Charging Properties and Particle Dynamics of Chang’e-5 Lunar Sample in an External Electric Field

Facing the challenges of in-situ utilization of lunar regolith resources,applying an external electric field to manipulate lunar particles has become a promising method for space particle control,which mainly depends on the particle charging properties in the applied electric field.Using the surficial lunar regolith samples brought back from the Moon by the Chang’e-5 mission(CE5 LS),this work successively studied their charging properties,particle dynamics,and their collision damages to aerospace materials under the action of an external electric field in high-vacuum conditions.The results indicated that the charging pro-cess and electrostatic projection of lunar regolith particles under high-vacuum conditions were different from those under atmosphere conditions.The particle diameter range of CE5 LS used in the experiment is 27.7-139.0 lm.For electric field strength of 3-12 kV·cm^(-1),the charge obtained by CE5 LS is 4.8×10^(-15)-4.7×10^(-13) C and the charge-to-mass ratio is 1.2×10^(-5)-6.8×10^(-4) C·kg^(-1).The CE5 LS is easier to be negatively charged in an external electric field.Furthermore,significant damages were observed on the target impact surfaces,indicating severe influences of lunar regolith particles on aerospace materials.Our work contributes to a more comprehensive understanding of physical mechanisms controlling the lunar regolith shielding and utilization,and will inspire broad efforts to develop the lunar in-situ engi-neering solutions.

Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17 W during charging were designed and simulated in the range of 0-12000 s using COMSOL Multiphysics software. This study efficiently employs the Taguchi optimization technique to develop lithium-ion batteries capable of storing a predetermined average electric power during the charging phase. Therefore, this method enables the battery to achieve complete charging within a specific timeframe tailored to a specificapplication. The implementation of this method can save costs, time, and materials compared with other alternative methods, such as the trial-and-error approach.

Strategic Placement of Charging Stations for Enhanced Electric Vehicle Adoption in San Diego, California

California mandated that 100% of vehicles sold must be electric by 2035. As electric vehicles (EVs) reach a higher penetration of the car sector, cities will need to provide publicly accessible charging stations to meet the charging demand of people who do not have access to a private charging spot like a personal garage. We have chosen to limit our scope to San Diego County due to its non-trivial size, well-defined shape, and dependence on personal vehicles;this project models 100% of current vehicles as electric, roughly 2.5 million. By planning for the future, our model becomes more useful as well as more equitable. We anticipate that our model will find locations that can service multiple population centers, while also maximizing distance to other stations. Sensitivity analysis and testing of our algorithms are conducted for Coronado Island, an island with 24,697 residents. Our formulation is then scaled to set the parameters for the whole county.

Study on site selection planning of urban electric vehicle charging station

The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric vehicles.Considering the costs of both operators and users,a site selection model for optimal layout planning of charging stations is constructed,and a queuing theory approach is used to determine the charging pile configuration to meet the charging demand in the planning area.To solve the difficulties of particle swarm global optimization search,the improved random drift particle swarm optimization(IRDPSO)and Voronoi diagram are used to jointly solve for the optimal layout of electric vehicles.The final arithmetic analysis verifies the feasibility and practicality of the model and algorithm,and the results show that the total social cost is minimized when the charging station is 9,the location of the charging station is close to the center of gravity and the layout is reasonable.

Designing an Effective Method for Automatic Electric Vehicle Charging Stations in a Static Environment

This article outlines an Effective Method for Automatic Electric Vehicle Charging Stations in a Static Environment. It consists of investigated wireless transformer structures with various ferrite forms. WPT technology has rapidly advanced in the last few years. At kilowatt power levels, the transmission distance grows from a few millimeters to several hundred millimeters with a grid to load efficiency greater than 90%. The improvements have made the WPT more appealing for electric vehicle (EV) charging applications in both static and dynamic charging scenarios. Static and dynamic WEVCS, two of the main applications, are described, and current developments with features from research facilities, academic institutions, and businesses are noted. Additionally, forthcoming concepts based WEVCS are analyzed and examined, including “dynamic” wireless charging systems (WCS). A dynamic wireless power transfer (DWPT) system, which can supply electricity to moving EVs, is one of the feasible alternatives. The moving secondary coil is part of the dynamic WPT system, which also comprises of many fixed groundside (primary) coils. An equivalent circuit between the stationary system and the dynamic WPT system that results from the stationary system is demonstrated by theoretical investigations. The dynamic WPT system’s solenoid coils outperform circular coils in terms of flux distribution and misalignment. The WPT-related EV wireless charging technologies were examined in this study. WPT can assist EVs in overcoming their restrictions on cost, range, and charging time.

Charging load prediction method for expressway electric vehicles considering dynamic battery state-of-charge and user decision

Accurate prediction of electric vehicle(EV)charging loads is a foundational step in the establishment of expressway charging infrastructures.This study introduces an approach to enhance the precision of expressway EV charging load predictions.The method considers both the battery dynamic state-of-charge(SOC)and user charging decisions.Expressway network nodes were first extracted using the open Gaode Map API to establish a model that incorporates the expressway network and traffic flow fea-tures.A Gaussian mixture model is then employed to construct a SOC distribution model for mixed traffic flow.An innovative SOC dynamic translation model is then introduced to capture the dynamic characteristics of traffic flow SOC values.Based on this foun-dation,an EV charging decision model was developed which considers expressway node distinctions.EV travel characteristics are extracted from the NHTS2017 datasets to assist in constructing the model.Differentiated decision-making is achieved by utilizing improved Lognormal and Sigmoid functions.Finally,the proposed method is applied to a case study of the Lian-Huo expressway.An analysis of EV charging power converges with historical data and shows that the method accurately predicts the charging loads of EVs on expressways,thus revealing the efficacy of the proposed approach in predicting EV charging dynamics under expressway scenarios.

Electric vehicle optimal scheduling method considering charging piles matching based on edge intelligence

To adress the problems of insufficient consideration of charging pile resource limitations,discrete-time scheduling methods that do not meet the actual demand and insufficient descriptions of peak-shaving response capability in current electric vehicle(EV)opti-mization scheduling,edge intelligence-oriented electric vehicle optimization scheduling and charging station peak-shaving response capability assessment methods are proposed on the basis of the consideration of electric vehicle and charging pile matching.First,an edge-intelligence-oriented electric vehicle regulation frame for charging stations is proposed.Second,continuous time variables are used to represent the available charging periods,establish the charging station controllable EV load model and the future available charging pile mathematical model,and establish the EV and charging pile matching matrix and constraints.Then,with the goal of maximizing the user charging demand and reducing the charging cost,the charging station EV optimal scheduling model is established,and the EV peak response capacity assessment model is further established by considering the EV load shifting constraints under different peak response capacities.Finally,a typical scenario of a real charging station is taken as an example for the analysis of optimal EV scheduling and peak shaving response capacity,and the proposed method is compared with the traditional method to verify the effectiveness and practicality of the proposed method.

Electrothermal Model Based Remaining Charging Time Prediction of Lithium-Ion Batteries against Wide Temperature Range

Battery remaining charging time(RCT)prediction can facilitate charging management and alleviate mileage anxiety for electric vehicles(EVs).Also,it is of great significance to improve EV users’experience.However,the RCT for a lithiumion battery pack in EVs changes with temperature and other battery parameters.This study proposes an electrothermal model-based method to accurately predict battery RCT.Firstly,a characteristic battery cell is adopted to represent the battery pack,thus an equivalent circuit model(ECM)of the characteristic battery cell is established to describe the electrical behaviors of a battery pack.Secondly,an equivalent thermal model(ETM)of the battery pack is developed by considering the influence of ambient temperature,thermal management,and battery connectors in the battery pack to calculate the temperature which is then fed back to the ECM to realize electrothermal coupling.Finally,the RCT prediction method is proposed based on the electrothermal model and validated in the wide temperature range from-20℃to 45℃.The experimental results show that the prediction error of the RCT in the whole temperature range is less than 1.5%.

Modulating charge separation and transfer for high-performance photoelectrodes via built-in electric field

Constructing a built-in electric field has emerged as a key strategy for enhancing charge separation and transfer,thereby improving photoelectrochemical performance.Recently,considerable efforts have been devoted to this endeavor.This review systematically summarizes the impact of built-in electric fields on enhancing charge separation and transfer mechanisms,focusing on the modulation of built-in electric fields in terms of depth and orderliness.First,mechanisms and tuning strategies for built-in electric fields are explored.Then,the state-of-the-art works regarding built-in electric fields for modulating charge separation and transfer are summarized and categorized according to surface and interface depth.Finally,current strategies for constructing bulk built-in electric fields in photoelectrodes are explored,and insights into future developments for enhancing charge separation and transfer in high-performance photoelectrochemical applications are provided.

Selection of Negative Charged Acidic Polar Additives to Regulate Electric Double Layer for Stable Zinc Ion Battery

Zinc-ion batteries are promising for large-scale electrochemical energy storage systems,which still suffer from interfacial issues,e.g.,hydrogen evolution side reaction(HER),self-corrosion,and uncontrollable dendritic Zn electrodeposition.Although the regulation of electric double layer(EDL)has been verified for interfacial issues,the principle to select the additive as the regulator is still misted.Here,several typical amino acids with different characteristics were examined to reveal the interfacial behaviors in regulated EDL on the Zn anode.Negative charged acidic polarity(NCAP)has been unveiled as the guideline for selecting additive to reconstruct EDL with an inner zincophilic H_(2)O-poor layer and to replace H_(2)O molecules of hydrated Zn^(2+)with NCAP glutamate.Taking the synergistic effects of EDL regulation,the uncontrollable interface is significantly stabilized from the suppressed HER and anti-self-corrosion with uniform electrodeposition.Consequently,by adding NCAP glutamate,a high average Coulombic efficiency of 99.83%of Zn metal is achieved in Zn|Cu asymmetrical cell for over 2000 cycles,and NH4V4O10|Zn full cell exhibits a high-capacity retention of 82.1%after 3000 cycles at 2 A g^(-1).Recapitulating,the NCAP principle posted here can quicken the design of trailblazing electrolyte additives for aqueous Zn-based electrochemical energy storage systems.

Diffusion Equations of the Electric Charges and Magnetic Flux

Innovative definitions of the electric and magnetic diffusivities through conducting mediums and innovative diffusion equations of the electric charges and magnetic flux are verified in this article. Such innovations depend on the analogy of the governing laws of diffusion of the thermal, electrical, and magnetic energies and newly defined natures of the electric charges and magnetic flux as energy, or as electromagnetic waves, that have electric and magnetic potentials. The introduced diffusion equations of the electric charges and magnetic flux involve Laplacian operator and the introduced diffusivities. Both equations are applied to determine the electric and magnetic fields in conductors as the heat diffusion equation which is applied to determine the thermal field in steady and unsteady heat diffusion conditions. The use of electric networks for experimental modeling of thermal networks represents sufficient proof of similarity of the diffusion equations of both fields. By analysis of the diffusion phenomena of the three considered modes of energy transfer;the rates of flow of these energies are found to be directly proportional to the gradient of their volumetric concentration, or density, and the proportionality constants in such relations are the diffusivity of each energy. Such analysis leads also to find proportionality relations between the potentials of such energies and their volumetric concentrations. Validity of the introduced diffusion equations is verified by correspondence their solutions to the measurement results of the electric and magnetic fields in microwave ovens.

The effect of ions on liquid-solid interface investigated by charge sensitive direct current droplet-based electricity generator

The contact electrification(CE)between DI water and SiO_(2)or fluorinated polymer has been proven to be mainly due to electron transfer,which is significantly influenced by ions in solution.However,how these ions in water affect the charge transfer at the liquid-solid(L-S)interface is still unresolved,especially for the already charged friction layer.Here,a direct current droplet-based electricity generator(DC-DEG)which is sensitive to the change of charge transfer at the L-S interface is adopted to detect the effects of ions in the neutral salt solution on the charged PTFE surface.The distribution of ions on the charged L-S interface(the change of electric potential on the solid surface)and its effects on the output of DC-DEGs have been studied.The results indicate that the charge transfer of droplets and then the output of DC-DEGs are closely related to the concentrations of salt solutions.Anions can enhance the surface potential of PTFE due to their adsorptions on PFTE while cations can reduce it due to their screen effect.At low ionic concentrations,the surface potential enhancement caused by anion adsorption is larger than that surface potential reduction caused by screen effect from cations.At high ionic concentrations,the electrostatic screen effect of cations increases a lot to weaken the surface potential and reducing the charge separation of droplets induced by electrostatic induction(EI).This work explains the redistribution process of ions at the L-S interface and also provides a clever solution for improving the electrical output performance of DEGs.

Design scheme for fast charging station for electric vehicles with distributed photovoltaic power generation

The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of "rationalization, modularization and intelligentization" of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.

Review of optimized layout of electric vehicle charging infrastructures

Electric vehicle is a kind of new energy vehicle which uses batteries as energy supply unit.A huge gap in charging infrastructures will be created by the expansion of electric vehicles.The effectiveness and rationality of charging facilities will directly affect the convenience and economy of the users,as well as the safe operation of the power grid.Three types of charging facilities:charging pile,charging station and battery swap station are introduced in this paper.According to the different methods of charging infrastructure planning,the research status of the method of determining charging demand points is expounded.And the spatial distribution of charging demand points extracted by the current site selection method has a certain deviation.Then the models and algorithms of charging infrastructure optimized layout are reviewed.Currently,many researches focus on three categories optimization objectives:benefit of power company side,investment cost of charging facility and user side cost,and the genetic algorithm and particle swarm optimization are the main solving algorithms.Finally,the relative methods and development trend of the charging infrastructures optimized layout are summarized,and some suggestions on the optimized layout of electric vehicle charging infrastructures are given forward.

Location of Electric Vehicle Charging Station Based on Spatial Clustering and Multi-hierarchical Fuzzy Evaluation

For the charging station construction of electric vehicle,location selecting is a key issue.There are two problems in location selection of the electric vehicle charging station.One is determining the location of charging station;the other is evaluating the location of charging station.To determine the charging station location,an spatial clustering algorithm is proposed and programmed.The example simulation shows the effectiveness of the spatial clustering algorithm.To evaluate the charging station location,a multi-hierarchical fuzzy method is proposed.Based on the location factors of electric vehicle charging station,the hierarchical evaluation structure of electric vehicle charging station location is constructed,including three levels,4first-class factors and 14second-class factors.The fuzzy multi-hierarchical evaluation model and algorithm are built.The analysis results show that the multi-hierarchical fuzzy method can reasonably complete the electric vehicle charging station location evaluation.

Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

Electric vehicle charging identification and positioning is critically important to achieving automatic charging.In terms of the problem of automatic charging for electric vehicles,a dual recognition and positioning method based on deep learning is proposed.The method is divided into two parts:global recognition and localization and local recognition and localization.In the specific implementation process,the collected pictures of electric vehicle charging attitude are classified and labeled.It is trained with the improved YOLOv4 networkmodel and the corresponding detectionmodel is obtained.The contour of the electric vehicle is extracted by the BiSeNet semantic segmentation algorithm.The minimum external rectangle is used for positioning of the electric vehicle.Based on the location relationship between the charging port and the electric vehicle,the rough location information of the charging port is obtained.The automatic charging equipment moves to the vicinity of the charging port,and the camera near the charging gun collects pictures of the charging port.The model is detected by the Hough circle,the KM algorithmis used for featurematching,and the homography matrix is used to solve the attitude.The results show that the dual identification and location method based on the improved YOLOv4 algorithm proposed in this paper can accurately locate the charging port.The accuracy of the charging connection can reach 80%.It provides an effective way to solve the problems of automatic charging identification and positioning of electric vehicles and has strong engineering practical value.

Influence of Low Speed Rolling Movement on High Electrical Breakdown for Water Dielectric with Microsecond Charging

By means of a coaxial apparatus, high electrical breakdown experiments are carried out in the rest state and the low speed rolling state with microsecond charging and the experimental results are analyzed. The conclusions are： （1） the breakdown stress of water dielectric in the rolling state is in good agreement with that in Martin formula, and so is that in the rest state; （2） the breakdown stress of water dielectric in the rolling state is about 5% higher than that in the rest state; （3） the results simulated with ANSYS demonstrate that the breakdown stress of water dielectric decreases when the bubbles appear near the surface of electrodes; （4） the primary mechanism to increase the breakdown stress of water dielectric in the rolling state is that the bubbles are driven away and the number of bubbles near the surface of electrodes is decreased by rolling movement.

Development of hydraulic power unit and accumulator charging circuit for electricity generation,storage and distribution

It is the purpose of the present paper to convert hydraulic energy to electric energy and saves both the pressure and electrical energy for re - use during the next system upstroke using two secondary units coupled to induction motor to drive cylinder loads. During upstroke operation, the variable pump/motor （P/M） driven by both electric motor and the second （P/M） works as hydraulic pump and output flow to the cylinders which drive the load. During load deceleration, the cylinders work as pump while the operation of the two secondary units are reversed, the variable （P/M） works as a motor generating a torque with the electric motor to drive the other （P/M） which transforms mechanical energy to hydraulic energy that is saved in the accumulator. When the energy storage capacity of the accumulator is attained as the operation continues, energy storage to the accumulator is thermostatically stopped while the induction motor begins to work as a generator and generates electricity that is stored in the power distribution unit. Simulations were performed using a limited PT2 Block, i.e. 2nd-order transfer function with limitation of slope and signal output to determine suitable velocity of the cylinder which will match high performance and system stability. A mathematical model suited to the simulation of the hydraulic accumulator both in an open-or close-loop system is presented. The quest for improvement of lower energy capacity storage, saving and re-utilization of the conventional accumulator resulting in the short cycle time usage of hydraulic accumulators both in domestic and industrial purposes necessitates this research. The outcome of the research appears to be very efficient for generating fluctuation free electricity, power quality and reliability, energy saving/reutilization and system noise reduction.

A Novel Ultra Short-Term Load Forecasting Method for Regional Electric Vehicle Charging Load Using Charging Pile Usage Degree

Electric vehicle(EV)charging load is greatly affected by many traffic factors,such as road congestion.Accurate ultra short-term load forecasting(STLF)results for regional EV charging load are important to the scheduling plan of regional charging load,which can be derived to realize the optimal vehicle to grid benefit.In this paper,a regional-level EV ultra STLF method is proposed and discussed.The usage degree of all charging piles is firstly defined by us based on the usage frequency of charging piles,and then constructed by our collected EV charging transactiondata in thefield.Secondly,these usagedegrees are combinedwithhistorical charging loadvalues toform the inputmatrix for the deep learning based load predictionmodel.Finally,long short-termmemory(LSTM)neural network is used to construct EV charging load forecastingmodel,which is trained by the formed inputmatrix.The comparison experiment proves that the proposed method in this paper has higher prediction accuracy compared with traditionalmethods.In addition,load characteristic index for the fluctuation of adjacent day load and adjacent week load are proposed by us,and these fluctuation factors are used to assess the prediction accuracy of the EV charging load,together with the mean absolute percentage error(MAPE).