Exploration of Energy-Saving Technologies in Building Electrical System Design

Green energy conservation is the mainstream trend in the current development of the construction industry.The application of energy-saving technology in building electrical system design can effectively reduce energy consumption,avoid unnecessary energy consumption,and truly achieve energy conservation and environmental protection.Based on this,the article elaborates on the principles of energy-saving design in building electrical systems,and actively explores the application of energy-saving technologies from different perspectives such as optimizing power supply and distribution system design,adopting high-efficiency energy-saving lighting equipment,applying renewable energy,promoting smart home technology,and improving the efficiency of building electrical equipment.

SOLIDWORKS Electrical在通过式脚踏封口机自动化改造设计中的应用

小型企业塑封工艺中通过式脚踏封口机应用广泛,但在塑封重型工件时,工人操作非常费力且次品率高,无法保障塑封质量,为此对其进行机构优化与软硬件设计自动化改造。利用SOLIDWORKS Electrical快速建立3D虚拟电气配盘与生成各类BOM清单,大大缩短了研发周期,安装人员还可以根据虚拟电气装配路径进行准确安装。最终设计出结构合理,满足生产工艺要求的自动化装置,企业以极少改造成本提质增效,为机电一体化装置自动化设计提供了一个高效开发途径。

Green,Sustainable Architectural Bamboo with High Light Transmission and Excellent Electromagnetic Shielding as a Candidate for Energy-Saving Buildings

Currently,light-transmitting,energy-saving,and electromagnetic shielding materials are essential for reducing indoor energy consumption and improving the electromagnetic environment.Here,we developed a cellulose composite with excellent optical transmittance that retained the natural shape and fiber structure of bamboo.The modified whole bamboo possessed an impressive optical transmittance of approximately 60%at 6.23 mm,illuminance of 1000 luminance(lux),water absorption stability(mass change rate less than 4%),longitudinal tensile strength(46.40 MPa),and surface properties(80.2 HD).These were attributed to not only the retention of the natural circular hollow structure of the bamboo rod on the macro,but also the complete bamboo fiber skeleton template impregnated with UV resin on the micro.Moreover,a multilayered device consisting of translucent whole bamboo,transparent bamboo sheets,and electromagnetic shielding film exhibited remarkable heat insulation and heat preservation performance as well as an electromagnetic shielding performance of 46.3 dB.The impressive optical transmittance,mechanical properties,thermal performance,and electromagnetic shielding abilities combined with the renewable and sustainable nature,as well as the fast and efficient manufacturing process,make this bamboo composite material suitable for effective application in transparent,energy-saving,and electromagnetic shielding buildings.

A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple locations.For multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed instruments.Currently,there is no such EFM with specified speed and phase control performance of the rotary part.Thus,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS module.Five EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test observation.Here we describe the design and a simple calibration method for our new EFM array.Data analysis method based on the assumption of a simple monopole charge structure is also summarized.For validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF bands.Initial results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.

Optimal transcorneal electrical stimulation parameters for preserving photoreceptors in a mouse model of retinitis pigmentosa

Retinitis pigmentosa is a hereditary retinal disease that affects rod and cone photoreceptors,leading to progressive photoreceptor loss.Previous research supports the beneficial effect of electrical stimulation on photoreceptor survival.This study aims to identify the most effective electrical stimulation parameters and functional advantages of transcorneal electrical stimulation(tcES)in mice affected by inherited retinal degeneration.Additionally,the study seeked to analyze the electric field that reaches the retina in both eyes in mice and post-mortem humans.In this study,we recorded waveforms and voltages directed to the retina during transcorneal electrical stimulation in C57BL/6J mice using an intraocular needle probe with rectangular,sine,and ramp waveforms.To investigate the functional effects of electrical stimulation on photoreceptors,we used human retinal explant cultures and rhodopsin knockout(Rho^(-/-))mice,demonstrating progressive photoreceptor degeneration with age.Human retinal explants isolated from the donors’eyes were then subjected to electrical stimulation and cultured for 48 hours to simulate the neurodegenerative environment in vitro.Photoreceptor density was evaluated by rhodopsin immunolabeling.In vivo Rho^(-/-)mice were subjected to two 5-day series of daily transcorneal electrical stimulation using rectangular and ramp waveforms.Retinal function and visual perception of mice were evaluated by electroretinography and optomotor response(OMR),respectively.Immunolabeling was used to assess the morphological and biochemical changes of the photoreceptor and bipolar cells in mouse retinas.Oscilloscope recordings indicated effective delivery of rectangular,sine,and ramp waveforms to the retina by transcorneal electrical stimulation,of which the ramp waveform required the lowest voltage.Evaluation of the total conductive resistance of the post-mortem human compared to the mouse eyes indicated higher cornea-to-retina resistance in human eyes.The temperature recordings during and after electrical stimulation indicated no significant temperature change in vivo and only a subtle temperature increase in vitro(~0.5-1.5°C).Electrical stimulation increased photoreceptor survival in human retinal explant cultures,particularly at the ramp waveform.Transcorneal electrical stimulation(rectangular+ramp)waveforms significantly improved the survival and function of S and M-cones and enhanced visual acuity based on the optomotor response results.Histology and immunolabeling demonstrated increased photoreceptor survival,improved outer nuclear layer thickness,and increased bipolar cell sprouting in Rho^(-/-)mice.These results indicate that transcorneal electrical stimulation effectively delivers the electrical field to the retina,improves photoreceptor survival in both human and mouse retinas,and increases visual function in Rho^(-/-)mice.Combined rectangular and ramp waveform stimulation can promote photoreceptor survival in a minimally invasive fashion.

Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

Patterning single-layer materials by electrical breakdown using atomic force microscopy

The development of nanoelectronics and nanotechnologies has been boosted significantly by the emergence of 2D materials because of their atomic thickness and peculiar properties,and developing a universal,precise patterning technology for single-layer 2D materials is critical for assembling nanodevices.Demonstrated here is a nanomachining technique using electrical breakdown by an AFM tip to fabricate nanopores,nanostrips,and other nanostructures on demand.This can be achieved by voltage scanning or applying a constant voltage while moving the tip.By measuring the electrical current,the formation process on single-layer materials was shown quantitatively.The present results provide evidence of successful pattern fabrication on single-layer MoS2,boron nitride,and graphene,although further confirmation is still needed.The proposed method holds promise as a general nanomachining technology for the future.

Research on Interpolation Method for Missing Electricity Consumption Data

Missing value is one of the main factors that cause dirty data.Without high-quality data,there will be no reliable analysis results and precise decision-making.Therefore,the data warehouse needs to integrate high-quality data consistently.In the power system,the electricity consumption data of some large users cannot be normally collected resulting in missing data,which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate.For the problem of missing electricity consumption data,this study proposes a group method of data handling(GMDH)based data interpolation method in distribution power networks and applies it in the analysis of actually collected electricity data.First,the dependent and independent variables are defined from the original data,and the upper and lower limits of missing values are determined according to prior knowledge or existing data information.All missing data are randomly interpolated within the upper and lower limits.Then,the GMDH network is established to obtain the optimal complexity model,which is used to predict the missing data to replace the last imputed electricity consumption data.At last,this process is implemented iteratively until the missing values do not change.Under a relatively small noise level(α=0.25),the proposed approach achieves a maximum error of no more than 0.605%.Experimental findings demonstrate the efficacy and feasibility of the proposed approach,which realizes the transformation from incomplete data to complete data.Also,this proposed data interpolation approach provides a strong basis for the electricity theft diagnosis and metering fault analysis of electricity enterprises.

Electric field and force characteristic of dust aerosol particles on the surface of high-voltage transmission line

High-voltage transmission lines play a crucial role in facilitating the utilization of renewable energy in regions prone to desertification. The accumulation of atmospheric particles on the surface of these lines can significantly impact corona discharge and wind-induced conductor displacement. Accurately quantifying the force exerted by particles adhering to conductor surfaces is essential for evaluating fouling conditions and making informed decisions. Therefore, this study investigates the changes in electric field intensity along branched conductors caused by various fouling layers and their resulting influence on the adhesion of dust particles. The findings indicate that as individual particle size increases, the field strength at the top of the particle gradually decreases and eventually stabilizes at approximately 49.22 k V/cm, which corresponds to a field strength approximately 1.96 times higher than that of an unpolluted transmission line. Furthermore,when particle spacing exceeds 15 times the particle size, the field strength around the transmission line gradually decreases and approaches the level observed on non-adhering surface. The electric field remains relatively stable. In a triangular arrangement of three particles, the maximum field strength at the tip of the fouling layer is approximately 1.44 times higher than that of double particles and 1.5 times higher compared to single particles. These results suggest that particles adhering to the transmission line have a greater affinity for adsorbing charged particles. Additionally, relevant numerical calculations demonstrate that in dry environments, the primary adhesion forces between particles and transmission lines follow an order of electrostatic force and van der Waals force. Specifically, at the minimum field strength, these forces are approximately74.73 times and 19.43 times stronger than the gravitational force acting on the particles.

Characterization of Aquifers in Crystalline and Crystallophyll Basement Zones Using the Electrical Resistivity Method (Trails and Electrical Soundings) in the Gagnoa Region, (Central-Western Côte d’Ivoire)

Introduction: Located in the central-western part of Côte d’Ivoire, the subsoil of the Gagnoa region is made up of sedimentary volcano formations and granitoids with developed fracturing. This complex Precambrian basement contains most of the region’s water resources. This is at the origin of the high failure rate during the various hydrogeological prospecting campaigns. Methodology: The database consists of resistivities from 42 holes and 51 trails drilled as part of the implementation of high-throughput drilling in the study area. The objective of this study is to deepen the knowledge of the fissured basement by interpreting profile curves and electrical soundings. It will be a question of classifying the different types of anomalies obtained on the profiles and their shapes. The orientation of the lineaments observed on the profiles was determined. Results: The interpretation of the geophysical data revealed various anomalies, the main ones being of the CC (Conductor Compartment) and CEDP (Contact between two bearings) types. These types of anomalies are mainly expressed in various forms: the “V”, “W” and “U” shapes. From these anomalies and the appearance of the electrical profiles, lineaments and their orientations were identified with N90-100, N130-140, N170-180 as major orientations. Conclusion: These results could contribute to a better understanding of the fractured environment of the Gagnoa region.

Reliability evaluation of IGBT power module on electric vehicle using big data

There are challenges to the reliability evaluation for insulated gate bipolar transistors(IGBT)on electric vehicles,such as junction temperature measurement,computational and storage resources.In this paper,a junction temperature estimation approach based on neural network without additional cost is proposed and the lifetime calculation for IGBT using electric vehicle big data is performed.The direct current(DC)voltage,operation current,switching frequency,negative thermal coefficient thermistor(NTC)temperature and IGBT lifetime are inputs.And the junction temperature(T_(j))is output.With the rain flow counting method,the classified irregular temperatures are brought into the life model for the failure cycles.The fatigue accumulation method is then used to calculate the IGBT lifetime.To solve the limited computational and storage resources of electric vehicle controllers,the operation of IGBT lifetime calculation is running on a big data platform.The lifetime is then transmitted wirelessly to electric vehicles as input for neural network.Thus the junction temperature of IGBT under long-term operating conditions can be accurately estimated.A test platform of the motor controller combined with the vehicle big data server is built for the IGBT accelerated aging test.Subsequently,the IGBT lifetime predictions are derived from the junction temperature estimation by the neural network method and the thermal network method.The experiment shows that the lifetime prediction based on a neural network with big data demonstrates a higher accuracy than that of the thermal network,which improves the reliability evaluation of system.

Harnessing overlapped temperature-salinity gradient in solar-driven interfacial seawater evaporation for efficient steam and electricity generation

Solar-driven interfacial water evaporation(SIWE)offers a superb way to leverage concentrated solar heat to minimize energy dissipation during seawater desalination.It also engenders overlapped temperaturesalinity gradient(TSG)between water-air interface and adjacent seawater,affording opportunities of harnessing electricity.However,the efficiency of conventional SIWE technologies is limited by significant challenges,including salt passivation to hinder evaporation and difficulties in exploiting overlapped TSG simultaneously.Herein,we report self-sustaining hybrid SIWE for not only sustainable seawater desalination but also efficient electricity generation from TSG.It enables spontaneous circulation of salt flux upon seawater evaporation,inducing a self-cleaning evaporative interface without salt passivation for stable steam generation.Meanwhile,this design enables spatial separation and simultaneous utilization of overlapped TSG to enhance electricity generation.These benefits render a remarkable efficiency of90.8%in solar energy utilization,manifesting in co-generation of solar steam at a fast rate of 2.01 kg m^(-2)-h^(-1)and electricity power of 1.91 W m^(-2)with high voltage.Directly interfacing the hybrid SIWE with seawater electrolyzer constructs a system for water-electricity-hydrogen co-generation without external electricity supply.It produces hydrogen at a rapid rate of 1.29 L h^(-1)m^(-2)and freshwater with 22 times lower Na+concentration than the World Health Organization(WHO)threshold.

Coexisting fast–slow dendritic traveling waves in a 3D-array electric field coupled neuronal network

Coexistence of fast and slow traveling waves without synaptic transmission has been found in hhhippocampal tissues,which is closely related to both normal brain activity and abnormal neural activity such as epileptic discharge. However, the propagation mechanism behind this coexistence phenomenon remains unclear. In this paper, a three-dimensional electric field coupled hippocampal neural network is established to investigate generation of coexisting spontaneous fast and slow traveling waves. This model captures two types of dendritic traveling waves propagating in both transverse and longitude directions: the N-methyl-D-aspartate(NMDA)-dependent wave with a speed of about 0.1 m/s and the Ca-dependent wave with a speed of about 0.009 m/s. These traveling waves are synaptic-independent and could be conducted only by the electric fields generated by neighboring neurons, which are basically consistent with the in vitro data measured experiments. It is also found that the slow Ca wave could trigger generation of fast NMDA waves in the propagation path of slow waves whereas fast NMDA waves cannot affect the propagation of slow Ca waves. These results suggest that dendritic Ca waves could acted as the source of the coexistence fast and slow waves. Furthermore, we also confirm the impact of cellular spacing heterogeneity on the onset of coexisting fast and slow waves. The local region with decreasing distances among neighbor neurons is more liable to promote the onset of spontaneous slow waves which, as sources, excite propagation of fast waves. These modeling studies provide possible biophysical mechanisms underlying the neural dynamics of spontaneous traveling waves in brain tissues.

Electrically controllable spin filtering in zigzag phosphorene nanoribbon based normal–antiferromagnet–normal junctions

We investigated the electric controllable spin-filtering effect in a zigzag phosphorene nanoribbon(ZPNR) based normal–antiferromagnet–normal junction. Two ferromagnets are closely coupled to the edges of the nanoribbon and form the edge-to-edge antiferromagnetism. Under an in-plane electric field, the two degenerate edge bands of the edge-to-edge antiferromagnet split into four spin-polarized sub-bands and a 100% spin-polarized current can be easily induced with the maximal conductance 2e~2/h. The spin polarization changes with the strength of the electric field and the exchange field,and changes sign at opposite electric fields. The spin-polarized current switches from one edge to the other by reversing the direction of the electric field. The edge current can also be controlled spatially by changing the electric potential of the scattering region. The manipulation of edge current is useful in spin-transfer-torque magnetic random-access memory and provides a practical way to develop controllable spintronic devices.

Innovation and Firm Co-ownership Network in China’s Electric Vehicle Industry

Firms are embedded in complex networks,where diverse ideas combine and generate new ideas.Shareholders of firms are of-ten seen as critical external resources that have significant influence on firm innovation.The current literature tends to focus on the rela-tionship between firms and their shareholders,while paying less attention to the connections between firms with the same shareholders.This article identifies two types of network spillover effects,intra-city network effect and inter-city network effect,by visualizing the co-ownership networks in China’s electric vehicle(EV)industry.We find that firms with the same shareholders,which are defined as co-owned EV firms,are more innovative than non-co-owned ones.Furthermore,there are two dominant types of firm co-ownership ties formed by corporate and financial institution shareholders.While corporate shareholders help exploiting local tacit knowledge,financial institutions are more active in bridging inter-city connections.The conclusion is confirmed at both firm and city levels.This paper theor-izes the firm co-ownership network as a new form of institutional proximity and tested the result empirically.For policy consideration,we have emphasized the importance of building formal or informal inter-firm network,and the government should further enhance the knowledge flow channel by institutional construction.

Reducing Operation Emissions and Improving Work Efficiency Using a Pure Electric Wheel Drive Tractor

In response to the problems of excessive greenhouse-gas and particulate emissions and the low traction efficiency of conventional diesel tractors in the field,a purely electric wheel-side drive tractor was studied,including an electric motor drive system,a battery ballast system,and an electro–hydraulic suspension system.This paper develops a dynamics model of an electric tractor-ploughing unit under complex soil conditions,leading to the proposal of an active control method for drive wheel torque and a joint control method for the traction force of the suspension system and the front-and rear-axle loads of a tractor.Finally,the tractor is prototyped and assembled,and ploughing tests are carried out.The ploughing results show that the active torque-distribution control method proposed in this study reduces the tractor slip by 14.83%and increases the traction efficiency by 10.28%compared with the average torquedistribution mode.Compared with the conventional traction control mode,the joint control method for traction and ballast proposed in this paper results in a 3.7%increase in traction efficiency,a 15.05%decrease in slip,and a 4.9%reduction in total drive motor energy consumption.This study will help to improve the operation quality and traction efficiency of electric tractors in complex soil conditions.

The Future Trend of E-Mobility in Terms of Battery Electric Vehicles and Their Impact on Climate Change: A Case Study Applied in Hungary

The transportation sector is responsible for 25% of the total Carbon dioxide (CO2) emissions, whereas 60.6% of this sector represents small and medium passenger cars. However, as noted by the European Union Long-term strategy, there are two ways to reduce the amount of CO2 emissions in the transportation sector. The first way is characterized by creating more efficient vehicles. In contrast, the second way is characterized by changing the fuel used. The current study addressed the second way, changing the fuel type. The study examined the potential of battery electric vehicles (BEVs) as an alternative fuel type to reduce CO2 emissions in Hungarys transportation sector. The study used secondary data retrieved from Statista and stata.com to analyze the future trends of BEVs in Hungary. The results showed that the percentage of BEVs in Hungary in 2022 was 0.4% compared to the total number of registered passenger cars, which is 3.8 million. The simple exponential smoothing (SES) time series forecast revealed that the number of BEVs is expected to reach 84,192 in 2030, indicating a percentage increase of 2.21% in the next eight years. The study suggests that increasing the number of BEVs is necessary to address the negative impact of CO2 emissions on society. The Hungarian Ministry of Innovation and Technologys strategy to reduce the cost of BEVs may increase the percentage of BEVs by 10%, resulting in a potential average reduction of 76,957,600 g/km of CO2 compared to gasoline, diesel, hybrid electric vehicles (HEVs), and plug-in hybrid vehicles (PHEVs).

Design and Analysis of Power and Transmission System of Downhole Pure Electric Command Vehicle

Electric vehicles use electric motors, which turn electrical energy into mechanical energy. As electric motors are conventionally used in all the industry, it is an established development site. It’s a mature technology with ideal power and torque curves for vehicular operation. Conventional vehicles use oil and gas as fuel or energy storage. Although they also have an excellent economic impact, the continuous use of oil and gas threatened the world’s reservation of total oil and gas. Also, they emit carbon dioxide and some toxic ingredients through the vehicle’s tailpipe, which causes the greenhouse effect and seriously impacts the environment. So, as an alternative, electric car refers to a green technology of decarbonization with zero emission of greenhouse gases through the tailpipe. So, they can remove the problem of greenhouse gas emissions and solve the world’s remaining non-renewable energy storage problem. Pure electric vehicles (PEV) can be applied in all spheres, but their special implementation can only be seen in downhole operations. They are used for low noise and less pollution in the downhole process. In this study, the basic structure of the pure electric command vehicle is studied, the main components of the command vehicle power system, namely the selection of the drive motor and the power battery, are analyzed, and the main parameters of the drive motor and the power battery are designed and calculated. The checking calculation results show that the power and transmission system developed in this paper meets the design requirements, and the design scheme is feasible and reasonable.

Effect of applied electric fields on supralinear dendritic integration of interneuron

Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron.However,it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic inputs.Considering the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations,we suppose that the applied EFs could functionally modulate interneurons’response via regulating dendritic integration.At first,we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials,which characterizes the relationship among EF-induced spatial polarizations,dendritic integration,and somatic output.By performing model-based singular perturbation analysis,it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input–output(sI/O)relationship of dendritic integration.It predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input,and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA spike.Also,the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA synapses.Furthermore,we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.

Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain

The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading market.Certificateless signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrowbased on identity cryptography.However,most certificateless signatures still suffer fromvarious security flaws.We present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature schemes.To ensure the integrity and verifiability of electricity carbon quota trading,we propose an electricity carbon quota trading scheme based on a certificateless signature and blockchain.Our scheme utilizes certificateless signatures to ensure the validity and nonrepudiation of transactions and adopts blockchain technology to achieve immutability and traceability in electricity carbon quota transactions.In addition,validating electricity carbon quota transactions does not require time-consuming bilinear pairing operations.The results of the analysis indicate that our scheme meets existential unforgeability under adaptive selective message attacks,offers conditional identity privacy protection,resists replay attacks,and demonstrates high computing and communication performance.