In dual active bridge (DAB) converters, the external series inductor is often placed on the high-voltage side to reduce its losses, but in this configuration, the transformer magnetizing inductance is excited by the reflected voltage of the low-voltage port. This configuration can lead to higher transformer core losses for the DAB converter. However, in a split inductor configuration, the magnetizing current is supplied by both the high-voltage and low-voltage side bridges, reducing the volt-seconds across the magnetizing inductance and therefore reducing core losses. In this work, an analytical expression for the transformer magnetization voltage is presented, and the reduction in transformer core loss achieved by using a split inductance configuration is calculated. An 11kW, 775V/450V prototype is implemented, and both magnetic configurations are experimentally compared under identical volume and thermal conditions for a wide power range at 450V. Under steady-state thermal conditions at 450V and 11kW, the split-inductance configuration achieves up to a 5.88% reduction in total converter losses and an 18.3°C decrease in the worst-case transformer core temperature compared to the high-voltage-side inductance configuration.

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.

Power control systems (PCSs) can exploit low-carbon technologies (LCTs) to provide grid ancillary services. This work develops a bilevel mixed-integer linear programming PCS of photovoltaics (PVs), electric vehicles (EVs), heat pumps (HPs), and battery energy storage systems (BESS), for providing automatic frequency restoration reserves (aFRR) with energy arbitrage, PV self-consumption, and customers’ thermal and charging comfort. The contribution of the BESS and the flexible loads is evaluated under different seasons, grid types and sizes, and energy/reserve prices. Validating against a PCS solely for minimum grid energy cost (energy arbitrage), the findings demonstrate the increased cost savings when a PCS participates in the reserve market with BESS and EV combined. The cost of solely energy arbitrage was found consistently higher than 100% (e.g., 40€ compared to only 19€ with aFRR provision). These benefits have become more important recently in 2023, with the higher energy prices, and much higher reserve prices compared to 2018 (up to 540% increase). While the always present BESS is able to contribute more to ancillary services compared to the uncertain EV fleets, the contribution of EVs increased to a notable 38.5% of the total provided aFRR energy share at larger grids. Finally, mixed nodes that comprise both residential-commercial buildings and home-public chargers have a higher potential for ancillary services provision, demonstrating a 5x and 12x higher potential compared to residential and commercial nodes, respectively. Overall, this work highlights the importance of PCSs in large grids or with a variety of loads to provide ancillary services for enhanced savings.

Batteries with silicon-graphite-based anodes, which offer higher energy density and improved charging performance, introduce pronounced voltage hysteresis, making state-of-charge (SoC) estimation particularly challenging. Existing approaches to modeling hysteresis rely on exhaustive high-fidelity tests or focus on conventional graphite-based lithium-ion batteries, without considering uncertainty quantification or computational constraints. This work introduces a data-driven approach for probabilistic hysteresis factor prediction, with a particular emphasis on applications involving silicon-graphite anode-based batteries. A data harmonization framework is proposed to standardize heterogeneous driving cycles across varying operating conditions. Statistical learning and deep learning models are applied to assess performance in predicting the hysteresis factor with uncertainties while considering computational efficiency. Extensive experiments are conducted to evaluate the generalizability of the optimal model configuration in unseen vehicle models through retraining, zero-shot prediction, fine-tuning, and joint training. By addressing key challenges in SoC estimation, this research facilitates the adoption of advanced battery technologies.

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.

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.

The accelerating electrification of transport, alongside the rapid growth of decentralized renewable generation, is increasing stress on distribution grids due to rising demand and generation peaks. While electric vehicles (EVs) are often seen as an additional burden, their batteries can be leveraged through Vehicle-to-Grid (V2G) to support grid flexibility. However, existing V2G research almost exclusively treats EVs as stationary storage resources, providing services only at a single charging location. This overlooks the unique mobility of EVs and the potential to deliver energy services at different nodes throughout the day, referred to in this work as Locational V2G.This paper introduces a modeling framework that integrates Locational V2G with grid operation to evaluate how EVs can improve system performance when (dis)charging at multiple nodes and not only at home. A real low-voltage distribution grid from the SimBench dataset is used to assess several scenarios with different EV penetration levels. Results show that enabling EVs to provide V2G services across locations consistently increases V2G revenue while maintaining voltage levels and line congestion within operational limits. These findings highlight the added value of exploiting EV mobility as a flexibility resource for distribution networks.

In the context of building electrification, the operation of distributed energy resources integrating multiple energy carriers (electricity, heat, mobility) poses a significant challenge due to the nonlinear device dynamics, uncertainty, and computational issues. As such, energy management systems seek to decide the power dispatch in the best way possible. The objective is to minimize and balance operative costs (energy bills or asset degradation) with user requirements (mobility, heating, etc.). Current energy management uses empirical battery ageing models outside of their specific fitting conditions, resulting in inaccuracies and poor performance. Moreover, the link to thermal systems is also overlooked. This paper presents an ageing-aware nonlinear economic model predictive controller for electrified buildings that incorporates physics-based battery ageing models. The models distinguish between energy storage systems (chemistry, ageing state, etc.) and make explicit the trade-off between grid cost and battery degradation. The proposed algorithm can either cut down on grid costs or extend battery lifetime (electric vehicle or stationary battery packs). Additionally, substituting NMC cells with LFP chemistries optimizes grid performance during the summer, yielding a 10% grid cost reduction and a 20% decrease in degradation. Finally, the grid cost and degradation of the presented MPC when using aged batteries are improved with respect to the state of the art by 10% and 5% respectively, in periods with high solar generation and low thermal loads like summer.

In recent years, the research interest in bidirectional charging of electric vehicles has increased significantly, driven by improved accessibility to charging and payment information as well as the increasing emphasis on integrating variable renewable energy sources more effectively into the grid. Integrating bidirectional charging with the grid/building/home can also reduce grid congestion. Despite this, broader implementation of this technology has not yet been achieved. In this context, this article comprehensively surveys direct current (DC) off-board vehicle to grid/building/home chargers and analyses the gaps which prevent the technologies’ wide implementation. These gaps are analysed by considering areas such as the development direction of bidirectional charging technology, battery cost and its degradation, V2G applicable standards, grid codes and charging protocols, deployment of V2G chargers (off-board versus on-board/wireless), market feasibility of V2G services, and the cost of bidirectional off-board chargers. The first survey of twenty-five commercial bidirectional chargers is presented and investigated in relation to the above-mentioned areas. Four key (technical, regulatory, financial, and behavioural) barriers are identified and discussed for the wide implementation of vehicle to grid/building/home charging.

As freight electrification progresses, the planning of high-power charging infrastructure becomes a critical challenge due to the interaction between time-constrained operations, spatially uneven demand, and limited grid-connection capacity. Current European Union regulation specifies corridor coverage requirements, but does not explicitly account for local demand intensity, station sizing, or grid constraints. This article presents an integrated optimization framework for planning highway charging infrastructure for heavy-duty electric vehicles (HDEVs). The framework combines freight-tour simulation, route- and energy-aware charging event generation, candidate-site identification, and optimization-based station siting, sizing, and event-level scheduling. In addition, a constant-current/constant-voltage (CC–CV) post-processing step is used to obtain more realistic charging durations and aggregate charging profiles. The framework is applied to the Netherlands for 2025, 2030, and 2040 under both demand-driven and regulatory-driven planning paradigms, considering charger ratings of 350 kW and 1 MW. The results show that demand-driven planning achieves full event feasibility on the modelled corridor network, whereas the regulatory-driven planning exhibits a small but persistent feasibility gap due to its more geographically constrained candidate set. Across scenario years, infrastructure expansion follows a two stage pattern, shifting from initial spatial coverage to capacity densification at persistent freight corridors. Sensitivity analysis further shows that 1 MW networks are substantially more exposed than 350 kW networks to grid limits and vehicle-side charging assumptions. Overall, the proposed framework provides a practical decision support tool for designing scalable, cost-effective, and operationally realistic HDEVs charging networks.

Electric aircraft represent a promising low-emission alternative to conventional fuel-powered aviation, driving the demand for lightweight and reliable electrical powertrain architectures. This study presents a design process for an electrical power system with an emphasis on the cabling system and battery in all-electric aircraft (AEA). Design considerations for the cabling system in power distribution architectures are discussed, including cable insulation material selection, conductor choice, sizing, and weight reduction methods. The influence of different system voltages and operating temperatures on cable weight is analyzed to identify optimal design tradeoffs. A comparison of polytetrafluoroethylene (PTFE) and perfluoroalkoxy (PFA) insulation materials, as well as aluminum and copper conductors, highlights their impact on weight and reliability, with PFA offering weight advantages under typical aerospace operating conditions. The batteries are sized based on the energy and power demands of a 90-seater AEA as a case study. After designing the components of the aircraft’s electrical power system, the electrical architectures are presented. Furthermore, a framework for evaluating the electrical power system architectures of AEAs is proposed, using two key criteria: reliability and weight. The weight of the electrical power system is then estimated based on aircraft performance requirements. The proposed framework provides practical guidelines for cable selection and architecture optimization in future AEAs.

Power management systems (PMS) of low-carbon technologies (LCTs) such as PV generation, electric vehicles (EVs), and heat pumps (HPs) battery energy storage systems (BESS) are becoming increasingly important for energy arbitrage and ancillary services provision. In this work, a PMS is developed which is based on optimal dispatch to maximize cost savings, perform direct load control (DLC) for congestion management, and offer frequency regulation reserves while simultaneously optimally allocating BESS capacity in a distribution grid. Results showed that a BESS installation is not economically viable only with energy arbitrage but becomes highly profitable when ancillary services such as frequency regulation are provided. Furthermore, it was shown that a centralized BESS at the closest node to the main grid is the most beneficial solution due to lower power losses, although that also depends on the price profiles and the different flexibilities of the nodes. The importance of a BESS installation and the benefits of its synergy with flexible loads for both system-wide frequency regulation, as well as for direct load control for congestion management, were also proven, increasing DLC and load shifting success rates to always above 90%. In this regard, commercial nodes that are characterized by low flexibility are in the greatest need of a BESS installation if they participate in ancillary services provision.

Distributed generation, such as photovoltaics (PVs), and electrification of heating and transportation with heat pumps (HPs) and electric vehicles (EVs) will play a major role in the energy transition. However, these low-carbon technologies (LCTs) do not come without side effects such as voltage violations, power loss increase, component overloading, higher energy consumption, power peaks, and power quality issues, e.g., harmonics and phase unbalance. This work constitutes a review analysis and summary of all the important findings concerning the various grid impact issues that can appear due to the grid integration of these 3 LCTs. The work also encapsulates various research characteristics such as grid topology, seasons, simultaneous operation under various LCT combinations, penetration levels, etc. Moreover, it incorporates a qualitative analysis of the impact level of the most investigated grid issues and quantitative comparisons between the different grid types and LCTs. It has been shown that the combined integration of PVs-EVs and PVs-HPs can result in mitigation effects without extra solutions. Moreover, voltage deviations and unbalance affect more the rural grids while component overloading is more hazardous for suburban grids. Finally, proposed mitigation solutions, such as energy storage, smart charging, etc., are correlated with their respective grid impact issues.

The growing demand for compact, reliable, and high-efficiency power conversion systems has spurred the need for the development of power-dense magnetic solutions. This paper introduces a design algorithm utilizing an improved magnetic equivalent circuit (MEC) model for an integrated magnetic structure, which provides a more accurate and computationally efficient approach to capturing complex magnetic interactions. The proposed MEC-based design algorithm shows promising results in predicting the different reluctances, resulting in optimal magnetic design parameters. The effectiveness of the methodology is demonstrated through the design of an integrated structure for a 12.5kW, 50kHz dual-active bridge converter, wherein the energy-transfer series inductor and high-frequency transformer are seamlessly integrated into a single magnetic structure hereafter referred to as the Integrated Magnetic Transformer (IMTx).

Quasi-resonant boundary-conduction mode (QR-BCM) and triangular current mode (TCM) have found widespread use in the literature and industry due to their good performance at relatively low complexity. However, additional control challenges occur when these modulations are applied to the four-switch buck-boost (FSBB) converter, due to a discontinuity in switching frequency in multimode operation. This article presents the first closed-loop operation of a variable-frequency, multimode, quasi-resonant BCM control scheme including smooth mode transitions. The proposed control utilizes feed-forward mode transition techniques, based on software interrupt handlers integrated into the digital control scheme. In contrast to most soft-switching schemes in the literature, the proposed digital control does not imperatively rely on high-frequency current measurements but uses dc measurements and high-frequency voltage measurements instead. A 10 kW prototype is developed with which the proposed modulation is compared with three other soft-switching modulation schemes. Our results indicate that the losses of FSBB converter can be reduced by up to 60% using the proposed modulation. Especially at partial powers and high voltages, significant efficiency gains can be achieved.