This paper introduces a novel control strategy for Modular Multilevel Resonant converters (MMR) in Solid-State Transformer (SST) applications, with a focus on medium-voltage conversion for hydrogen electrolyzers. The article first reviews voltage control methods in MMR, analyzing their operational principles and regulation capabilities. A continuous modulation index control method with double-step staircase waveform modulation is then proposed, simplifying the control scheme to a single control variable while maintaining robust controllability. Meanwhile, the proposed approach maintains comparable power loss and harmonic performance to existing methods under the investigated operating conditions. Simulations and experiments are conducted to verify the feasibility and practical implementation of the proposed approach.

Due to the increasing demand for high-power charging in heavy-duty electric vehicles (HDEVs) and the inherent limitations of conductive charging, the development of a modular wireless power transfer (WPT) charging system has become indispensable. However, most existing studies rely on conventional two-stage AC-DC-AC converters at the primary side, which limit power density and reliability because of the bulky DC-link electrolytic capacitors. This paper proposes a novel modular medium-voltage AC (MVAC) grid-connected WPT system based on direct matrix converters (DMCs). A full-bridge DMC (FBDMC)-based WPT system is proposed with a simple fixed 50 % duty-cycle modulation strategy. Analytical and simulation results verify that the AC-input FBDMC-based WPT system can be equivalently represented by a DC-input fullbridge inverter-based WPT system with the same seriesseries compensation, RMS input voltage, and modulation. To achieve higher power transfer capability, scalability, and efficiency, input-series output-parallel (ISOP) and inputparallel output-series (IPOS) modular topologies are investigated. The simulation results demonstrate that, when connected to the MVAC grid using the ISOP configuration, the system is capable of delivering power at the hundred-kW to MW level. The proposed topologies are verified by the downscaled experimental platform. The FBDMC-based prototype achieves an output power of 2.51 kW with a grid-to-load efficiency of 91.6 % at 230 VAC. The IPOS and ISOP configurations are experimentally validated using two modular half-bridge DMC (HBDMC) modules derived from the FBDMC design.

This paper proposes a hybrid model predictive control (HMPC) strategy for a three-level neutral-point-clamped (3L NPC) rectifier to optimize the operation of electrolyzers for green hydrogen production. Unlike conventional approaches that focus primarily on inverter applications, the proposed method directly addresses the critical issue of neutral-point voltage imbalance in NPC rectifiers. The control framework combines discrete switching-state selection with adaptive objective prioritization, utilizing real-time capacitor voltage measurements to exploit switching-state redundancy. A multi-objective cost function balances current tracking, DC-link voltage regulation, neutral-point voltage balancing, and switching-loss minimization. An adaptive weighting mechanism dynamically prioritizes control objectives in response to system conditions such as renewable intermittency and grid disturbances. To improve long-term reliability, the strategy introduces state diversity enforcement and inactivity penalties, reducing capacitor stress without compromising harmonic performance. The effectiveness of the proposed method is evaluated using a dynamic equivalent model of a proton exchange membrane (PEM) electrolyzer, enabling a realistic assessment of green hydrogen production. Validation through hardware in the loop (HIL) test demonstrates robust current control and stable DC-link voltages in varying operating scenarios.

The operation of residential energy hubs with multiple energy carriers (electricity, heat, mobility) poses a significant challenge due to different carrier dynamics, hybrid storage coordination and high-dimensional action-spaces. Energy management systems oversee their operation, deciding the set points of the primary control layer. This paper presents a novel 2-stage economic model predictive controller for electrified buildings including physics-based models of the battery degradation and thermal systems. The hierarchical control operates in the Dutch sequential energy markets. In particular common assumptions regarding intra-day markets (auction and continuous-time) are discussed as well as the coupling of the different storage systems. The best control policy it is best to follow continuous time intra-day in the summer and the intra-day auction in the winter. This sequential operation comes at the expense of increased battery degradation. Lastly, under our controller, the realized short-term flexibility of the thermal energy storage is marginal compared to the flexibility delivered by stationary battery pack and electric vehicles with bidirectional charging.

This article provides a comprehensive review of power electronics converter control and energy management for hydrogen production systems through water electrolysis. Hydrogen production from renewable energy sources is a key pathway toward decarbonizing energy systems and enabling large-scale energy storage. Efficient and dependable operation necessitates addressing the dynamic properties of electrolyzers, the intermittent nature of renewable sources, and the coordination among numerous power electronic interfaces. Unlike earlier studies that addressed these aspects separately, this review systematically connects electrolyzer modeling, converter design, control architectures, and energy management to reveal their critical interdependence. By examining these connections, the analysis reveals critical research gaps in real-time coordination, parameter adaptation, and scalable architectures, outlining pathways toward intelligent and grid-independent hydrogen production systems. This review integrates electrolyzer modeling, power converter control algorithms, AC and DC energy hub architectures, hierarchical control schemes, and energy management systems from classical to advanced methods.

This work presents a downscaled validation of a medium-voltage, medium-frequency transformer (MFT) concept designed for high-current operation on the secondary side using multiple parallel paths. The design is based on a modular winding approach, which simplifies the construction process and conductor placement on the bobbin. A systematic design and optimization procedure is developed, combining analytical calculations and finite-element simulations to explore the mass-efficiency tradeoff and to select a candidate design that meets specified leakage inductance and loss targets. The developed prototype serves as a proof of concept, demonstrating that the electrical, magnetic, and insulation requirements of the full-scale MFT can be effectively verified at reduced power levels. The fabricated prototype is tested under short-circuit and partial discharge conditions. The impedance measurements confirmed the expected resonance behavior, and the partial discharge test results verified sufficient insulation performance under high-voltage stress. The results provide experimental evidence for the scalability and feasibility of the proposed transformer design and offer guidelines for the use of 3D-printed supports, grain-oriented electrical steel cores, and windings in medium-voltage, MFT systems for hydrogen production applications.

This paper presents a practical approach to reduce the size of medium-frequency, medium-voltage dry-type transformers through the innovative use of semiconductive screening. The proposed method minimizes the required air gaps, a critical aspect of dry-type transformer design, particularly for medium-frequency applications. Analytical approaches and Finite Element Method (FEM) simulations in COMSOL are used to demonstrate how to achieve a uniform electric field distribution within the transformers. Experimental investigations by means of partial discharge measurement on a prototype epoxy-based stress cone termination with a semiconductive shield are conducted. The results demonstrate the potential for this method to enhance transformer performance and provide a foundation for further advancements in medium-frequency transformer design.

In dual active bridge (DAB) converters, series inductor and transformer functionalities are integrated into a single magnetic core structure to improve efficiency or power density. Allowing independent tuning of this integrated series inductance and magnetizing inductance gives higher design flexibility. However, the existing integrated magnetic methods often lower magnetizing inductance, compromise the transformer winding coupling, require complex custom core designs, or cannot effectively decouple transformer and inductor fluxes in the case of separate transformer and inductor windings. To overcome these problems, this article proposes a unified core structure that allows independent tuning of series inductance without the above-mentioned limitations. To demonstrate the performance of the proposed integrated structure, a DAB converter for a dc–dc electric vehicle charging application is built, and the proposed integrated structure is compared with discrete transformer and inductor structures under identical core volume and thermal steady-state conditions. It is experimentally validated that for the proposed structure at a high output voltage and high load conditions of 450 V and 9 kW, the magnetic power loss reduction is 8.8%, whereas, at a low output voltage and high load conditions of 250 V and 7 kW, the magnetic power loss reduction is 13.0%. Furthermore, this article presents an iterative design methodology based on the derived reluctance and analytical models to systematize the design process.

Many DC energy solutions have emerged as potential candidates to enhance the electrical infrastructure in a localized approach, allowing future expansion in the transportation sector despite the congestion of the utility grid. However, the risk of designing large power converter units as controllable substations in complex networks, such as electric railway systems, has encouraged the sophistication of modeling and testing tools. This paper presents a high-fidelity, real-time model implementation of a controllable substation for DC traction power systems. This representative model is developed to facilitate the testing of different upgrading options to understand and quantify how these changes will affect the system and, more importantly, which features are critical to further increasing the sustainability of the railways. This is applied to a case study of the Dutch railway system in Wierden. It is found that while controllable substations can reduce voltage drops from an average of 400 V to only about 230 V, the benefit they bring in regenerative braking harvesting does not outweigh the investment costs, calling for further investigation of energy storage systems as another potential solution.

This study presents a current balancing technique for high-current windings in medium-frequency transformers (MFTs), particularly relevant to solid-state transformer (SST) applications. Handling high currents on the low-voltage high-current winding of MFTs is challenging due to skin and proximity effects. Conventional techniques, such as continuously transposed conductors (CTCs) and parallel winding paths, are applicable but have limitations in medium-and high-frequency applications such as SSTs due to skin and proximity effects. To address these issues, a modular and tunable compensation method is proposed, based on adding small, series-connected inductive elements (compensation toroids) to each parallel winding path. Experimental results from a prototype validate the proposed compensation technique, highlighting its effectiveness in mitigating unbalanced current distribution. Finite element analysis (FEA) and experimental validation across a wide frequency range (1–10 kHz) confirm the effectiveness of the method. The results demonstrate a significant reduction in current imbalance with minimal added losses or system impact.

In a dual active bridge converter, the split series inductance configuration with finite magnetizing inductance can provide an additional degree of freedom to optimize the converter's performance. However, this magnetic configuration results in three separate magnetic structures, which increases the volume and footprint. To address this issue, this article proposes a four-winding integrated magnetic structure comprising decoupled primary inductance, secondary inductance, and a transformer capable of independent tuning. The fluxes produced by primary and secondary inductors within the integrated structure consistently oppose in the middle leg of the inductor core, resulting in reduced losses and a smaller volume. A design methodology based on an analytical model has also been developed to systematize the design process. A sensitivity analysis is performed using the finite element method to verify the decoupling operation. An 11 kW, 775 V/450 V prototype is implemented, and the integrated magnetic structure is compared with its discrete implementation under steady-state thermal conditions at different ambient temperatures. A volume reduction of 12.1% and magnetic loss reduction of 4.5% is achieved, while the converter efficiency remains higher or comparable to that of the discrete implementation across the entire operating range.

Rising grid congestion raises concerns that conventional grid expansion may not keep pace with projected increases in demand and renewable generation. This research proposes a supplementary solution: leveraging the inherent mobility of Electric Vehicles to enable energy transfer within different locations. Through an analytical modelling approach, a stochastic energy transport model using Monte Carlo sampling is developed. This model generates synthetic weekly charging and driving profiles to quantify the energy transport potential of private EV fleets, accounting for battery capacity, mobility patterns, and energy consumption. Building on this concept, the study introduces Flexible Energy Communities (FlexECs), where members share the same living location but commute to different workplaces or vice versa. By enabling electric vehicles to charge at one location and discharge at another during routine daily travels, Flexible Energy Communities exploit private EV mobility as a mechanism for spatial energy transfer, extending Energy Community operation beyond purely grid energy exchange.Results reveal that approximately 35 kWh, equivalent to 60% of the total energy stored in the EV battery at the time of departure, can be discharged upon arrival. Additionally, when charging patterns are optimized, up to 30 kWh, representing 70% of the energy charged prior to the journey, can be effectively transported and discharged at the destination. By quantifying the impact of EV-imported energy on cost, peak demand, and overall energy consumption reduction, this study underscores the potential of EVs as dynamic energy transporters, providing a technical foundation for energy sharing through private EVs daily travelling patterns.

Electric aircraft represent a promising lowemission alternative to conventional fuel-powered aviation. This study proposes a battery sizing method for small all-electric aircraft using an electro-thermal battery cell model, considering different flight segments based on a reference commercial aircraft. The experiment is conducted to verify the proposed electro-thermal battery cell model. It considers varying battery efficiency throughout the flight mission, highlighting the importance of battery efficieny in the design process.

This study addresses a 1.8kV bilateral feeding system for DC railway applications, composed of multi-pulse diode rectifiers at both ends and a storage unit with a DC/DC converter located at an intermediate station. The storage system introduces an additional degree of freedom to control power flows by applying a specific voltage at a strategic point between the passive rectifiers. This paper formulates a voltage compensation problem aimed at reinforcing the network while minimizing conduction losses along the catenary. Due to the nonlinear nature of the power balance equations, a closed-form analytical solution is not directly obtained. To overcome this, the paper proposes an approximation method for the pantograph voltage to enable an analytical formulation of the optimization problem. A comparison between the proposed analytical approach and a numerical iterative optimization method is presented and discussed.

This study proposes a model predictive control (MPC) strategy integrated with closed-loop space vector modulation (CL-SVM) for a three-phase, three-level neutral point clamped (3L-NPC) rectifier supplying two alkaline electrolyzers connected in series. Electrolyzers present a nonlinear and dynamically varying load due to their dependence on temperature, pressure, and electrochemical reaction rates, imposing strict requirements on the stability and responsiveness of the power supply. Among, multi-level converter topologies, the 3L-NPC rectifier is a promising candidate for low to medium-voltage, high power applications due to its reduced harmonic distortion, improved high power handling, and balanced trade-off between complexity and performance. However, maintaining DC-link capacitor voltage balance under dynamic loads remains challenging, risking power quality and system reliability. The proposed approach optimizes voltage vector selection to regulate DC output and minimize neutral-point voltage deviation. Simulation results in MATLAB/Simulink confirm the effectiveness of the designed controller in achieving stable DC voltage and a balanced neutral-point voltage, thereby enhancing the overall performance of the power-electronics interface in electrolyzer applications.

The development of lithium-ion batteries has experienced massive progress in recent years. Battery aging models are employed in advanced battery management systems (BMSs) to optimize the use of the battery and prolong its lifetime. However, Li-ion battery cells often experience fluctuations in battery capacity and performance during cycling, which makes capacity prediction more difficult. Moreover, the reason for the capacity regeneration phenomenon occurring after resting periods is not clear yet, as well as the influence of cycling conditions on capacity regeneration. A relationship between this phenomenon to cycling state of charge (SoC) ranges and current rates was investigated in this article on a battery cell with lithium nickel manganese cobalt (NMC) oxide positive electrode. Experimental results show that the capacity increase is a consequence of decreased internal impedance after the resting period. The experiments also showed that a significant power drop and subsequent power regeneration after a resting period occurs only for specific SoC ranges, and applying a resting period after battery cycling can mitigate this power fading process. The semi-empirical model of battery degradation including capacity regeneration is proposed in this article based on physical processes inside of the cell retaining low computational requirements. The acquired results can be utilized in BMSs for more accurate state of health (SoH) estimation and to prolong battery lifetime.

The compensation and high-efficiency operation of the multimodular inductive power transfer (IPT) systems has been a challenge because of the inter- and cross-coupling between modular charging pads. This article analyzes the series–series (S–S) compensation and the associated bifurcation problem in multimodular IPT systems based on closed-form analytical modeling of the coupled circuits. From the analytical results, an improved compensation tuning method for multimodular systems is demonstrated. This improved compensation addresses the intercoupling between coils on the same side, in addition to the self-inductance of the charging pad. As a result, the system’s efficiency improves while also saving an extra capacitor compared with other circuit-based decoupling methods. In addition, a design guideline based on the sum of the coupling coefficients including cross-coupling is derived to avoid bifurcation. The phase angle of the input impedance is studied under various scenarios, demonstrating the validity of the proposed design guideline. Experimental results on a downscaled prototype show that the improved compensation method enhances efficiency by more than 2% compared with scenarios where intercoupling is not compensated, and verification of the proposed bifurcation mitigation guideline.

Properly addressing uncertainties in reliability analysis is essential for realistic lifetime predictions of power devices. This paper investigates parameter uncertainties on the lifetime estimation of power devices using an empirical lifetime model and Monte Carlo simulations. Key parameters such as junction temperature swings (ΔT _j), minimum junction temperature (T _{j, min}), and lifetime model constants are analyzed for their impacts on lifetime outcomes. Sensitivity analysis reveals significant effects from variations in parameters like β ₁ and ΔT _j on the expected lifetime and its variability. Simultaneous variations across all parameters further highlight the dominant influence of β ₁ on lifetime predictions. The analysis suggests that a 5 % uncertainty margin appears to offer a balanced trade-off between realistic lifetime estimations and predictability. This Study underscores the importance of considering parameter uncertainties for precise reliability evaluations. It addresses a critical gap by examining the rationale behind commonly assumed 5 %, and 10 % uncertainty margins in lifetime modeling. By systematically evaluating these margins’ impacts on key reliability parameters, the study provides a framework for selecting reasonable assumptions based on physical insights and variability analysis, advancing the reliability modeling of power devices.

The study presents Electric Vehicle (EV) Point-of-View (POV) Vehicle to Grid (V2G) optimisation, where the system knows the trips and energy demand of the EV. This allows it to be less conservative in the departure State of Charge (SoC) of the EV battery. The peak and cost reduction of Vehicle POV optimisation are compared with state-of-the-art Location Point-of-View optimisation, this is, the car can do V2G but it has to depart each location with at least 80% SoC as the next trip energy demand is unknown. A Mix Integer Linear Programming (MILP) V2G optimisation approach is presented to reduce peak demand and total system cost of a fleet of EVs travelling between several residential locations and one common workplace. Simulations were conducted with 26 EVs unevenly distributed between five residential locations and commuters to a common workplace. The results indicate little differences in the reduction of peak demand between both POVs of V2G optimisation. However, the system cost can be further reduced with Vehicle Point-of-View optimization, saving an additional 200 euros annually per household by transporting cheaper energy from workplaces to residential locations.

This paper presents a data-driven control framework to improve the stability and optimize the performance of DC-DC boost converters supplying constant power loads (CPLs). The inherent negative impedance and non-linear characteristics of CPLs pose significant stability challenges in power electronic systems. To address these issues, this study evaluates the performance of data-driven integrator (I) and linear quadratic integral (LQI) controllers, both optimized using iterative feedback tuning (IFT), that eliminates the need for an explicit system model. The proposed controllers are systematically compared against conventional model-based designs to assess their effectiveness. Key dynamic challenges, including converter non-linearity, CPLinduced instability, and measurement noise, are considered in the analysis. Simulation results demonstrate that the data-driven LQI and I controllers achieve superior tracking accuracy, robustness, and stability. These findings underscore the advantages of datadriven control methodologies in ensuring reliable and efficient operation in practical power electronic applications.