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A ubiquitous network of charging stations is vital to facilitate the adoption of electric vehicles (EVs) and the achievement of a low-carbon transportation system. Currently, the availability of EV infrastructure differs significantly between communities as planning procedures are not necessarily equitable. Understanding the charging behavior of EV users is a crucial step toward creating an electric vehicle service equipment (EVSE) infrastructure that serves users efficiently, equitably, and sustainably. Presently, public charging station deployment efforts differ across communities, with little context surrounding urbanicity. This study analyzes data from 66 public Level 2 charging stations across Rhode Island. Motivated by the significant disparities in infrastructure availability between urban and rural areas, the research explores behavioral differences to inform infrastructure planning. Key findings reveal that urban stations are predominantly used during weekdays, with longer charging durations and higher energy consumption, whereas rural stations are primarily utilized on weekends and exhibit shorter, more efficient charging sessions. On average, dwell times at rural stations are approximately 50% shorter, while average energy demand is only 7% less. These results provide actionable insights for optimizing charging station deployment and utilization across diverse communities to support the growing demand for EVs. [ABSTRACT FROM AUTHOR]

The right methods for effective financing of electric vehicle charging infrastructure investments should be identified. However, in the literature, there is no consensus on which funding source would be right for these projects. There is a need for a new study to recommend the most appropriate financing strategy for these projects. Accordingly, the purpose of this study is to identify innovative solutions for financing electric vehicle charging infrastructure investments. A novel fuzzy decision-making model is introduced to reach this objective. Firstly, the weights of experts are calculated using dimension reduction. Secondly, Spherical fuzzy decision matrix is obtained. Thirdly, the criteria in charging infrastructure for electric vehicles are weighted using Spherical fuzzy criteria importance through intercriteria correlation (CRITIC). Fourthly, innovative solutions for financing electric vehicles charging infrastructure are ranked via Spherical fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS). The main contribution of this study is that effective strategies can be identified for financing electric vehicle charging infrastructure investments by establishing a novel decision-making model. Most of the existing models in the literature could not consider the weights of the experts. This condition is criticized by different scholar because these experts can have different qualifications. To satisfy this problem, in this study, dimension reduction algorithm with machine learning is taken into consideration to compute thee weights of the experts. The findings demonstrate that the most effective criterion in the innovative financial solution for the charging infrastructure of electric vehicles is determined as “potential income”. According to the ranking results, it is also defined that the most sustainable solution among the innovative strategies for financing the charging infrastructure of electric vehicles is “blockchain technology”. [ABSTRACT FROM AUTHOR]

Recently, Unmanned Aerial Vehicles (UAVs) have been proposed as the carriers of mobile edge servers. Such UAV-mounted edge servers can offer computation offloading service to users more efficiently due to their fast movement. However, the limited battery endurance of the UAVs places a real challenge. In this paper, we propose MobiPower: a two-layer UAV-based edge computing and charging scheme for Internet of Vehicles (IoVs). The UAV-mounted edge servers fly in the air to serve the IoV nodes, while the Mobile Charging Stations (MCSs) move on ground to charge these UAVs. As the mobile charging stations are low-speed trucks which are difficult to respond to the realtime traffic change, we predict the future traffic based on the historical data to facilitate obtaining the offline scheduling strategies in advance. Moreover, we use hierarchical clustering to analyze the traffic patterns and classify the regions with same pattern into the same cluster. Mobile charging stations will only be scheduled between different clusters to reduce the complexity. Finally, we design an auction-based mobile charging station scheduling algorithm to maximize the amount of offloaded tasks and reduce the moving distance of the mobile charging stations. We conduct experiments on a popular trace, i.e., the TaxiBJ trace, and the experimental results show that our heuristic strategies effectively schedule the mobile charging stations over the entire map and demonstrate superior performance compared with existing popular methods, e.g., up to 36.46 % improvement in terms of task offloading ratio and 39.06 % less scheduling distance of the mobile charging stations under typical scenarios. [ABSTRACT FROM AUTHOR]

Lithium-ion battery management requires an accurate determination of the batteries' remaining usable lives. A novel hybrid method used for the RUL and short-term capacity prediction of batteries is presented in this manuscript. The proposed technique is combined with a White Shark Optimizer (WSO) with the Multi-kernel Support Vector Machine (MSVM); therefore, it is called the WSO-MSVM technique. The major goal of this WSO-MSVM method is to attain effective future capacities and RUL forecast for the Lithium-Ion Battery (LIB) with reliable management of uncertainty. The hybrid technique solves the difficulty of forecasting the RUL of LIB. This proposal trains the WSO-MSVM model using the LIB data. The trained model is utilized to forecast the capacity and RUL of LIBs. In this proposed system, capacity, current, and voltage are considered in the discharge operation. The proposed technique validates good reliability and prediction accuracy with this suitable mechanism. Compared to the existing techniques like artificial neural network (ANN), ant lion optimizer-optimized artificial neural network, and adaptive network-based fuzzy inference system, the proposed technique shows fewer errors under charge and discharge conditions. In addition, the uncertainty intervals of the proposed WSO-MSVM technique for the predicted RUL may include the actual remaining life of the battery. The proposed technique's charging error is lower the other exciting methods. [ABSTRACT FROM AUTHOR]

As the number of electric vehicles (EVs) on North American roads continues to rise, driven by the shift toward sustainable transportation, understanding the economic implications of this transition is crucial. This review paper prioritizes an evaluation of the Total Cost of Ownership (TCO) for various types of EVs, providing insights into how different driving profiles align with the financial benefits of EV adoption. It demonstrates that at-home charging and government incentives are pivotal in reducing TCO. The analysis also offers a comprehensive overview of the factors driving EV growth, including declining operating and maintenance costs. Additionally, the paper explores adoption rates, charging infrastructure, and other non-monetary factors that influence consumer decisions in the shift to EVs. Conclusions emphasize that while EVs offer a financial advantage for many drivers, the success of broader adoption depends on decreasing the initial cost of EVs, developing charging infrastructure, and investing in charging networks. [ABSTRACT FROM AUTHOR]

Solar Air Heaters (SAHs) are widely used to harness solar energy for various heating applications. Recent research aims to improve the ability to capture maximum irradiation, addressing the weather-dependent and intermittent nature of solar energy availability. The incorporation of Phase Change Materials (PCMs) in SAHs can improve the capacity to absorb the irradiation due to their high latent storage capacity. However, conventional PCMs often exhibit low thermal conductivity. Various enhancement techniques can improve the thermal conductivity of pure PCMs and enhance the system's performance. This review article explores single-pass and double-pass SAHs with Integrated Collector PCM Storage (IC-PCMS) systems and various techniques to enhance the thermal conductivity of PCMs. The findings are based on the detailed analysis of systems and provide quantitative results showing the performance improvements of PCM-integrated SAHs. The inclusion of PCM not only maximizes irradiation capture but also extends the duration of hot air availability during periods of uneven irradiation. Further, carbon-based nanocomposites and metal foams have shown the most significant improvements in the thermal conductivity of PCMs and thus enhance the system's performance. Future research should focus on optimization and economic analysis to commercialize these systems for various thermal applications. [ABSTRACT FROM AUTHOR]

The installed capacity of photovoltaic (PV) systems has increased significantly over the past few decades, and related technologies have advanced significantly. The electrical characteristics of a PV system change nonlinearly based on irradiation and temperature, and the I–V characteristic curve, expressed in terms of the voltage and current, is used to verify these characteristics. The maximum power point tracking (MPPT) control method was applied to maximize the performance of the PV system. Voltage and current sensors are used to control the I–V characteristic curve and MPPT; however, current sensors have various disadvantages in terms of price and system configuration. Therefore, this study presents a method for calculating the current of a PV system using the charging characteristics of a capacitor. The method presented in this paper analyzes the I–V characteristic curve's qualities through simulations and experiments under normal, shaded, and mismatched conditions of the PV module. [ABSTRACT FROM AUTHOR]

The shift from cars with a combustion engine to electric cars is a key ingredient in the transition toward a carbon-neutral mobility system. However, this leads to a drastic increase in the demand for renewable electric energy. In this study, we investigate the size and shape of this additional electricity demand. We develop an agent-based model to calculate the overall demand and, more importantly, the distribution throughout the day with a fine temporal resolution in order to identify demand peaks. We also take into account the existing demand for electricity to gain a more complete picture of the load on the entire grid. We find that the demand peaks arising from charging a fully electric fleet are extensive and the most prominent demand peak occurs at the so-called charging rush hour in the early evening. These findings suggest that our current mobility system is in need of drastic changes to make sustainable mobility achievable. Plain language summary: Modelling electricity demand from charging electric cars Moving from cars with gasoline engines to electric cars is an important part of the shift toward a transportation system that doesn't harm the environment. However, this change results in a significant increase in the need for renewable electric power. In this study, we examine how much additional electricity is required and when it is needed. We create a computer model that calculates the overall demand for electricity, including the distribution of demand throughout the day with precise time intervals. This helps us identify the times when the demand for electricity is highest. We also consider the existing electricity demand to get a complete understanding of the strain on the entire power grid. Our research shows that the peak demand for electricity caused by charging a fleet of fully electric vehicles is substantial, and the most significant peak occurs during the busy charging period in the early evening, which we call the "charging rush hour." These findings indicate that significant changes are necessary in our current transportation system to achieve sustainable and eco-friendly mobility. [ABSTRACT FROM AUTHOR]

The practicality and substitutability of electric vehicles depend on there being a fast, reliable way to recharge on round trips beyond the range of a single charge. Grouping such infrastructure into charging hubs benefits developers and operators through economies of scale and electric vehicle drivers in terms of travel logistics and passed-through cost savings. The need for charging capacity at en-route charging hubs is impacted by the following four identifiable geo-social parameters: (a) highway travel volumes, reflecting the rate at which electric vehicles are expending energy in the area; (b) local population, reflecting both the increased needs of electric vehicle owners without dedicated home chargers and the reduced needs of those commuting into a metropolitan center; (c) the quantity of competing charging stations; and (d) being on a critical interprovincial route. Twelve charging stations located in diverse locations around Nova Scotia, Canada, were evaluated in terms of these four parameters, and their recorded use was investigated from a dataset of 26,000 charging events between April 2022 and April 2024. The regression reveals that there are strong positive correlations between demand for fast charging and (a) traffic volumes (45%) and (c) being on an interprovincial route (42%), while there is only a very weak correlation with (b) local population (2%). Interestingly, there is only a weak negative correlation with (c) the number and capacity of nearby competing chargers (−6%), suggesting that either in short-term route choice or longer-term vehicle choice, the presence of chargers encourages electric vehicles. [ABSTRACT FROM AUTHOR]

Solar energy is one of the major sources of renewable energy and is being extensively harnessed. However, the intermittent nature limits solar energy to act as a stand-alone energy source. Therefore, it becomes imperative that effective and economical methods of storing solar energy on a large scale are developed. Both sensible and latent heat storage methods are available. The use of a thermal energy storage (TES) system is an attractive choice for high-temperature applications such as power generation plants. The present study investigates the development of a small-scale TES system using a concentrated solar collector. For this purpose, a small cylindrical thermocline tank with suspended copper pipes in the storage medium was developed, with vegetable oil working as the heat transfer fluid (HTF) and being circulated through the pipes to transfer heat to used engine oil as the storage medium. A pump continuously circulates the HTF through the charging loop. TES was designed and developed based on the results of numerical simulations before the physical development of the experimental setup. Numerical calculations were performed for determining heat transfer and charging characteristics using different heat storage materials. The numerical results showed that a maximum temperature of 67 °C was achieved in the 100-min simulation while in the experimental results, a maximum temperature of 64 °C was achieved. The experimental results were found in close conformance with the simulation results. The experiments showed that the flow rate of 0.088 L s−1 was optimal and provided the highest temperature in the thermocline tank. The discharging experiment showed that the apparatus is viable to be used for 5.5 h for heating purposes. The salient feature of the study is an inexpensive TES system development and can act as a benchmark for the future development of renewable technology. [ABSTRACT FROM AUTHOR]

In this work, we consider a problem from the field of power-aware scheduling in which a fleet of electric vehicles have to be charged in a minimum time. Each vehicle is equipped with a lithium-ion battery of a given capacity. The initial power used for charging each battery is known, whereas it is assumed that the power drops to zero at the moment when the battery gets fully loaded. The power usage function is linear and decreasing. The charging jobs are nonpreemptable and independent, whereas the total available amount of power is limited. The objective is to minimize the schedule length. In this paper, we analyze the case of a problem with identical jobs that already cover a wide variety of practical situations. By employing inverses of natural numbers, similar to harmonic series, we prove two properties of this case, and we also discuss the phenomenon of the stabilization of the difference between the start times of two successive jobs in a schedule. We also take under examination a few special cases of the problem. Some conclusions and directions for future research are given. [ABSTRACT FROM AUTHOR]

In terms of electric vehicle architectures, the drivetrain offers unprecedented freedom, but it also creates new obstacles in terms of achieving all needs. The architecture of electric vehicles is simplified and adjustable at the component level because they don't have a combustion engine or fuel tank, only an electric motor and a battery. Implementing safe zones within electric vehicles (EVs) to accommodate battery packs necessitates significant adjustments to ensure the secure integration of the battery. A Battery EV, also known as a pure EV, solely relies on rechargeable battery packs as its source of energy, without any additional propulsion system. The Battery Management System (BMS) plays a significant role in maintaining the safety of electric vehicles by controlling the electronics of rechargeable batteries, whether they are individual cells or battery packs. The BMS plays crucial role in protecting both the user and the battery by monitoring and maintaining the cell's operation within safe limits. This research paper focuses on the control of solar‐powered charging for lithium‐ion batteries. An optimized FOPID controller is utilized to maximize power extraction from PV array and efficiently charge the battery. A hybrid optimization model is employed to optimize the gain parameters of the FOPID controller. [ABSTRACT FROM AUTHOR]

The efficient dispersion of single-walled carbon nanotubes (SWCNTs) has been the subject of extensive research over the past decade. Despite these efforts, achieving individually dispersed SWCNTs at high concentrations remains challenging. In this study, we address the limitations associated with conventional methods, such as defect formation, excessive surfactant use, and the use of corrosive solvents. Our novel dispersion method utilizes the spontaneous charging of SWCNTs in a solvated electron system created by dissolving potassium in hexamethyl phosphoramide (HMPA). The resulting charged SWCNTs (c-SWCNTs) can be directly dispersed in the charging medium using only magnetic stirring, leading to defect-free c-SWCNT dispersions with high concentrations of up to 20 mg/mL. The successful dispersion of individual c-SWCNT strands is confirmed by their liquid-crystalline behavior. Importantly, the dispersion medium for c-SWCNTs exhibits no reactivity with metals, polymers, or other organic solvents. This versatility enables a wide range of applications, including electrically conductive free-standing films produced via conventional blade coating, wet-spun fibers, membrane electrodes, thermal composites, and core-shell hybrid microparticles. [ABSTRACT FROM AUTHOR]

Sample charging during X-ray photoelectron spectroscopy analyses of electrically insulating samples is a widely recognized challenge of this essential technique. If the electron loss caused by the photoelectric effect is not compensated due to specimens’ poor electrical conductivity, the positive charge building up in the surface region results in an uncontrolled shift of detected core level peaks to higher binding energy (BE). This seriously complicates chemical bonding assignment, which is based on measured peak positions, and accounts for a large spread in reported core level BE values. Here, we show that peaks from several industry-relevant oxides, serving as model insulators, typically displaced by several eV due to charging, shift back to positions characteristic of electrically-neutral samples following ex-situ capping with a few nm thick metallic layer with low affinity to oxygen. The effect is present only if the capping layers contain sufficiently large non-oxidized volume that provides long-range conduction paths to grounded Cu clamps, while being thin enough to allow for recording high quality spectra from the underlying insulators. The versatility of the charging elimination is demonstrated for different oxides/cap combinations, air exposure times, and sample types (including thin film and bulk specimens).

The increasing energy demand caused by digitalization, the integration of renewable energy sources, and the growing adoption of electric vehicles (EVs) pose significant challenges to power grids. The Vehicle-to-Grid (V2G) technology emerges as a solution that provides cost-effective energy storage capacities to address these challenges. This paper explores the roles, potentials, and challenges for the stakeholders involved in a V2G architecture. These include Consumers, V2G Systems, Power Markets, and V2G Communication operators. A major emphasis is on the importance of data in a bidirectional charging environment. Through a comprehensive literature research and in-depth interviews with 16 V2G experts, we identify the current state, research gaps, and insights related to V2G. In particular, we focus on addressing the challenges in a V2G architecture. Our analysis reveals evolving stakeholder roles, the potential for cost benefits and new revenue streams, and challenges related to costs, functionality, legal aspects, and market collaboration. Additionally, we highlight behavioral shifts among consumers and the crucial role of data collection, utilization, and sharing. This study contributes to V2G research by offering insights into customer adoption challenges, the extension of charging infrastructure, the importance of software and machine learning tools, and the need for grid player collaboration.

The trend following the purchase of electric-powered vehicles is currently the biggest challenge of the Polish automotive industry. Increasing restrictions and looming deadlines for selling electric-only cars contribute to their increasing purchase numbers. It is known that electric vehicles require a stable charging infrastructure. From 2020 to 2022, infrastructure development is significant in Poland, but is it sufficient? Is this the main drawback of owning an electric vehicle? More and more users are charging their cars locally at their places of residence, but not everyone has this option. This raises the question of whether it is safe to own an electric vehicle. Is it possible to cover the route from point A to point B without much trouble? Awareness of the need to stop longer to charge an electric vehicle is not a problem among the Polish public; a bigger and more significant issue is the number of publicly available charging points. Therefore, these topics will be analyzed more extensively in this article; the possibilities of alternative charging and energy harvesting methods will be presented, as the growing interest in electric-powered vehicles and the indicated questions regarding the development of charging infrastructure and safety for electric vehicle users will be answered.

Advances in electric vehicles and charging infrastructure technology have given the electrification of road traffic a positive momentum. Nowadays, it is becoming more and more evident that the related energy and financial processes of the current e-mobility ecosystem are reaching their limits. This leads to usability losses for end users as well as administrative and non-causation-based financial burdens on various energy system participants. In this article, use cases are inferred from the literature, the aforementioned challenges are discussed in more detail, and strategies for addressing them are presented. Furthermore, the information system architecture of the BANULA project, with its core elements of open communication standards, virtual balancing areas, and blockchain components, is explained. BANULA addresses the aforementioned challenges by holistically considering the needs of all participants. A special focus of the project is implementing and investigating the concept of virtual balancing areas. This concept has been available since 2020 but has not been implemented in the market yet. To the best of the authors’ knowledge, BANULA is the first project that utilizes current legislation to transfer charging infrastructure to virtual balancing areas in conjunction with distributed ledger technology to support related processes. In the first step, the BANULA implementation prototype targets the German e-mobility ecosystem, but applicability to other states in the European Union is planned. Using an independent framework, the BANULA architecture and its prototypical implementation are evaluated. The authors show that the unique combination of virtual balancing areas and the related processes, enhanced through distributed ledger technology, has the potential to contribute to a user-centered, trustworthy, and grid-supportive e-mobility ecosystem.

A ubiquitous network of charging stations is vital to facilitate the adoption of electric vehicles (EVs) and the achievement of a low-carbon transportation system. Currently, the availability of EV infrastructure differs significantly between communities as planning procedures are not necessarily equitable. Understanding the charging behavior of EV users is a crucial step toward creating an electric vehicle service equipment (EVSE) infrastructure that serves users efficiently, equitably, and sustainably. Presently, public charging station deployment efforts differ across communities, with little context surrounding urbanicity. This study analyzes data from 66 public Level 2 charging stations across Rhode Island. Motivated by the significant disparities in infrastructure availability between urban and rural areas, the research explores behavioral differences to inform infrastructure planning. Key findings reveal that urban stations are predominantly used during weekdays, with longer charging durations and higher energy consumption, whereas rural stations are primarily utilized on weekends and exhibit shorter, more efficient charging sessions. On average, dwell times at rural stations are approximately 50% shorter, while average energy demand is only 7% less. These results provide actionable insights for optimizing charging station deployment and utilization across diverse communities to support the growing demand for EVs.

The heat storage system (HHS) still faces the problem of void formation as a result of the supercooling phenomenon caused by the use of paraffin. This study was conducted to analyze the effect of HTF discharge variation in the HHS system on the increase of heat storage efficiency in both the charging and discharging processes. The prototype helical coil heat exchanger is designed, fabricated, and experimentally analyzed on 4 types of helical coils with different models of fin designs: finless helical coil, straight fin, branched fin, and crossed fin. The phase change material (PCM) used is 9 kg of commercial paraffin type. The heat transfer fluid (HTF) is SAE 20W40 oil which is heated to a temperature of 210 °C with the heat source coming from the heating element. The pump is used to circulate the HTF with an output of 10 mL·s−1, 11 mL·s−1, and 12 mL·s−1. The experimental results show that the variation of the HTF flow rate affects the melting temperature, the paraffin freezing temperature, and the power efficiency of the LHS. The highest temperature absorption by paraffin was achieved by the branch fin model at 124 °C with a discharge of 11 mL·s−1, and the highest temperature release in the Branch Fin at 90 °C with a discharge of 12 mL·s−1. The highest effective power achieved by the branched fin model with effective power of 73 % charge and 53 % discharge occurred at a discharge of 12 mL·s−1. Varying the HTF discharge makes a positive contribution to the charge/discharge pattern, so it can be used as a reference for latent heat storage models. [ABSTRACT FROM AUTHOR]

Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenue, as well as to operate air pollution control devices at design conditions. Depending on plant type and design, these plants can adjust output within a fixed range in response to plant operating or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation, such as wind and solar, is shifting the traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and a lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. Recent studies have shown that the flexibility of a coal-fired power plant can be improved by energy storage. The objective of this work was to analyze a set of energy storage options and determine their impact on the flexibility and economics of a representative coal-fired power plant. The effect of three energy storage systems integrated with a coal power plant on plant flexibility and economics was investigated. The results obtained in this project show that energy storage systems integrated with a thermal power plant improve plant flexibility and participation in the energy and ancillary services markets, which improves plant financial performance. The study was funded by the U.S. Department Office of Fossil Energy FE-1 under award number DE-FE0031903. [ABSTRACT FROM AUTHOR]

Here we outline a vignette of the Bioscience Technology Facility (BTF) at the University of York as a singular exemplar of the Full Cost Recovery model. It is fully appreciated that every facility operates slightly differently, and each are subject to various rules at the institutional, regional and national level. Understanding the regulations that need to be followed for your cost recovery model may require discussion with your administrators to ensure compliance regulations for your Institution and governing bodies are followed. The below is almost a pick and mix of ways of working. It is, however, one of the few examples that is able to fully recover its operating costs within an academic environment and has sought and obtained full institutional and funders support. This model is now being much more widely adopted across the United Kingdom although again always with slightly different interpretations. [ABSTRACT FROM AUTHOR]

One of the primary types of sensible heat storage systems in drying applications is the packed rock bed. However, to create large‐scale heat storage systems for industrial use, one must comprehend the hydrodynamic and effectiveness of the heat transport mechanism inside the bed. In this study, the thermal storage unit uses river rock as heat storage materials with equivalent particle diameters of 36 mm in bed 1 and 56 mm in bed 2. The rocks were stacked in a truncated cone‐shaped concrete wall section with an average diameter and depth of 1.1 m and 1.3 m, respectively and a volume of 2.32 m3. During the charging phase, two airflow configurations were used, one from the top with an air mass flow rate of 0.753 and 0.332 kg/m2‐s and the other from the bottom with an air mass flow rate of 0.955 kg/m2‐s. During the discharging phase, the entire flow configuration is from the bottom section. It was observed that the mass flow rate and particle equivalent diameter had an important effect on the thermal performance and behaviour of the rock bed during charging and discharging operations. Maximum efficiency was achieved with an airflow configuration provided from the bottom when charging at 0.955 kg/m2.s. Consequently, a sizable quantity of heat or energy (60 MJ) was retained. It was also observed that the relationship between air mass flow rate and particle size was significant, with smaller particles retaining more energy. When comparing bed 1 with bed 2 at this air mass flow rate, bed 1 stored 2.1 times more energy than bed 2. A wind tunnel experiment was used to measure the pressure drop in the packed rock bed. The pressure drop in the bed increases with an increase in particle Reynolds number and decreases with an increase in particle size. Rock bed heat transfer coefficient and Nusselt number were calculated using the correlation that has already been established in the literature smaller particles showed higher heat transfer coefficients and lower Nusselt numbers. This is due to the increase in particle‐to‐particle interaction and larger particle surface areas. For a given Reynolds number, the Nusselt number increases with the size of the rock particle. [ABSTRACT FROM AUTHOR]

The resonance circuit's design has a major influence on the inductive electric vehicle (EV) charging system's performance and the distance between the primary and secondary inductive coils. If resonance circuitry is not included in an inductive power transfer (IPT) system, its performance suffers dramatically and its power transfer efficiency suffers significantly. Furthermore, the design of the resonance circuit has a major impact on the rating as well as the voltage and current strains on the semiconductor switches. The sequence, amplitude, and shape of the waveform are determined by the configuration of the energy storage components. The arrangement of these components is critical in defining how the inductive power transfer system behaves and operates. A few popular architectures play an important role in shaping how the system works. In this paper, the significance and effect of resonance circuits on the inductive charging of electric vehicles have been reviewed and discussed comprehensively. Furthermore, a detailed discussion was presented for the second-order resonance circuit, the higher-order resonance circuit, and the hybrid resonance circuit. Additionally, H-bridge resonant inverter topology was discussed and three main resonant architectures for the H-bridge inverter were studied inclusively. They include the inductor-capacitor-inductor (LCL) resonance architecture, switched inductor-capacitor (SLC) resonance architecture, and High-gain resonance architecture. Also, a comparison of these architectures was done and represented in tabular form. Lastly, an analysis of the effect of frequency variations in the resonant circuit architectures. [ABSTRACT FROM AUTHOR]

Using Critical Race Theory and an intersectional framework, the present study focuses on the case processing of sexual assault (SA) incidents involving Black and Latina victims. Importantly, much of the prior literature assessing arrest and charging decisions have been whitewashed by failing to consider that the factors influencing the case progression of white victims' SA experiences may not appropriately apply to women of Color. Oftentimes, this scholarship merely controls for victim and suspect race without considering how legal and extralegal incident and case factors may operate differently for victims of Color. The present study addresses this oversight. [ABSTRACT FROM AUTHOR]

The demand for cooling applications increases severalfold; the integration of the CTES system will mitigate the demand and pollution caused by the building sectors. The objective of this study is to investigate the effect of grooving on the inner surface of the spherical capsule on the solidification characteristics of deionized (DI) water, which finds widespread use in the bed of cool thermal energy storage applications. Eight hemispheres made of mild steel of 100-mm diameter and 1-mm thickness are used to make four spherical capsules by the welding process for the study. Among the four capsules, one with a plain surface and the remaining with a groove depth of 0.3 mm, 0.5 mm, and 0.7 mm are made. The grooving in the hemispherical capsule is obtained by the turning operation. The experiments are conducted at various bath temperatures of − 6 °C, − 9 °C, and − 12 °C. The experimental result reveals that the surface modification leads to a significant reduction in solidification time, and in particular, the maximum percentage reduction in solidification time is achieved at − 6 °C. The provision of grooves makes the evaporator operate at − 6 °C instead of − 12 °C till the solidification of 75% mass and the predicted energy saving is 18 to 24%. As the enhancement of heat transfer rate techniques is carbon-free, the recycling of the PCM will have zero impact on environmental pollution. [ABSTRACT FROM AUTHOR]

Quantum control allows us to address the problem of engineering quantum dynamics for special purposes. While recently the field of quantum batteries has attracted much attention, optimization of their charging has not benefited from the quantum control methods. Here we fill this gap by using an optimization method. We apply for the first time the convergent iterative method for the control of the population of a bipartite quantum system in two cases, starting with a qubit-qubit case. The quantum charger-battery system is considered here, where the energy is pumped into the charger by an external classical electromagnetic field. Secondly, we systematically extend our investigation to a second case involving two harmonic oscillators in the Gaussian regime, presenting an original formulation of the method. In both cases, the charger is considered to be an open dissipative system, as its interaction with the drive may require a more pronounced exposure to general interaction with environment. A key consideration in our optimization strategy is the practical concern of turning the charging external field on and off. We find that optimizing the pulse shape yields a substantial enhancement in both the power and efficiency of the charging process compared to a sinusoidal drive. The harmonic oscillator configuration of quantum batteries is particularly intriguing, as the optimal driving pulse remains effective regardless of the environmental temperature. This study introduces a novel approach to quantum battery charging optimization, opening avenues for enhanced performance in real-world applications. [ABSTRACT FROM AUTHOR]

With more electric vehicles introduced in society, there is a need for the further implementation of charging infrastructure. Innovation in electromobility may result in new charging and discharging strategies, including concepts such as smart charging and vehicle-to-grid. This article provides an overview of vehicle charging and discharging innovations with a cable connection. A MATLAB/Simulink model is developed to show the difference between an electric vehicle with and without the vehicle-to-grid capabilities for electricity grid prices estimated for Sweden for three different electric vehicle user profiles and four different electric vehicle models. The result includes the state-of-charge values and price estimations for the different vehicles charged with or without a bidirectional power flow to and from the electric grid. The results show that there is a greater difference in state-of-charge values over the day investigated for the electric vehicles with vehicle-to-grid capabilities than for vehicles without vehicle-to-grid capabilities. The results indicate potential economic revenues from using vehicle-to-grid if there is a significant variation in electricity prices during different hours. Therefore, the vehicle owner can potentially receive money from selling electricity to the grid while also supporting the electric grid. The study provides insights into utilizing vehicle-to-grid in society and taking steps towards its implementation. [ABSTRACT FROM AUTHOR]

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In this study, we introduce the water wave optimized bidirectional long short-term memory (WWO-BLSTM) model for predicting the charging usage of electric vehicles (EVs).WWO can be utilized to optimize the charging schedules of EVs, enabling the flexible change of charging patterns. The estimation of EV charging use implements BLSTM, a model that analyzes sequential data in forward and backward directions. Initially, we collected a dataset that includes 10,595 unregulated charging operations from workplace charging. This dataset represents the diversity of EV charging .A comprehensive data cleansing procedure was performed. To ensure the suggested method is effective, we employ MATLAB software to conduct simulations. This model was able to obtain a recall of 96%, F1 score of 93%, accuracy of 88% and precision of 95%. We offer outstanding outcomes for the charging consumption of EVs using our innovative WWO-BLSTM methodology.

Greenhouse gas (GHG) emissions from transport contribute significantly to climate change. Some of the transport policies with the greatest potential to mitigate climate change are related to zero-emission vehicles. This study aimed to analyse the different factors, and their importance, influencing purchase decisions for battery electric vehicles (BEV). Experts’ perceptions were collected with a Delphi study consisting of a two-round survey to assess factors that would increase the probability of a petrol- or diesel-car owner purchasing a BEV in Finland in the year 2025. Increasing the possibilities for home charging and the provision of a purchase subsidy were seen as the most important factors. Public fast charging and the difference in use costs between current technology vehicles and BEVs were also recognised as important factors. Existing systems of financial instruments and policies must be constantly evaluated and updated due to the evolving BEV industry.