This article proposes a transformerless, capacitively isolated converter based on a full-bridge topology with phase shift control. Compared to the existing capacitively isolated converters, the proposed design offers the advantage of zero mean voltage across the isolating capacitors, thereby reducing voltage stress. A comprehensive analytical model is developed to describe the converter’s operation in both continuous and discontinuous conduction modes. The model is validated through an experimental prototype tested at power levels up to 6 kW and switching frequencies up to 500 kHz, achieving a peak conversion efficiency exceeding 98%. The experimental results confirm the accuracy of the theoretical model and waveforms.

Highly self-sufficient energy hubs offer a promising solution to mitigate grid congestion in favor of grid operators and to reduce grid fees for the benefit of energy hub operators. Meanwhile, the energy hub's capacity may far exceed the grid connection capacity, creating a weak grid situation. As a result, power quality issues such as voltage fluctuations, frequency deviations, and even instability may occur. In this work, a grid-forming energy storage system (GFM-ESS) is integrated to address these potential problems. A model of the GFM-ESS and energy hub is established based on a 50 kW PV-Hydrogen energy hub demonstrator, where PV-generated power is utilized for green hydrogen production. A trade-off design is proposed to identify the optimal balance between the capacity of the GFM-ESS and the grid connection. The voltage and frequency response at the hub's bus are analyzed to evaluate this trade-off. While experiments with the 50 kW demonstrator are ongoing, simulation results are provided to validate the effectiveness of the proposed design.

In electric vehicle (EV) charging stations, a common approach to charge multiple EVs is to utilize a shared DC bus for all the converters. However, as the scale of the station grows, this method leads to increased complexity and higher expenses due to the growing number of components. This paper proposes a novel AC multiplexed wireless power transfer (WPT) topology, in which charging modules are connected in parallel on the AC side of a single converter via a highly coupled multi-winding transformer. This topology reduces costs and enables multidirectional power flow for V2X (vehicle-to-vehicle and vehicle-to-grid) applications. In this paper, a comprehensive introduction to the AC multiplexed WPT system is presented, followed by an analysis of its multidirectional power flow characteristics. Finally, a three-port prototype was developed to validate theoretical analysis.

Modular Multilevel Converters (MMCs) offer significant advantages in the medium to high-voltage settings. The modular architecture of MMCs allows for redundant submodules (SMs) to improve overall reliability. These redundant SMs can be deployed using various redundancy strategies, such as Load-Sharing Active Redundancy Strategy (LS-ARS), Fixed-Level Active Redundancy Strategy (FL-ARS), and Standby Redundancy Strategy (SRS). The primary contribution of this paper is the introduction of guidelines for applying Monte Carlo Simulation (MCS) and a comprehensive methodology for its application across various redundancy strategies. This enables precise planning of preventive maintenance and estimation of the number of faulty SMs with a specific lifespan in the MMC. More importantly, MCS is applied to estimate the reliability of the MMC applying Mission Profile for SRS and LS-ARS where analytical solutions are unavailable. An analysis of uncertainty and the applicability of MCS is also presented to demonstrate the advantages of MCS over analytical methods. The computational time required for applying MCS across different redundancy strategies and arm levels is also assessed.

High-power flexible dc links employ modular multilevel converters (MMC) for compact active power redirection in medium and high voltage grids. During contingencies, such converters may need to provide an enhanced active power capacity to avoid overload in vulnerable grid locations. This paper achieves this target by using the capacitor voltage ripple margin of the MMC submodules (SM) to enhance the dc voltage beyond the rated value. This voltage enhancement enables the enhanced active power capacity of the MMC while maintaining rated electro-thermal stresses on the components. Moreover, dynamically varying the dc side voltage reduces the MMC's circulating current, improving its operating efficiency. Because the average capacitor voltage is controlled to remain constant, the overall stresses and harmonic performance of the enhanced MMC remain the same as in the base case. In this paper, the analytical expressions for the voltage and power enhancement limits are derived, revealing a dependence on the grid-injected reactive power. Furthermore, a controller is designed to achieve stable operation during transient conditions when the power enhancement is carried out. Finally, the enhancement concept is validated using simulations and experiments with a down-scaled laboratory MMC prototype.

Low-carbon technologies (LCTs) such as Electric vehicles (EVs), heat pumps (HPs), and PV systems increase phase unbalance due to uneven phase distribution. Phase unbalance can lead to overheating, suboptimal capacity utilization, and power losses. This work analyzes the unbalance impact inflicted by the grid integration of PVs, HPs, and EVs under different combinations and penetration levels. The main novelty of this study is the use of different types of real-world distribution grids (rural, suburban, and urban) for the LCT unbalance impact comparison, while simultaneously considering the influence of several unbalance factors; LCT phase connections and grid distributions, the seasonal effect, and the power and consumption levels, the latter of which have been evaluated as mitigation strategies. The results showed that the combined integration of PVs, EVs, and HPs can cause high voltage unbalance, especially in grids with high existing loading. The seasonal effect was the most impactful unbalance factor, intensifying unbalance by the integration of PVs-HPs and PVs-EVs combinations during Winter and Summer, respectively. Furthermore, reductions in the power and consumption levels of the LCTs decreased the unbalance total violation duration in a range between 11% and 25% for all distribution grids. Reducing the LCT consumption levels also decreased the unbalance magnitude, which reached up to 15% for the urban grid under 100% HP and PV penetration. Finally, it was found that consumption duration enhances unbalance, such as the peak power levels, because it increases the simultaneity of technologies operating in different phases.

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.

To tackle the potential grid overloading issue induced by excessive Electric Vehicles (EV) charging demand, a Low Voltage (LV) grid congestion management algorithm with three centralised EV charging management schemes is proposed in this study. The developed algorithm integrates grid information and aims at tackling the foreseen congestion issues by operating on the EV charging processes. This is done through linear programming (LP) or iterative calculations. While the first charging scheme aims at managing the congestion by only affecting the elements with the greatest influence on the congestion, the other two aim at ensuring impartiality towards all users and the overall energy transfer to the EVs, respectively. The simulated results are compared in terms of performance criteria such as grid impact, user satisfaction and fulfilment of charging energy demand. Overall, this study shows that the first scheme brings the best results from a grid perspective. On the other hand, the last scheme leads to competitive results from a grid point of view and the best overall results from a user perspective.

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.

This article presents an extended hybrid modulation (EHM) technique to achieve multistage constant-current (MSCC) charging of electric vehicles using wireless power transfer (WPT) technology. Although most research focuses on constant-current constant-voltage charging, MSCC charging offers key advantages, such as lower temperature rise, decreased charging time, and prolonged battery lifespan. However, the existing phase-shift-modulation (PSM) method encounters substantial circulating reactive power and significant efficiency drops in MSCC charging. To overcome this, an EHM strategy is proposed to expand the modulation range of PSM. By applying EHM to both the inverter and active rectifier, the proposed method provides up to 16 operating modes to facilitate multiple CC outputs. Furthermore, an optimal mode trajectory, specifically designed for the MSCC charging, is developed. By implementing this trajectory across different charging stages, zero-voltage-switching is achieved for all power switches, and the overall power loss of the system is minimized. Finally, a WPT prototype was developed to validate the proposed approach. Experimental results demonstrate that the proposed approach effectively enables the MSCC charging while notably enhancing transmission efficiency, achieving dc-to-dc efficiencies between 92.45% and 95.67% across a power range of 231 to 3.015 kW.

Modular multilevel converters (MMCs) are widely used in various applications due to their scalability, efficiency, and fault-tolerant capabilities. This article proposes a fault-tolerant methodology tailored for full-bridge (FB) submodules (SMs) in MMCs to enhance system reliability under open-circuit faults (OCFs) in insulated-gate bipolar transistors (IGBTs). The method adopts a hybrid approach, using control logic adjustments to reconfigure faulty SMs into half-bridge (HB) configuration for T2/T3 faults while employing redundant SMs for T1/T4 faults. Accurate fault detection and localization are achieved through established methods, such as state observers and voltage comparisons. It is shown using MCS that the proposed method can improve the 17 kV 10 MVA converter reliability by almost 25% over solely redundancy-based solution for given lifetime requirements. Finally, using a lab-scale FB MMC prototype, it is experimentally shown that the proposed reconfiguration technique can successfully localize the fault and revert to normal operating requirements by shifting from FB to HB SM configuration in approximately 20 ms of fault initiation.

The growth of suburbs is a challenge for public transport, and new tools are needed to electrify suburban and intercity bus lines sustainably. In-motion-charging (IMC) buses combine the advantages of both trolleybuses and electric buses. This paper analyses a case of using IMC buses on a 17-km-long intercity route service between Arnhem and Wageningen in the Netherlands. The analysis covers different traction battery technologies, sizes, and charging strategies to find the economically optimal solution. The study was carried out using a numerical model of an IMC bus, which was validated and tuned based on year-round experimental recordings obtained from Arnhem trolleybuses. The model outputs were next used to analyse the batteries ageing under specific charging-discharging current profiles. The analysis shows that the most long-term cost-effective solution for the considered case consists of using merged IMC and opportunity charging as well as a 90 kWh LTO battery, whose expected lifetime would be more than 14 years.

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.

Grid-following control (GFL) has been widely implemented as the dominant control method for inverter-based resources (IBR). However, because GFL cannot provide sufficient inertia for frequency regulation, grid-forming control (GFM) is proposed as an alternative solution. However, the impact of grid dynamics characteristics on GFL and GFM control is rarely discussed. Therefore, this paper systematically derives and compares the frequency response of GFL and GFM control, considering the grid dynamics that are emulated by a synchronous generator. The impact of the inertia of GFM is investigated by pole-zero maps.

Targeting a climate-neutral maritime sector drives the adoption of the all-electric ship (AES). While AESs can utilize both ac and dc shipboard power systems (SPS), a dc system offers advantages in efficiency, power density, and source synchronization. However, the enhanced network complexity of dc grids combined with the high penetration of power electronic devices and harsh environmental conditions can compromise the system's reliability. Therefore, this article provides an overview of the reliability aspect of dc-SPSs, addressing the power system design, adequacy assessment, and reliability improvement. First, the performance tradeoffs associated with the SPS design are examined, revealing how changes in the power system topology and dc bus structure impact the vessel's reliability along with other performance parameters. Second, a hierarchical reliability model framework is proposed for the adequacy assessment of dc-SPSs, considering the reliability from the component level up to the system level. To determine the system-level reliability, multiple probabilistic methods, including simulation and analytical models, are compared using a propulsion subsystem example. Finally, an overview of the reliability improvement strategies is provided, addressing methods at the system, device, and component level. These three topics combined aim to provide guidance in the design of future reliable dc-SPSs.

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.

Due to the increasing requirement of charging power for electric vehicles, especially heavy-duty electric vehicles (HDEVs), this paper proposes novel matrix converter-based three-phase medium voltage AC (MVAC) grid-connected modular high-power wireless charging systems. The stiff DC-link absent power transfer from low-frequency AC to high-frequency AC is achieved by the full-bridge direct matrix converter (FBDMC). The cascaded FBDMC structure is proposed to achieve the MVAC grid connection. The three-phase coupler is used here to generate the rotating magnetic fields to achieve higher transfer capability and power density. The second and third grid harmonics can be cancelled due to the nature of the FBDMC and three-phase system, which results in significantly less DC-link current ripple compared to single-phase wireless charging systems. Several novel connections between FBDMCs and coils are proposed to provide more flexibility and multiplexity for WPT charging. The topology is verified by the simulation in PLECS and by a down-scale experiment setup.

A fast and efficient charging infrastructure has become indispensable in the evolving energy landscape and thriving electric vehicle (EV) market. Irrespective of the charging stations’ internal alternating current (AC) or direct current (DC) bus configurations, the main concern is the exponential growth in charging demands, resulting in network congestion issues. In the context of exponential EV growth and the provision of charging facilities from low-voltage distribution networks, the distribution network may require frequent upgrades to meet the rising charging demands. To avoid network congestion problems and minimize operational expenses (OE) by integrating energy storage systems (ESS) into ultra-fast charging stations (UFCS). This paper presents a techno-economic analysis of a UFCS equipped with a battery ESS (BESS). To reduce reliance on the electric grid and minimize OE, a dual-objective optimization problem is formulated and solved via grid search and dual-simplex algorithms. Analytical energy and physical BESS models are employed to evaluate the optimization matrices. The intricacies of BESS aging are examined to ensure an optimal BESS size with a more extensive lifespan than the corresponding payback period. The integrated BESS significantly reduced reliance on the grid to tackle network congestion while fulfilling charging demands. The dynamic pricing (DP) structure has proven more favorable, as the average per unit cost remains lower than the static tariff (ST). Results illustrate that integrating BESS reduces the OE and peak-to-average ratio (PAR) by 5-to-49% and 16-to-73%, respectively. Moreover, the combination of 70% BESS and 30% grid capacities outperforms the other configurations with a 73% reduction in PAR and a 49% reduction in OE before BESS reaches the end-of-life.

The increasing number of electric vehicles (EVs) means both a challenge and an opportunity for the electric grid. Different charging algorithms have been proposed in the literature to tackle these specific challenges and make use of the potential services that EVs can provide. However, to properly investigate the conflicting objectives, a multi-objective approach is paramount. These algorithms provide a family of solutions instead of just one, so the decision-maker can see the connection and trade-offs between the objectives. This paper proposes a highly customisable multi-objective framework based on an expanded version of the augmented ε-constraint 2 method. Together with a mixed integer linear programming (MILP) formulation, it is used to solve a charging station scheduling problem. An energy management system (EMS) executes the calculated schedules to show the effect on the individual EVs. Numerical simulations based on market and EV data from the Netherlands demonstrate the adaptability and effectiveness of the proposed algorithm.

Electric aircraft represent a promising low-emission alternative to fuel-powered aviation. As the energy source, the battery pack must guarantee key performance metrics such as energy density, power density, lifetime, and safety. Among these, energy density is particularly critical as it directly impacts the range and payload capacity. Additionally, the battery thermal management system (BTMS) of the battery pack is essential to maintain safety, efficiency, and lifetime. Hence, to design a battery pack with improved energy density and optimized thermal and aging performance, a complete electro-thermal-aging (ETA) model at both cell and pack levels is developed to predict pack behavior under operational conditions. Simulations demonstrate that the proposed model achieves an accurate thermal prediction accuracy within 0.87°C during an example all-electric aircraft (AEA) mission profile. Optimization based on the proposed model is conducted, focusing on geometric configurations of the battery pack and coolant flow parameters, including channel wall thickness (L_Al), inlet width (W_cl), cell spacing (D_cell), package wall thickness (L_enc), inlet flow temperature (T_cl,in), and flow velocity (U_cl,in). An optimized liquid-cooled battery module using Samsung 18650-35E cells is designed with [L_Al, W_cl, D_cell, L_enc] = [0.4, 1.6, 20, 0.5]mm, T_cl,in =35°C, and U_cl,in = 0.05ms^-1 during cruise and 0.02ms^-1 during takeoff, climb, and descent. This configuration achieves a maximum temperature of 41.76°C and a maximum cell-to-cell temperature difference of 3.11°C, improving thermal uniformity. The lifetime performance also demonstrates a 5.51% improvement in state-of-health (SOH) after 180 cycles. Based on the module-to-pack structure analysis, the battery pack exhibits energy densities of 227.01Wh kg^-1 gravimetrically and 353.67Wh L^-1 volumetrically. This study facilitates the guideline for compact and lightweight liquid-cooled battery pack design with improved thermal and aging performance for AEA applications.