Power Charging Research Articles

Investigation of microwave power transfer near sea surface with 2D parabolic equation method

AbstractDue to the existence of the evaporation duct near‐sea‐surface described as an inhomogeneous refractive index of atmosphere, microwaves can be trapped in the duct and propagate along it. To investigate wireless power transfer (WPT) over the sea surface, we utilize the two‐dimensional parabolic equation to calculate the electric field distribution and to obtain the transferred power. By analysing the propagation results with specific evaluation functions, we obtained the proper conditions for long‐distance WPT over the sea surface. When the initial field distributes uniformly on the one‐meter aperture, the frequency is 12 GHz, and the centre position is 4 m, a unique focusing spot can be obtained in the duct and nearly 5%, 8%, and 12% of the initial power remains at a distance of 10 km with a receiving aperture of 1, 2, and 3 m, respectively. The presented WPT scheme near the sea surface has potential applications in the power supply or charging for ships or small islands.

Renewable sources-based efficient electric vehicle charging system through power forecasting and charge scheduling

Renewable sources-based efficient electric vehicle charging system through power forecasting and charge scheduling

A robust sliding mode control strategy for DC voltage stabilization in solar powered electric vehicle charging station

ABSTRACT Integrating DC power sources and AC grid in an electric vehicle charging station through converters can introduce oscillations, potentially leading to system instability. This paper explored the utilization of a sliding mode controller in a bidirectional DC-DC buck-boost converter for DC bus voltage control within the charging station. This controller aims to promptly respond to power fluctuations, offering robustness against variations in system parameters, external disturbances, and uncertainties. Control strategies play a critical role in mitigating DC link voltage fluctuations and ensuring power stability. The system entails a photovoltaic array employing maximum power point tracking for optimal energy harnessing. In addition, a bidirectional buck-boost converter is employed to effectively manage battery charging in buck mode and discharging in boost mode. A comparative analysis between Proportional-Integral control and sliding mode control incorporating a washout filter was conducted. This assessment is simulated and validated using MATLAB/Simulink, and the Sim Power System toolbox. The proposed model offers a comprehensive solution for integrating solar power, battery storage, and grid-based charging by enhancing overall system efficiency and reliability.

High efficiency deep ultraviolet micro-LED and optical fiber coupling for low power charge management applications

During space gravitational wave detection missions, it is necessary to manage the charge accumulated on the surface of the test mass. A common method involves using optical fibers to transmit ultraviolet (UV) light, leveraging the photoelectric effect for charge management. An important issue in this process is achieving efficient coupling between the UV light source and the optical fiber. In this paper, for the first time we proposed to use DUV micro-LEDs as light sources for charge management systems, which will have lower power consumption. We conducted simulations to investigate the effect of the size ratio between deep ultraviolet (DUV) micro-LEDs and optical fibers on the coupling efficiency. We further employed a direct coupling method to conduct coupling experiments of DUV micro-LEDs and optical fibers with varying wavelengths and sizes. The simulation and experiment results both indicate that, under the influence of both size and divergence angle, there exists an optimal DUV micro-LED size responsible for maximum coupling efficiency between DUV micro-LEDs and optical fibers which is 80 μm when the optical fiber size is 1000 μm. Applying the 80 μm DUV micro-LED in charge management experiments demonstrated the feasibility of using DUV micro-LEDs as light sources for low power charge management systems, achieving rapid charge–discharge rates and high photoelectric current at lower driving electrical power.

Water/oil interfacial photocatalysis of amphiphilic CdS/Bi2WO6 S-scheme heterojunctions for efficient production and spontaneous separation of H2O2 and value-added organics

The photocatalytic co-production of H2O2 and value-added organics in a suitable water/oil biphasic system offers an intriguing strategy to address the challenges encountered in a single liquid-phase solution, including the efficient separation of H2O2 and organic products as well as the mitigation of undesirable secondary reactions. For this, exploring amphiphilic photocatalysts with high performance is highly required. Herein, an amphiphilic CdS/Bi2WO6 S-scheme heterojunction photocatalyst is designedly synthesized through a two-step solvothermal process, aiming to achieve efficient interfacial photocatalytic reactions at the water/oil interface for simultaneous generation and selective separation of H2O2 and organic products. The CdS/Bi2WO6 heterojunction photocatalyst exhibits enhanced light absorption in UV–visible region, increased electron-hole separation efficiency, and powerful charge carriers with high redox abilities. Moreover, the formation of S-scheme heterojunction improves the catalyst stability by preventing CdS from photocorrosion. As a result, the production rate of H2O2 reaches up to 216.76 mmol g−1 h−1, accompanied by the generation of organic products (benzaldehyde: 104.91 mmol g−1 h−1, benzoic acid: 49.88 mmol g−1 h−1, and benzyl benzoate: 38.01 mmol g−1 h−1), in a water/benzyl-alcohol biphasic system under simulated sunlight irradiation. The photocatalytic mechanism is elucidated based on the results of comprehensive experiments and characterizations. This study highlights a rational construction of amphiphilic photocatalysts and their application in organic/water interfacial photocatalytic reactions.

Flexibility potential quantification of electric vehicle charging clusters

A significant obstacle to providing flexibility services with electric vehicles (EVs) is the uncertainty surrounding the profitability and flexibility potential of charging clusters when utilised as a flexible load. Currently, there is a lack of comprehensive and easily applicable methods for quantifying flexibility in the literature. This paper introduces an evaluation tool and a set of flexibility indexes to assess the capability of charging clusters to deliver flexibility services. The method is designed to evaluate and quantify the flexibility potential of charging clusters in terms of short-term and long-term power adjustments and charge scheduling. Through sensitivity analysis, we examine how connection capacity, EV battery capacities, power capabilities, and the number of daily charging sessions influence the flexibility potential of charging clusters. Our findings highlight a direct relationship between the grid connection capacity of clusters and their ability to perform short-term power adjustments. Moreover, while larger batteries tend to reduce energy and time flexibility, their increased storage capability facilitates managing and scheduling a larger energy volume. Furthermore, for the days analysed, the flexibility potential showed minimal sensitivity to the number of daily charging sessions. Instead, the amount of energy requested and connection patterns emerge as key determinants of overall flexibility. In summary, this research provides valuable insights that can inform the design, monitoring, and assessment of EV charging clusters when evaluating their suitability for various flexibility services.

Evaluation of electric vehicle power routing and charging analysis using artificial neural network synchronized with 5G-network

To motivate the advanced National Clean Air Program (NCAP) strategy announced by the Indian Government in 2017, automizing the routing control on electric vehicle (EV) is a challenging area. According to the public authority guideline, the air contamination issues over the nation focus on accomplishing a 20% to 30% decrease in vehicular outflows in 2024 by enhancing EV mobility. However electric vehicle's limitations on battery capacity and route strategy to charging stations to preserve an adequate level of battery charge still need automized communication strategy. Fixed route solutions might not always be executable because battery consumption varies on several external factors. To better fit the real situation, this study proposes the notion of breaking down the self-adaptive online routing by encountering automatic path detection concerning battery efficiency with adaptive charging decisions. An inventory control-style charging technique is suggested to account for stochastic battery use. In the proposed work, by using an artificial neural network, the power demand and energy consumption of the EV world will be monitored and controlled by using 5G coverage on the smart city evolution. The obtained simulation analysis confirms that in comparison to current conventional and fixed tariff schemes, 5G accompanied EV accomplish an examined rate of SoC charge around 19.95 MW holding a peak range of 108.96 MW. Also, an evaluated typical power loss rate of 2.873 kWH which is less than 11.95% through frequency band analysis with signal-to-noise ratio and downlink power utilization.

Charge storage mechanism and pseudocapacitance performance of NiO and Ce-doped NiO synthesized via modified combustion technique

Supercapacitors, as promising energy storage devices, have gained significant attention due to their ability to deliver high power and efficient charge storage mechanisms. In this work, we report the synthesis and electrochemical characterization of pristine NiO and Ni1-xCexO (x = 0.01, 0.02, 0.03) nanoparticles using a single-step auto ignition combustion method. Preliminary investigations indicate that Ni1-xCexO (x = 0.02) nanoparticles (2 % Ce doping) exhibit superior specific capacitance compared to other compositions. Therefore, we focused on structural, morphological, and vibrational studies on pristine and 2 % Ce-doped NiO. XPS and BET techniques were explored to assess the electronic state and porosity of the samples. Subsequent electrochemical performance evaluations included Cyclic Voltammetry (CV) at various scan rates, Galvanostatic Charge-Discharge (GCD), and Electrochemical Impedance Spectroscopic (EIS) techniques. From CV at a scan rate of 5 mVs−1, specific capacitance values of 419 Fg-1 and 604 Fg-1 were obtained for pristine and 2 % Ce-doped NiO, respectively. GCD studies revealed a specific capacitance of 381 Fg-1 for 2 % Ce-doped NiO at a current density of 1 Ag-1 and demonstrated capacitance retention of 95.1 % over 3000 GCD cycles for a current density of 4 Ag-1. The symmetric two-electrode supercapacitor cell demonstrates exceptional electrochemical performance, exhibiting a high specific capacitance of 122 Fg-1, an impressive energy density of 8.17 WhKg−1, a power density of 700 WKg-1 at 1 Ag-1, and a remarkable 88 % capacitance retention after 5000 GCD cycles. DFT calculations suggest that Ce doping significantly alters pristine NiO's electronic and structural features due to lattice strain. Our work highlights the enhanced electrochemical performance of 2 % Ce-doped NiO and its potential as a good-quality supercapacitor material.

Vectorial manipulation of twisted vector vortex optical fields in strongly nonlocal nonlinear media

Abstract We theoretically investigate the propagation properties and vectorial manipulation of twisted vector vortex beams (TVVB) with a cross-phase in a strongly nonlocal nonlinear medium (SNNM). The root mean square beam-width (RMS-BW) and the critical power required to retain the invariant RMS-BM of the TVVB in an SNNM are derived using the coupled nonlocal nonlinear Schrödinger equation. Numerical calculations reveal novel characteristics of the evolution of the state of polarization (SoP) and the optical intensity distributions during the TVVB propagating in an SNNM. It is found that mode conversions between a Laguerre Gaussian and a Hermite Gaussian mode take place during propagation in an SNNM, and the topological charge of the TVVB can be accurately measured by observing the interference intensity structure in the cross-section. Manipulation of the beam shape, SoP, and rotation of the TVVB is achieved by controlling factors such as the initial power, twisting coefficient, initial beam-width, and topological charge. These findings hold promise for applications in optical micro-manipulation, optical communication, and material processing.

A multi-objective coordinating model for distribution network with EVs, energy storage, and reactive power compensation devices

Promoting electric vehicles (EVs) is regarded as an effective solution for reducing carbon emissions and addressing growing environmental concerns. However, the increasing number of EVs has significantly heightened the demand for electric power charging, posing challenges to distribution systems. Studies have shown that a coordination strategy combining various compensation devices, such as energy storage systems and reactive power compensation devices, can enhance the integration capability of EVs. Furthermore, EVs can be managed as controllable loads that can be shed at low costs, contributing to the flexibility of the distribution network. This paper explores the uncertainties of EV load sizes and the coordination of active and reactive power. A multi-objective optimization model was developed to augment the flexibility of the distribution network and mitigate the risk of load shedding. The Monte Carlo method is utilized to simulate scenarios with EV load uncertainties. To simplify the power flow calculations in the proposed convex optimization model, the Distflow equation was adopted. Case study results demonstrate that managing EV loads in the distribution network can significantly reduce load shedding costs by 80 %, and the proposed EV charging strategy can effectively eliminate load shedding costs in most scenarios.

Efficient power factor correction in single phase AC–DC boost converter for retrofitted electric bicycle battery charging: A finite element analysis approach

This research paper describes modifying a conventional bicycle into an electric bike by retrofitting it with a single-phase boost power factor correction (PFC) rectifier for low power battery chargers. The proposed work was designed and developed in a single stage, as opposed to the traditional two-stage chargers used to charge E-bicycle, to provide the desired outcomes of enhanced efficiency, good power quality, and dependability due to the charger's lower cost. Additionally, the proposed converter uses a single switch, which reduces not necessary body diode conduction and circulating current and enhances the PFC device's thermal management. Additionally, this research makes use of the diode bridge rectifier (DBR) arrangement, which offers low current stress and is suitable for electric bicycles. The converter operates at a low cost with reduced magnetics (DCM) by operating the charger in discontinuous conduction mode at such low voltage levels. It also accomplishes intrinsic power factor at the ac mains by employing a simple control method to maintain the battery in high power density constant current (CC) and constant voltage (CV) states. A thorough state space investigation is carried out in combination with modeling and testing to ensure that the electric bicycle charger operates effectively. Consequently, low power chargers are a good fit for the proposed single stage front-end converter, and a 250 W hardware prototype is used to verify the findings.

Optimizing Location and Power of Chargers to Reduce Interference in Battery-Less WSNs

Optimizing Location and Power of Chargers to Reduce Interference in Battery-Less WSNs

HBN/PVDF‐HFP and BNNS/PVDF‐HFP nanocomposites as flexible and lightweight dielectric capacitors: High energy storage performance via electrically insulating nanoparticles

AbstractAs the energy demand continuously increases, polymer‐based materials have attracted much attention for energy storage systems as dielectric capacitors due to their higher power density and charge–discharge rate than lithium‐ion batteries and supercapacitors. However, it is necessary to increase the energy density of dielectric capacitors. In this context, poly(vinylidene fluoride‐co‐hexafluoropropylene), PVDF‐HFP, matrix nanocomposites are produced by solution casting method reinforced with hexagonal boron nitride (hBN) nanoparticles and silane‐modified boron nitride nanosheets ‐BNNSs‐ (BNNS‐VTS) up to 10 wt.% filler content. The effects of filler content and surface modification of hBN/BNNSs on PVDF‐HFP matrix nanocomposites' microstructure, phase evolution, crystalization behavior, dielectric properties, and energy storage performance are discussed. 4% hBN/PVDF‐HFP nanocomposite demonstrates 641 MV·m−1 of breakdown strength and 23.2 J·cm−3 of discharged energy density due to hexagonal boron nitride's excellent electrical insulating behavior. The achieved values are 3.0 and 10.5 times superior to the values of the neat thin film, respectively, and they are noteworthy among hBN‐ or BNNS‐reinforced PVDF‐based nanocomposites, even in multi‐layered structures. Furthermore, 4% hBN/PVDF‐HFP presents a giant charge–discharge energy efficiency (92%). It is thus demonstrated that hBN/PVDF‐HFP nanocomposites hold a great potential to be used in energy storage applications as flexible and lightweight dielectric capacitors.Highlights PVDF‐HFP matrix nanocomposites for electrical energy storage as flexible dielectric capacitors hBN NPs and silane‐modified BNNSs are reinforced into the matrix by 0–10 wt.%. The effects of filler content and surface modification of hBN/BNNSs are discussed. 4% hBN loading results in 23.2 J·cm−3 energy density and 92% efficiency at 641 MV·m−1 breakdown strength. Those metrics are relatively high in hBN‐ or BNNS‐reinforced PVDF‐based nanocomposites.

Prelithiated Silicon Anodes for High-Energy and High-Power Lithium-Ion Batteries

Lithium-ion batteries (LIBs) are pivotal in powering modern electronic devices and next-generation land and air electric vehicles. Silicon-based anodes are considered the next technology to replace traditional graphite anodes due to their high theoretical capacity. However, the inherent challenges associated with their large volume expansion and high irreversible capacity loss (IRCL) limit their practical application. This abstract explores our patented strategy of prelithiation as a viable approach to mitigate the IRCL limitations of SiOx dominant anodes. Prelithiation involves the precise addition of supplemental lithium into the anode, mitigating the adverse effects of initial lithiation and enhancing overall cyclability, energy, power, and extreme fast charge capability for silicon oxide dominant LIBs. Various prelithiation techniques, including Li powder, Li slurry, Li-foil, and the chemical doping of SiOx are examined to evaluate their effectiveness in providing supplemental lithium. The effectiveness of the prelithiation process is assessed by examining the impact on the structural stability, cycling performance, power capability, and rate capability of SiOx dominant anodes integrated into high-capacity (~30 Ah) pouch cells. Our focus is to emphasize prelithiation as a practical and scalable solution to enhance the electrochemical performance of SiOx dominant anodes, contributing to the development of high-energy and high-power LIBs enabling advanced air mobility and high-performance electric vehicles. The findings presented in this abstract contribute to the growing body of knowledge aimed at advancing the fundamental understanding and practical implementation of prelithiation as an enabler for SiOx-based anodes in LIBs. Figure 1

The power control and efficiency optimization strategy of dynamic wireless charging system for multiple electric vehicles

PurposeThis study aims to solve the problem that both the speed and the required driving power of electric vehicles (EVs) will change during the dynamic wireless charging (DWC) process, making it difficult to charge EVs with a constant power considering the overall efficiency of DWC system, the numbers of EVs and the power supply capacity. Therefore, this paper proposes the power control and efficiency optimization strategies for multiple EVs.Design/methodology/approachThe wireless power charging system for multiple loads with a structure of double-sided LCC compensation topology is established. The expressions of optimal transmission efficiency and optimal equivalent impedance are derived. Taking the Tesla Model 3 as an example, a method to determine the number of EVs allowed by one transmitter coil and the overall charging power is proposed considering EV speed, power supply capacity, safe braking distance and overall efficiency. Then, the power control strategy, which can adapt to the changes of EV speed and the efficiency optimization strategy under different numbers of EVs are proposed.FindingsIn this paper, a method to determine the numbers of EVs allowed by one transmitter coil and the overall charging power is proposed considering EVs speed, power supply capacity, safe braking distance and overall efficiency. The accuracy of the charging power is good enough and the overall efficiency reaches a maximum of 91.79% when the load resistance changes from 5Ω to 20Ω.Originality/valueIn this paper, the power control and efficiency optimization strategy of DWC system for multiple EVs are proposed. Specifically, a method of designing the number of EVs and charging power allowed by one transmitter coil considering the factors of EV speed, power supply capacity, safe braking distance and overall efficiency is designed. The overall efficiency of the experiment reaches a maximum of 91.79% after adopting the optimization strategy.

An optimized AC side startup strategy of E‐STATCOM for ITER pulsed power electrical network

AbstractDuring the operation of the ITER machine, hundreds of MW/Var of active and reactive power will be exchanged with the grid. The E‐STATCOM scheme composed of the Modular Multilevel Converter (MMC) and split supercapacitor energy storage has been proposed to improve the power compensation performance of the existing reactive power compensation system in the previous study. However, one of the main technical challenges which is lack of research is to precharge all submodule capacitors and supercapacitors from zero to their nominal voltage values efficiently during a startup process. As the capacitance and operating voltage of supercapacitors are much different from capacitors in each submodule, the startup of E‐STATCOM is a more complicated process. To coordinate the energy exchange between submodule capacitors and supercapacitors, submodule capacitors and the grid, this paper presents an optimized four‐stage AC side startup strategy for the E‐STATCOM. The proposed method minimizes the use of current‐limiting resistors while suppressing the surge current in the zero‐voltage startup process of supercapacitors, in addition to optimizing the energy consumption. The pulse current charging, constant current charging and constant power charging strategies of supercapacitors are adopted in different charging stages, and the detailed coordinated control scheme between submodule capacitors and supercapacitors are described and analyzed. The effectiveness and performance of the proposed method are verified by simulation results and hardware‐in‐the‐loop (HIL) experiments.

Uncertain scheduling potential of charging stations under multi-attribute uncertain charging decisions of electric vehicles

A method for analyzing the uncertain adjustability of charging stations (CSs) under the influence of multi-attribute group decision-makings of electric vehicles (EVs) is proposed. Firstly, considering physical constraints of parameters such as charging power and energy stored, a model for characterizing the schedulability of a single EV under different charging modes including rated power charging, adjustable charging, and flexible charging and discharging is constructed. Secondly, since the charging mode selection of EVs is a comprehensive decision considering charging cost, charging time and other attributes, and individual decision-making is often affected by group users, an EV charging mode selection probability model is developed based on the multi-attribute group decision-making theory. Further, scheduling potential boundary parameters of CSs affected by the scheduling potential of all EVs in the station are derived based on the Minkowski sum theory, and their probability characteristics are calculated by combining the charging mode selection probability of single EVs and the schedulability under each mode. Finally, case studies prove the superiority of the proposed theory.

Dynamic Charging Optimization Algorithm for Electric Vehicles to Mitigate Grid Power Peaks

The rapid proliferation of electric vehicles (EVs) presents both opportunities and challenges for the electrical grid. While EVs offer a promising avenue for reducing greenhouse gas emissions and dependence on fossil fuels, their uncoordinated charging behavior can strain grid infrastructure, thus creating new challenges for grid operators and EV owners equally. The uncoordinated nature of electric vehicle charging may lead to the emergence of new peak loads. Grid operators typically plan for peak demand periods and deploy resources accordingly to ensure grid stability. Uncoordinated EV charging can introduce unpredictability and variability into peak load patterns, making it more challenging for operators to manage peak loads effectively. This paper examines the implications of uncoordinated EV charging on the electric grid to address this challenge and proposes a novel dynamic optimization algorithm tailored to manage EV charging schedules efficiently, mitigating grid power peaks while ensuring user satisfaction and vehicle charging requirements. The proposed “Proof of Need” (PoN) charging algorithm aims to schedule the charging of EVs based on collected data such as the state of charge (SoC) of the EV’s battery, the charger power, the number of connected vehicles per household, the end-user’s preferences, and the local distribution substation’s capacity. The PoN algorithm calculates a priority index for each EV and coordinates the charging of all connected EVs at all times in a way that does not exceed the maximum allocated power capacity. The algorithm was tested under different scenarios, and the results offer a comparison of the charging power demand between an uncoordinated EV charging baseline scenario and the proposed coordinated charging model, proving the efficiency of our proposed algorithm, thus reducing the charging demand by 40.8% with no impact on the overall total charging time.

The influence of socio-technical variables on vehicle-to-grid technology

Vehicle-to-grid technology (V2G) is a novel large scale energy storage option to improve the grid integration of renewable energy sources (RES). Using electric vehicle (EV) batteries to store and provide electricity to the grid, the intermittency of RES can be reduced. However, a successful implementation of this technology depends on various social and technological factors. This study analyses the influence of social and technical factors such as V2G acceptance (percentage of EV users that allow V2G energy transfer), EV battery availability for V2G service (percentage of the EV battery), EV adoption level (number of EVs in EV fleet) and the charger power for the energy transfer between the storage system and grid.Using Germany for the case study, a simulation model is developed and employed for the study. The base simulation results show that Germany needs 190 GW of PV and 170 GW of wind turbine installation to meet 80 % of electricity generation from RES in 2030. Further results show that an increased V2G acceptance and EV battery availability reduces the V2G contribution from individual EVs. A V2G acceptance of only 30 %, using half of the battery capacity dedicated to V2G, can help to reach an hourly reliability of 86.6 %. Having 50 % V2G acceptance, the hourly reliability increases by 5.3 %–91.9 %. The final analysis on charger power and EV adoption level highlights that a normal charger power of 7 kW or 11 kW can successfully accommodate V2G service. The study's overall results indicate that V2G technology will be an effective storage solution for Germany in the future.

Enhanced Thermoelectric Performance of PbTe Nanocomposites with Ag Nanoinclusions

Nanocomposites have already been widely used to enhance thermoelectric performance since they exhibit exceptionally low lattice thermal conductivities. Further improvement is expected to arise from boosting the power factor and charge carrier relevant figure of merit ZT with nanoinclusions. Here we present that Ag nanoscale inclusions embedding in the n-PbTe can meet this requirement. The quantitative relationships between such nanostructures in PbTe and thermoelectric properties, using a versatile model including the details of geometry, electron–phonon interactions, quantization, and tunneling, showed that the Seebeck coefficient can be significantly enhanced due to interface potential barrier induced by Ag nanoinclusions. Additionally, it was found that high-concentration Ag nanoinclusions with 1–2 nm radius can effectively enhance the thermoelectric performance of PbTe through energy-selective carrier scattering, especially around room temperature. The power factor and charge carrier relevant figure of merit ZT can be elevated by at least 80% and 260%, respectively. These findings highlight effective strategies to nanostructuring for overcoming the high threshold to commercial application for cooling and power generation.