This thesis investigates the integration of electric vehicle (EV) charging, photovoltaic (PV) power, and battery energy storage (BES), using a direct current (DC) integrated multi-port power converter. The goal is to aid the energy transition using the intelligent operation of the aforementioned components to provide a more cost-effective system that helps increase the penetration of small-scale local PV system and increase the sustainability of local loads, such as EV charging. To achieve this, this work focuses on two parts: the power electronic converter and the smart charging control, including battery degradation. A. Power Electronics In this thesis a modular DC-integrated multi-port converter is developed. The DC integration allows to reduce the amount of power converters hereby reducing its costs, while increasing efficiency and power density. All converters ports are developed for bidirectional operation to maximize its flexibility. a two level DC-AC converter is used for the bidirectional AC grid connection. Next, a 4-phase interleaved flyback converter is used for isolated EV charging. Finally, two interleaved four-switch buck-boost (FSBB) converters are used for both the PV and BES ports. All DC-DC converters utilize quasi-resonant boundary conduction mode (QR-BCM), combined with silicon carbide semiconductors to achieve efficiencies up to above 99%. A novel control method for the interleaved FSBB converter is proposed to enable multi-mode QR-BCM operation. Based on an experimental comparison with three other soft-switching modulation schemes it is shown that the proposed modulation and control achieve the highest efficiency (up to 99.5%) with little to no compromise in power density and control complexity. B. Smart Charging Next, a two-level smart charging structure is proposed to utilize the flexibility obtained from the multi-directional power electronic hardware. The first level is a non-linear programming (NLP) model that optimizes the charging powers of the EV and BES in a moving horizon context, to minimize the operational costs, including primary frequency control market participation and battery degradation. To minimize the battery degradation, a literature survey study has been done on lithium-ion ageing mechanisms and how to model it. Based on this survey the best suited degradation model is chosen and integrated in the NLP model. The second level of the proposed smart charging structure recalculates the setpoints based on grid frequency deviation, and PV forecasting errors. Both the theoretical and experimental results show that the proposed control method is effective in reducing the lifetime system costs. In combination with optimal sizing of the components the total lifetime system costs can be reduced up to 460% compared to conventional non-optimal charging methods.@en

This paper presents a multi-objective approach to designing an optimal PV-BES assisted EV fast charging station. The trade-offs between lifetime net present value (NPV), energy independence, and grid power reduction are analyzed using particle swarm optimization and real 50kW fast charging data. Our results show a maximum lifetime profit of close to 4M euro. Furthermore, for only a 8% decrease in profit the we can achieve up to 62% of the maximum energy independence and 46% peak power demand reduction. This show that EV fast charging stations can become more significantly more sustainable and have a less fluctuating demand, for very little reduction in profits.@en

Battery aging is one of the critical problems to be tackled in battery research, as it limits the power and energy capacity during the battery's life. Therefore, optimizing the design of battery systems requires a good understanding of aging behavior. Due to their simplicity, empirical and semiempirical models (EMs) are frequently used in smart charging studies, feasibility studies, and cost analyses studies, among other uses. Unfortunately, these models are prone to significant estimation errors without appropriate knowledge of their inherent limitations and the interdependence between stress factors. This article presents a review of empirical and semiempirical modeling techniques and aging studies, focusing on the trends observed between different studies and highlighting the limitations and challenges of the various models. First, we summarize the main aging mechanisms in lithium-ion batteries. Next, empirical modeling techniques are reviewed, followed by the current challenges and future trends, and a conclusion. Our results indicate that the effect of stress factors is easily oversimplified, and their correlations are often not taken into account. The provided knowledge in this article can be used to evaluate the limitations of aging models and improve their accuracy for various applications.

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This paper proposes a method for optimally dimensioning the components of a prosumer energy management system that integrates photovoltaic (PV) panels, multiple bidirectional electric vehicle chargers, an inverter, and a battery energy storage charger. Besides optimally dimensioning the components, it also optimizes power management while integrating the frequency containment reserve market and Li-ion battery degradation. The results show that the integration of the frequency containment reserve (FCR) market can increase lifetime cost savings by 36%, compared to optimal power management alone and up to 460% compared to non-optimal power management. Furthermore, the effects of PV and battery energy storage (BES) degradation on reservable capacity are analyzed including the importance of battery second-life value on lifetime net present cost is investigated.

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This paper discusses the design and optimization of electric vehicles’ fast-charging stations with on-site photovoltaic energy production and a battery energy storage system. Three scenarios, varying the number of chargers, distance from the main grid, and on-site photovoltaic generation potential, are investigated. Such scenarios are benchmarked in investment, operating costs, and grid connection requirements. The addition of a battery storage system is also evaluated to reduce the operating cost and, therefore, boost the system’s economic parameters, such as the net present value, and increase the grid independence.The analysis shows that the addition of the battery system can be effective in both performance metrics, the reduction of the grid connection, which can be reduced up to 80% by the addition of a large size battery, and the increase of the net present value, which can be even doubled with respect to the case when the battery storage system is not installed.@en

An integrated energy system consisted of PV panels, EV (electric vehicle), BES (battery energy storage), and a HP (heat pump) coupled with thermal storage tanks (TES) has been studied. The research aimed to minimize the total energy costs by scheduling the optimal power consumption of each device as response to two external signals as part of a demand response program. One of the signals corresponded to a selling electricity price tariff or feed-in tariff (FIT) to account for the ability of the system to sell energy towards the grid. On the other hand, the second signal corresponded to the buying electricity price tariff to account for the system's energy consumption from the grid. This control scheme allowed to determine the optimal energy consumption of the HP and its flexibility potential to shift its load towards times of low electricity prices. It was concluded that the proposed integrated system will produce a 50 % total energy cost reduction while the operation of the HP for one week in winter will reduce the gas consumption in 53 m3 in a traditional Dutch house.@en

In this paper a review on the effects of pulse charging of lithium based battery technology is done. Results published in existing literature are not in complete agreement regarding the effects of pulse charging. Several studies claim to have beneficial effects on charging efficiency, charging time, and capacity fade. While others have found disadvantageous effects on the same parameters. The goal of this paper is to summarize and review these results, based on fundamental theory. Additionally, it will be shown that the electrical equivalent circuit analysis of batteries, often used to explain the beneficial results of pulse charging is an incomplete analogy to fully explain the results of pulse charging.@en

This paper proposes a two-stage smart charging algorithm for future buildings equipped with an electric vehicle, battery energy storage, solar panels, and a heat pump. The first stage is a non-linear programming model that optimizes the charging of electric vehicles and battery energy storage based on a prediction of photovoltaïc (PV) power, building demand, electricity, and frequency regulation prices. Additionally, a Li-ion degradation model is used to assess the operational costs of the electric vehicle (EV) and battery. The second stage is a real-time control scheme that controls charging within the optimization time steps. Finally, both stages are incorporated in a moving horizon control framework, which is used to minimize and compensate for forecasting errors. It will be shown that the real-time control scheme has a significant influence on the obtained cost reduction. Furthermore, it will be shown that the degradation of an electric vehicle and battery energy storage system are non-negligible parts of the total cost of energy. However, despite relatively high operational costs, V2G can still be cost-effective when controlled optimally. The proposed solution decreases the total cost of energy with 98.6% compared to an uncontrolled case. Additionally, the financial benefits of vehicle-to-grid and operating as primary frequency regulation reserve are assessed.

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Since the power transfer efficiency in inductive power transfer (IPT) systems is directly related to the coupling of the transformer, coil misalignment can drastically decrease the efficiency. In this paper a misalignment tolerant control scheme is proposed which tracks the maximum power transfer efficiency point under misalignment. It does this by matching the impedance of the load with respect to the transformer based on an online coupling factor estimation, as well as tracking the resonance of the system. The control scheme is implemented on a series-series compensated system and designed such that it can be operated bidirectionally in the future, however this is not in the scope of this paper. The proposed control results in an overall efficiency improvement of 5% and 23% under 0 and 8 cm misalignment, respectively, compared to a constant rectifier output voltage of 48V.@en