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.

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.

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 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 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.

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.

Lithium-ion batteries (LIB) are widely used in various applications. The LIB degradation curve and, most significantly, the knee-point and End-of-life (EoL) point identification are critical factors for the selection of the appropriate application, such as electric vehicles and stationary energy storage systems, due to their effect on performance and lifespan, safety, and environmental footprint. Linear degradation models can be inaccurate in capturing the highly nonlinear behavior of LIB degradation caused by multiple simultaneous degradation mechanisms. Hence, this work first analyzes the main different mechanisms, their causes, and their interrelations. Secondly, the various single- and multi-mechanism physics-based (PB) and data-driven (DD) models for LIB degradation and knee-point identification are summarized and compared regarding their prediction performance on degradation and transition from stabilized to saturated aging. While single-mechanism PB models can be effective in the LIB first-life prediction, they can seriously undermine the knee-point and saturated aging. Moreover, the modeling of the different aging mechanisms can significantly increase the complexity of the multi-mechanism PB models. Finally, while DD models for LIB degradation have been developed, a DD model focused on knee-point identification and LIB second-life is still missing from the literature.

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.

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 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 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.

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.

Airports and airlines are examining and committing to the electrification of Ground Support Equipment (GSE). In line with this trend, in this paper, we develop a model to simulate and optimize the GSE operations at airports. The aim is to estimate the required quantity of eGSE, the charging requirements of eGSE, the change in airport electricity requirements, and the scheduling possibilities of eGSE charging for the existing turnaround procedures. This is done by means of a Task Scheduling Problem (TSP), that is optimized using Mixed-Integer Linear Programming (MILP). A case study is performed on KLM's GSE fleet at Amsterdam Airport Schiphol. Based on this, it is concluded that daily operations can be sustained without increasing fleet size for GSE types capable of lasting a full day on a single charge, assuming vehicles can recharge overnight. This is the case at many airports due to nighttime curfews. The operational procedures used by the handler play a key role in achieving this outcome. The results confirm that the model is suitable for strategic decision-making and it is effective at the operational level. The model has the potential to lead to a more efficient use of resources in the operation.