracking efficiency (91.85%) and average output power (481.4 W), whereas INC converged within 36.9 ms. Under temperature variations, TML achieved the highest average tracking efficiency (97.448%) and average power output (549.30 W), while INC maintained the fastest convergence rate (68.6 ms). With wide-range combined variation, QL achieves the highest average tracking efficiency (91.32%) and output power (469.9 W), outperforming TML (84.06%) and INC (57.39%) by 7.3 and 33.9 percentage points, respectively; INC converges fastest (33.1 ms) but delivers 64.1% less output power than QL. The simulation results demonstrate that artificial intelligence-driven algorithms can significantly improve maximum power point tracking (MPPT) under dynamic conditions. To establish real-world viability, future work requires hardware-in-the-loop (HIL) testing and experimental validation. Full article

This paper presents a comprehensive review of state-of-the-art developments in electric vehicle (EV) charging technologies, charging stations, and charging protocols, with particular emphasis on their integration with renewable energy sources (RESs). EV chargers are generally classified into on-board and off-board configurations. This study examines recent designs and advanced control strategies for both AC/DC and DC/DC power conversion stages, highlighting key technical aspects, recent innovations, and existing challenges. Furthermore, it provides an in-depth discussion of emerging multiport EV charger architectures that integrate photovoltaic (PV) systems, energy storage units, EVs, and the power grid within a unified framework. A comparative analysis is also presented to evaluate various converter topologies and energy management strategies used in the AC/DC and DC/DC stages of EV charging systems. Critical performance indicators such as power rating, output voltage level, efficiency, economic feasibility, and system complexity are also discussed. A comprehensive comparison is conducted among 13 review papers between 2015 and 2026, identifying key trends, methodological differences, and common findings. Full article

This paper presents an on-load programmable configuration of individual dual active bridge modules on a single-core transformer for wide voltage range and multi-port DC-DC power conversion. The mathematical models of power delivery and control transfer functions are presented for the proposed configurable converter. The universal control structure to implement the programmable configuration, control parameter programming, and closed-loop current regulation is presented. Simulation of the proposed converter and control is implemented in MATLAB/SIMULINK 2026A. A reduced-scale hardware prototype is implemented to validate simulation results. The performance of the converter in terms of feasible on-load switching of configurations and simultaneous regulation of multiple loads are compared to existing topologies, which demonstrated stable operation of proposed converter and control scheme over the investigated voltage range. Full article

The trend in the power electronics industry toward higher power density and efficiency has brought high-frequency transformers (HFTs) to the forefront of critical applications, including isolated DC–DC converters, electric vehicle chargers, and solid-state transformers. This paper focuses on the leakage inductance of HFTs and presents a systematic comparative framework that evaluates five surrogate modeling and hybrid optimization approaches for the rapid and accurate estimation of leakage inductance. A comprehensive parametric dataset was constructed, comprising 1210 finite element analysis simulations conducted via finite element analysis in the ANSYS Maxwell 2024 R1 environment, varying the number of winding turns, primary winding thickness, and secondary winding thickness of the HFT. All five methods were trained and evaluated on the same dataset under identical conditions. The comparative evaluation demonstrates that the proposed hybrid Gray Wolf optimizer–artificial neural network (GWO-ANN) framework achieved the highest prediction accuracy (R² = 0.9832, MSE = 0.01780, MAE = 0.0935 µH) and the fastest convergence among all tested approaches. The generalization capability of the proposed model was confirmed through blind validation tests across six geometric configurations spanning the full range of the design space, yielding a maximum prediction error of 8.15% and an average error of 2.14%. The functional validity of the proposed parameters was further tested in a third validation layer using MATLAB/Simulink R2024b transformer circuit studies, demonstrating a theoretical efficiency of 96.06%. This three-layer validation approach proves both the parametric and functional reliability of the proposed framework for HFT designs. Full article

This study presents a hybrid controller that integrates fuzzy logic control and the Incremental Conductance method. This controller optimizes maximum power point tracking in a 330 W photovoltaic system by designing a DC-DC converter. The study evaluates how the number and distribution of membership functions, specifically three-, five-, and seven-function configurations, affect system performance using the Integral Square Error (ISE) and Integral Absolute Error (IAE) indices. The empirical results demonstrate that the seven-function architecture yields optimal performance, minimizing ISE and IAE to 0.1155 and $7.365\times {10}^{-4}$, respectively. Furthermore, this optimal configuration attains an energy efficiency of 99.7%, notably outperforming the baseline three-function configuration, which exhibited a worst-case efficiency of 98.9 %. To assess robustness against dynamic environmental variations, this study subjects the optimal configuration to fluctuating irradiance and temperature profiles. Additionally, an analysis of computational resource consumption reveals that the proposed hybrid controller incurs a lower computational load for rule evaluation than three controllers reported in the recent literature. These findings demonstrate the system’s structural efficiency and superior optimization capability, achieving maximized photovoltaic energy harvesting at a low computational cost. Full article