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。

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.

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.

Flexible and Robust Functionalized Boron Nitride/Poly(p‑Phenylene Benzobisoxazole)Nanocomposite Paper with High Thermal Conductivity and Outstanding Electrical Insulation

With the rapid development of 5G information technology,thermal conductivity/dissipation problems of highly integrated electronic devices and electrical equipment are becoming prominent.In this work,“high-temperature solid-phase&diazonium salt decomposition”method is carried out to prepare benzidine-functionalized boron nitride(m-BN).Subsequently,m-BN/poly(pphenylene benzobisoxazole)nanofiber(PNF)nanocomposite paper with nacremimetic layered structures is prepared via sol–gel film transformation approach.The obtained m-BN/PNF nanocomposite paper with 50 wt%m-BN presents excellent thermal conductivity,incredible electrical insulation,outstanding mechanical properties and thermal stability,due to the construction of extensive hydrogen bonds andπ–πinteractions between m-BN and PNF,and stable nacre-mimetic layered structures.Itsλ∥andλ_(⊥)are 9.68 and 0.84 W m^(-1)K^(-1),and the volume resistivity and breakdown strength are as high as 2.3×10^(15)Ωcm and 324.2 kV mm^(-1),respectively.Besides,it also presents extremely high tensile strength of 193.6 MPa and thermal decomposition temperature of 640°C,showing a broad application prospect in high-end thermal management fields such as electronic devices and electrical equipment.

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.

Superposition of dual electric fields in covalent organic frameworks for efficient photocatalytic hydrogen evolution

Covalent organic frameworks(COFs)are promising materials for converting solar energy into green hydrogen.However,limited charge separation and transport in COFs impede their application in the photocatalytic hydrogen evolution reaction(HER).In this study,the intrinsically tunable inter-nal bond electric field(IBEF)at the imine bonds of COFs was manipulated to cooperate with the internal molecular electric field(IMEF)induced by the donor-acceptor(D-A)structure for an effi-cient HER.The aligned orientation of IBEF and IMEF resulted in a remarkable H_(2)evolution rate of 57.3 mmol·g^(-1)·h^(-1)on TNCA,which was approximately 520 times higher than that of TCNA(0.11 mmol·g^(-1)·h^(-1))with the opposing electric field orientation.The superposition of the dual electric fields enables the IBEF to function as an accelerating field for electron transfer,kinetically facilitat-ing the migration of photogenerated electrons from D to A.Furthermore,theoretical calculations indicate that the inhomogeneous charge distribution at the C and N atoms in TNCA not only pro-vides a strong driving force for carrier transfer but also effectively hinders the return of free elec-trons to the valence band,improving the utilization of photoelectrons.This strategy of fabricating dual electric fields in COFs offers a novel approach to designing photocatalysts for clean energy synthesis.

Improved YOLOv8n Model for Detecting Helmets and License Plates on Electric Bicycles

Wearing helmetswhile riding electric bicycles can significantly reduce head injuries resulting fromtraffic accidents.To effectively monitor compliance,the utilization of target detection algorithms through traffic cameras plays a vital role in identifying helmet usage by electric bicycle riders and recognizing license plates on electric bicycles.However,manual enforcement by traffic police is time-consuming and labor-intensive.Traditional methods face challenges in accurately identifying small targets such as helmets and license plates using deep learning techniques.This paper proposes an enhanced model for detecting helmets and license plates on electric bicycles,addressing these challenges.The proposedmodel improves uponYOLOv8n by deepening the network structure,incorporating weighted connections,and introducing lightweight convolutional modules.These modifications aim to enhance the precision of small target recognition while reducing the model’s parameters,making it suitable for deployment on low-performance devices in real traffic scenarios.Experimental results demonstrate that the model achieves an mAP@0.5 of 91.8%,showing an 11.5%improvement over the baselinemodel,with a 16.2%reduction in parameters.Additionally,themodel achieves a frames per second(FPS)rate of 58,meeting the accuracy and speed requirements for detection in actual traffic scenarios.

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.

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.

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.

Oxygen-assisted zinc recovery from electric arc furnace dust using magnesium chloride

Electric arc furnace(EAF)dust is an important secondary resource containing metals,such as zinc(Zn)and iron(Fe).Recover-ing Zn from EAF dust can contribute to resource recycling and reduce environmental impacts.However,the high chemical stability of ZnFe_(2)O_(4)in EAF dust poses challenges to Zn recovery.To address this issue,a facile approach that involves oxygen-assisted chlorination using molten MgCl_(2)is proposed.This work focused on elucidating the role of O2 in the reaction between ZnFe_(2)O_(4)and molten MgCl_(2).The results demonstrate that MgCl_(2)effectively broke down the ZnFe_(2)O_(4)structure,and the high O2 atmosphere considerably promoted the sep-aration of Zn from other components in the form of ZnCl_(2).The presence of O2 facilitated the formation of MgFe_(2)O_(4),which stabilized Fe and prevented its chlorination.Furthermore,the excessive use of MgCl_(2)resulted in increased evaporation loss,and high temperatures pro-moted the rapid separation of Zn.Building on these findings,we successfully extracted ZnCl_(2)-enriched volatiles from practical EAF dust through oxygen-assisted chlorination.Under optimized conditions,this method achieved exceptional Zn chlorination percentage of over 97%within a short period,while Fe chlorination remained below 1%.The resulting volatiles contained 85wt%of ZnCl_(2),which can be further processed to produce metallic Zn.The findings offer guidance for the selective recovery of valuable metals,particularly from solid wastes such as EAF dust.

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.

Urban Electric Vehicle Charging Station Placement Optimization with Graylag Goose Optimization Voting Classifier

To reduce the negative effects that conventional modes of transportation have on the environment,researchers are working to increase the use of electric vehicles.The demand for environmentally friendly transportation may be hampered by obstacles such as a restricted range and extended rates of recharge.The establishment of urban charging infrastructure that includes both fast and ultra-fast terminals is essential to address this issue.Nevertheless,the powering of these terminals presents challenges because of the high energy requirements,whichmay influence the quality of service.Modelling the maximum hourly capacity of each station based on its geographic location is necessary to arrive at an accurate estimation of the resources required for charging infrastructure.It is vital to do an analysis of specific regional traffic patterns,such as road networks,route details,junction density,and economic zones,rather than making arbitrary conclusions about traffic patterns.When vehicle traffic is simulated using this data and other variables,it is possible to detect limits in the design of the current traffic engineering system.Initially,the binary graylag goose optimization(bGGO)algorithm is utilized for the purpose of feature selection.Subsequently,the graylag goose optimization(GGO)algorithm is utilized as a voting classifier as a decision algorithm to allocate demand to charging stations while taking into consideration the cost variable of traffic congestion.Based on the results of the analysis of variance(ANOVA),a comprehensive summary of the components that contribute to the observed variability in the dataset is provided.The results of the Wilcoxon Signed Rank Test compare the actual median accuracy values of several different algorithms,such as the voting GGO algorithm,the voting grey wolf optimization algorithm(GWO),the voting whale optimization algorithm(WOA),the voting particle swarm optimization(PSO),the voting firefly algorithm(FA),and the voting genetic algorithm(GA),to the theoretical median that would be expected that there is no difference.

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.

Electrospinning-hot pressing technique for the fabrication of thermal and electrical storage membranes and its applications

The combination of electrospinning and hot pressing,namely the electrospinning-hot pressing technique(EHPT),is an efficient and convenient method for preparing nanofibrous composite materials with good energy storage performance.The emerging composite membrane prepared by EHPT,which exhibits the advantages of large surface area,controllable morphology,and compact structure,has attracted immense attention.In this paper,the conduction mechanism of composite membranes in thermal and electrical energy storage and the performance enhancement method based on the fabrication process of EHPT are systematically discussed.Moreover,the state-of-the-art applications of composite membranes in these two fields are introduced.In particular,in the field of thermal energy storage,EHPT-prepared membranes have longitudinal and transverse nanofibers,which generate unique thermal conductivity pathways;also,these nanofibers offer enough space for the filling of functional materials.Moreover,EHPT-prepared membranes are beneficial in thermal management systems,building energy conservation,and electrical energy storage,e.g.,improving the electrochemical properties of the separators as well as their mechanical and thermal stability.The application of electrospinning-hot pressing membranes on capacitors,lithium-ion batteries(LIBs),fuel cells,sodium-ion batteries(SIBs),and hydrogen bromine flow batteries(HBFBs)still requires examination.In the future,EHPT is expected to make the field more exciting through its own technological breakthroughs or be combined with other technologies to produce intelligent materials.

Alternating current heating techniques for lithium-ion batteries in electric vehicles:Recent advances and perspectives

The significant decrease in battery performance at low temperatures is one of the critical challenges that electric vehicles(EVs)face,thereby affecting the penetration rate in cold regions.Alternating current(AC)heating has attracted widespread attention due to its low energy consumption and uniform heating advantages.This paper introduces the recent advances in AC heating from the perspective of practical EV applications.First,the performance degradation of EVs in low-temperature environments is introduced briefly.The concept of AC heating and its research methods are provided.Then,the effects of various AC heating methods on battery heating performance are reviewed.Based on existing studies,the main factors that affect AC heating performance are analyzed.Moreover,various heating circuits based on EVs are categorized,and their cost,size,complexity,efficiency,reliability,and heating rate are elaborated and compared.The evolution of AC heaters is presented,and the heaters used in brand vehicles are sorted out.Finally,the perspectives and challenges of AC heating are discussed.This paper can guide the selection of heater implementation methods and the optimization of heating effects for future EV applications.

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.

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.

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).