Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobje...To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.展开更多
Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–di...Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–discharge cycles and fixed-form physical constraints,which limit adaptability to different chemistries and real-world conditions.To address these issues,this study proposes an approach that extracts features from segmented state of charge(SOC)intervals and integrates them into an enhanced physics-informed neural network(PINN).Specifically,voltage data within the 25%–75%SOC range during charging are used to derive statistical,time–frequency,and mechanism-based features that capture degradation trends.A hybrid PINN-Lasso-Transformer-BiLSTM architecture is developed,where Lasso regression enables sparse feature selection,and a nonlinear empirical degradation model is embedded as a learnable physical term within a dynamically scaled composite loss.This design adaptively balances data-driven accuracy with physical consistency,thereby enhancing estimation precision,robustness,and generalization.The results show that the proposed method outperforms conventional neural networks across four battery chemistries,achieving root mean square error and mean absolute error below 1%.Notably,features from partial charging segments exhibit higher robustness than those from full cycles.Furthermore,the model maintains strong performance under high temperatures and demonstrates excellent generalization capacity in transfer learning across chemistries,temperatures,and C-rates.This work establishes a scalable and interpretable solution for accurate SOH estimation under diverse practical operating conditions.展开更多
With the advances of our society,the application scope of energy storage technologies has expanded dramatically,spanning diverse scenarios.These include electric air vehicles(EAVs)that require instantaneous high-power...With the advances of our society,the application scope of energy storage technologies has expanded dramatically,spanning diverse scenarios.These include electric air vehicles(EAVs)that require instantaneous high-power bursts for takeoff and maneuvering,portable medical devices demanding rapid rechargeability,and grid-connected energy storage systems that must swiftly respond to load fluctuations[1].展开更多
To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate elect...To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate electrolyte to form a dual-salt system.The optimization mechanism enhancing the fast-charging capability of LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)(NCM523)cathode is systematically explored.Molecular dynamics simulations and electrochemical characterization demonstrate the reconstruction of Li+solvation structures,expanding the voltage window and reducting Li^(+)desolvation barriers.In addition,the incorporation of LiDFOB induces the generation of a LiF/Li_(x)BO_(y)F_(z)-enriched cathode-electrolyte interphase,which effectively suppresses the dissolution of transition metals.In situ impedance measurements reveal the accelerated interfacial charge transfer kinetics.As expected,the NCM523 cathode achieves an 82%state-of-charge(SOC)in 12 min at 5 C(25°C)with 87%capacity retention after 100 cycles,and exhibits a 65%higher discharge capacity at 1 C than the baseline at−20°C.The 1 Ah pouch cells based on LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)cathodes,graphite anodes,and 0.5 wt%LiDFOB-modified electrolyte demonstrate fast-charging capabilities:charging 97%of the pouch cell capacity within 30 min(2 C)and 80%within 15 min(4 C)at 25°C.This study offers a practical electrolyte design strategy that enhances the fast-charging performance of lithium-ion batteries(LIBs)over a wide temperature range(from−20 to 25°C).展开更多
Zn-based thermal charging devices,utilizing the synergistic effect of ion thermoextraction and thermodiffusion,are able to efficiently convert thermal energy into electrical energy and storage in the devices,making th...Zn-based thermal charging devices,utilizing the synergistic effect of ion thermoextraction and thermodiffusion,are able to efficiently convert thermal energy into electrical energy and storage in the devices,making them a highly promising technology for low-grade heat recovery and utilization.However,the low output power density and energy conversion efficiency resulted by the slow diffusion kinetics of Zn^(2+)hinder their development.Herein,we present a highperformance thermal charging cell design using Zn^(2+)/NH_(4)^(+)hybrid ion electrolyte,which not only maintains the high output voltage of the Zn-based thermoelectric system,but also significantly enhances the output power density due to the fast diffusion kinetics of NH_(4)^(+).Based on this strategy,the thermal charging cell displays a high thermopower of 12.5 mV K^(-1)and an excellent normalized power density of 19.6 mW m^(-2)K^(-2)at a temperature difference of 35 K.The Carnot-relative efficiency is as high as 12.74%.Moreover,it can operate continuously for over 72 h when the temperature difference persists,achieving a balance between thermoelectric conversion and output.This work provides a simple and effective strategy for the design of high-performance thermal charging cells for low-grade heat conversion and utilization.展开更多
This paper introduces a method for modeling the entire aggregated electric vehicle(EV)charging process and analyzing its dispatchable capabilities.The methodology involves developing a model for aggregated EV charging...This paper introduces a method for modeling the entire aggregated electric vehicle(EV)charging process and analyzing its dispatchable capabilities.The methodology involves developing a model for aggregated EV charging at the charging station level,estimating its physical dispatchable capability,determining its economic dispatchable capability under economic incentives,modeling its participation in the grid,and investigating the effects of different scenarios and EV penetration on the aggregated load dispatch and dispatchable capability.The results indicate that using economic dispatchable capability reduces charging prices by 9.7%compared to physical dispatchable capability and 9.3%compared to disorderly charging.Additionally,the peak-to-valley difference is reduced by 64.6%when applying economic dispatchable capability with 20%EV penetration and residential base load,compared to disorderly charging.展开更多
The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challe...The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.展开更多
In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including i...In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including increased peak power demand and the need for substantial upgrades to power infrastruc-ture.Here,we introduce an integrated model to assess fast and ultrafast charging impacts for represen-tative charging stations in China,combining real-world charging patterns and detailed station optimization models.We find that larger stations with 12 or more chargers experience modest peak power increases of less than 30%when fast-charging power is doubled,primarily because shorter charg-ing sessions are less likely to overlap.For more typical stations(e.g.,8-9 chargers and 120 kW·charger^(−1)),upgrading chargers to 350-550 kW while allowing managed dynamic waiting strategies(of∼1 minute)can reduce overall charging times to∼9 minutes.At stations,deploying battery storage and/or expanding transformers can help manage future increases in station loads,yet the primary device cost of the former is∼4 times higher than that of the latter.Our results offer insights for charging infrastructure planning,EV-grid interactions,and associated policymaking.展开更多
Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles,this paper proposes a coordinated ...Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles,this paper proposes a coordinated charging scheduling strategy for multiple types of electric vehicles based on the degree of urgency of vehicle use.First,considering the range loss characteristics,dynamic time-sharing tariff mechanism,and user incentive policy in the lowtemperature environment of northern winter,a differentiated charging model is constructed for four types of vehicles:family cars,official cars,buses,and cabs.Then,we innovatively introduce the urgency parameter of charging demand for multiple types of vehicles and dynamically divide the emergency and non-emergency charging modes according to the difference between the regular charging capacity and the user’s minimum power demand.When the conventional charging capacity is less than the minimum power demand of the vehicle within the specified time,it is the emergency vehicle demand,and this type of vehicle is immediately charged in fast charging mode after connecting to the grid.On the contrary,it is a non-emergency demand,and the vehicle is connected to the grid to choose the appropriate time to charge in conventional charging mode.Finally,by optimizing the objective function to minimize the peakto-valley difference between the grid and the vehicle owner’s charging cost,and designing the charging continuity constraints to avoid battery damage,it ensures that the vehicle is efficiently dispatched under the premise of meeting the minimum power demand.Simulation results show that the proposed charging strategy can reduce the charging cost of vehicle owners by 26.33%,reduce the peak-to-valley difference rate of the grid by 29.8%,and significantly alleviate the congestion problem during peak load hours,compared with the disordered charging mode,while ensuring that the electric vehicles are not overcharged and meet the electricity demand of vehicle owners.This paper solves the problems of the existing research on the singularity of vehicle models and the lack of environmental adaptability and provides both economic and practical solutions for the cooperative optimization of electric vehicles and power grids in multiple scenarios.展开更多
High-power direct current fast charging(DC-HPC),particularly for megawatt-level charging currents(≥1000 A),is expected to significantly reduce charging time and improve electric vehicle durability,despite the risk of...High-power direct current fast charging(DC-HPC),particularly for megawatt-level charging currents(≥1000 A),is expected to significantly reduce charging time and improve electric vehicle durability,despite the risk of instantaneous thermal shocks.Conventional cooling methods,which separately transmit current and heat,struggle to achieve both flexible maneuverability and high-efficiency cooling.In this study,we present a synergetic cooling and transmission strategy using a gallium-based liquid metal flexible charging connector(LMFCC),which efficiently dissipates ultra-high heat flux while simultaneously carrying superhigh current.The LMFCC exhibits exceptional flexible operability(bending radius of 2 cm)and transmission stability even under significant deformation owing to the excellent liquidity and conductivity of liquid metal(LM).These properties are markedly better than those of solid metal connector.A compact induction electromagnet-driven method is optimized to significantly increase the LM flow rate and the active cooling capacity,resulting in sudden low temperature(<16℃at 1000 A).This synergetic cooling and charging strategy are expected to enable ultrahigh-heat-flux thermal management and accelerate development of the electric vehicle industry.展开更多
The properties of electrolytes are critical for fast-charging and stable-cycling applications in lithium metal batteries(LMBs).However,the slow kinetics of Li^(+)transport and desolvation in commercial carbonate elect...The properties of electrolytes are critical for fast-charging and stable-cycling applications in lithium metal batteries(LMBs).However,the slow kinetics of Li^(+)transport and desolvation in commercial carbonate electrolytes,cou pled with the formation of unstable solid electrolyte interphases(SEI),exacerbate the degradation of LMB performance at high current densities.Herein,we propose a versatile electrolyte design strategy that incorporates cyclohexyl methyl ether(CME)as a co-solvent to reshape the Li^(+)solvation environment by the steric-hindrance effect of bulky molecules and their competitive coordination with other solvent molecules.Simulation calculations and spectral analysis demonstrate that the addition of CME molecules reduces the involvement of other solvent molecules in the Li solvation sheath and promotes the formation of Li^(+)-PF_(6)^(-)coordination,thereby accelerating Li^(+)transport kinetics.Additionally,this electrolyte composition improves Li^(+)desolvation kinetics and fosters the formation of inorganic-rich SEI,ensuring cycle stability under fast charging.Consequently,the Li‖LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)battery with the modified electrolyte retains 82% of its initial capacity after 463 cycles at 1 C.Even under the extreme fast-charging condition of 5 C,the battery can maintain 80% capacity retention after 173 cycles.This work provides a promising approach for the development of highperformance LMBs by modulating solvation environment of electrolytes.展开更多
The origin of tight reservoirs in the Yanchang Formation of the Ordos Basin and their relationship with hydrocarbon charging remain unclear.Based on petrological observations,physical property analysis,fluid inclusion...The origin of tight reservoirs in the Yanchang Formation of the Ordos Basin and their relationship with hydrocarbon charging remain unclear.Based on petrological observations,physical property analysis,fluid inclusion system analysis and in situ U-Pb dating,the sequence of tight sandstone reservoir densification and oil charging was determined.Through petrological observations,fluid inclusion analysis and physical property analysis,it is concluded that compaction and cementation are the primary causes of reservoir densification.When the content of calcite cement is less than or equal to 7%,compaction dominates densification;otherwise,cementation becomes more significant.However,determining the exact timing of compaction densification proved challenging.Microscopic observations revealed that oil charging likely occurred either before or during the densification of the reservoir.According to in situ U-Pb dating and the porosity evolution curve,cementation densification occurred between 167.0±20.0 Ma and 151.8 Ma.Temperature measurements of the aqueous inclusions indicate that oil charging occurred between 125.0 and 96.0 Ma,suggesting that densification preceded oil charging.This study provides valuable insights for the future exploration of tight oil reservoirs in the Ordos Basin.展开更多
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time perfor...Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.展开更多
Sodium-ion batteries have emerged as competitive substitutes for low-temperature applications due to severe capacity loss and safety concerns of lithium-ion batteries at−20°C or lower.However,the key capability o...Sodium-ion batteries have emerged as competitive substitutes for low-temperature applications due to severe capacity loss and safety concerns of lithium-ion batteries at−20°C or lower.However,the key capability of ultrafast charging at ultralow temperature for SIBs is rarely reported.Herein,a hybrid of Bi nanoparticles embedded in carbon nanorods is demonstrated as an ideal material to address this issue,which is synthesized via a high temperature shock method.Such a hybrid shows an unprecedented rate performance(237.9 mAh g^(−1) at 2 A g^(−1))at−60℃,outperforming all reported SIB anode materials.Coupled with a Na_(3)V_(2)(PO_(4))_(3)cathode,the energy density of the full cell can reach to 181.9 Wh kg^(−1) at−40°C.Based on this work,a novel strategy of high-rate activation is proposed to enhance performances of Bi-based materials in cryogenic conditions by creating new active sites for interfacial reaction under large current.展开更多
Lithium-ion batteries(LIBs)are an electrochemical energy storage technology that has been widely used for portable electrical devices,electric vehicles,and grid storage,etc.To satisfy the demand for user convenience e...Lithium-ion batteries(LIBs)are an electrochemical energy storage technology that has been widely used for portable electrical devices,electric vehicles,and grid storage,etc.To satisfy the demand for user convenience especially for electric vehicles,the development of a fast-charging technology for LIBs has become a critical focus.In commercial LIBs,the slow kinetics of Li+intercalation into the graphite anode from the electrolyte solution is known as the main restriction for fast-charging.We summarize the recent advances in obtaining fast-charging graphite-based anodes,mainly involving modifications of the electrolyte solution and graphite anode.Specifically,strategies for increasing the ionic conductivity and regulating the Li+solvation/desolvation state in the electrolyte solution,as well as optimizing the fabrication and the intrinsic activity of graphite-based anodes are discussed in detail.This review considers practical ways to obtain fast Li+intercalation kinetics into a graphite anode from the electrolyte as well as analysing progress in the commercialization of fast-charging LIBs.展开更多
Developing fast-charging lithium-ion batteries(LIBs)that feature high energy density is critical for the scalable application of electric vehicles.Iron vanadate(FVO)holds great potential as anode material in fast-char...Developing fast-charging lithium-ion batteries(LIBs)that feature high energy density is critical for the scalable application of electric vehicles.Iron vanadate(FVO)holds great potential as anode material in fast-charging LIBs because of its high theoretical specific capacity and the high natural abundance of its constituents.However,the capacity of FVO rapidly decays due to its low electrical conductivity.Herein,uniform FVO nanoparticles are grown in situ on ordered mesoporous carbon(CMK-3)support,forming a highly electrically conductive porous network,FVO/CMK-3.The structure of CMK-3 helps prevent agglomeration of FVO particles.The electrically conductive nature of CMK-3 can further enhance the electrical conductivity of FVO/CMK-3 and buffer the volume expansion of FVO particles during cycling processes.As a result,the FVO/CMK-3 displays excellent fast-charging performance of 364.6 mAh·g^(-1)capacity for 2500 cycles at 10 A·g^(-1)(with an ultralow average capacity loss per cycle of 0.003%)through a pseudocapacitive-dominant process.Moreover,the LiCoO_(2)//FVO/CMK-3 full cell achieves a high capacity of 100.2 mAh·g^(-1)and a high capacity retention(96.2%)after 200 cycles.The superior electrochemical performance demonstrates that FVO/CMK-3 is an ideal anode material candidate for fast-charging,stable LIBs with high energy density.展开更多
In this article,a hybrid energy storage system powered by renewable energy sources is suggested,which is connected to a grid-tied electric vehicle charging bay(EVCB)in Sarawak and is examined for its techno-economic e...In this article,a hybrid energy storage system powered by renewable energy sources is suggested,which is connected to a grid-tied electric vehicle charging bay(EVCB)in Sarawak and is examined for its techno-economic effects.With a focus on three renewable energy sources,namely hydrokinetic power,solar power,and hydrogen fuel cells,the study seeks to minimize reliance on the electrical grid while meeting the growing demand from the growing electric vehicle(EV)infrastructure.A hybrid renewable energy storage system that combines solar power,hydrogen fuel cells,hydrokinetic power,and the grid was simulated and analyzed.The system design leverages Kuching,Sarawak's unique geographical and renewable source profile,including abundant hydro and solar potential as well as supportive regional energy policies,to optimize economic and environmental performance.The findings showed that the technoeconomic evaluation of the hydrogen storage-integrated EVCB system in Kuching,Sarawak,demonstrates promising performance under current market conditions.The system successfully meets charging demand while generating an annual profit of approximately$5l,104.30 through excess energy sales to the grid.Hydrokinetic power dominates generation,contributing 81.4%of the total output,with the hydrogen fuel cell adding a modest 2.84%.The system achieves a cost of electricity of$0.0617/kWh and a Levelized Cost of Hydrogen of approximately$7.33/kg,confirming its economic feasibility.With a total investment of approximately$2.43 million,the hydrogen storage subsystem represents the largest cost share at 55.2%($1.34 million).A high renewable fraction of 97.2%enhances the system's sustainability,which is further supported by significant annual emissions reductions of approximately 102,209 kg of carbon dioxide,8.48 kg of sulfur dioxide,and 43.1 kg of nitrogen oxides.These results demonstrate that the proposed hybrid EVCB exhibits excellent economic and environmental sustainability,making it a viable option for Sarawak's sustainable electric vehicle charging infrastructure.展开更多
Carbonate electrolytes have been widely applied in sodium-ion batteries(SIBs);however,the strong Na^(+) -solvent coordination induces sluggish desolvation kinetics and severe parasitic reactions at hard carbon(HC)anod...Carbonate electrolytes have been widely applied in sodium-ion batteries(SIBs);however,the strong Na^(+) -solvent coordination induces sluggish desolvation kinetics and severe parasitic reactions at hard carbon(HC)anodes.Herein,tris(2,2,2-trifluoroethyl)phosphite(TFEPi)is introduced into a propylene carbonate/diethyl carbonate electrolyte(PDT,PC/DEC/TFEPi in a volume ratio of 5:4:1)to enhance the coordination of Na^(+)-PF_(6)^(-)for fast-charging SIBs.The electron-withdrawing CF_(3)groups in TFEPi reduce the electrondonating ability of carbonate solvents to weaken Na^(+) -solvent interactions and enrich PF_(6)^(-)in the first solvation sheath.This lowers Na^(+) desolvation energy from 68.1 kJ mol^(-1)in PC/DEC with a volume ratio of 5:5 to 54.1 kJ mol^(-1)in PDT.The anion-dominated solvation structure of PDT promotes its preferential adsorption on the HC anode,forming a NaF/Na_(3)PO_(4)-rich solid electrolyte interphase with enhanced Na^(+) transport and mechanical stability.Moreover,the phosphite group of TFEPi scavenges H/OH radicals to suppress combustion chain reactions,endowing PDT with exceptional flame retardancy with selfextinguishing time<1 s g^(-1).It is demonstrated that Na//HC half cell retains 80.6%and 61.7%of HC capacity at 200 and 500 mA g^(-1),respectively,and HC//Na_(3)V_(2)(PO_(4))_(2)F_(3)(NVPF)full cell shows 80%charge capacity of NVPF within 5 min at 1000 mA g^(-1)at 25℃ and maintains stable operation from -20 to 60℃.This work provides new insights into electrolyte solvation engineering for high chargeability and safety of SIBs.展开更多
The global public HPC(high-power charging)network for EVs(electric vehicles)is rapidly expanding.This growth is crucial for supporting the increasing adoption of EVs but highlights the industry’s early stage.Regional...The global public HPC(high-power charging)network for EVs(electric vehicles)is rapidly expanding.This growth is crucial for supporting the increasing adoption of EVs but highlights the industry’s early stage.Regional maturity varies,with China leading due to strong government support,followed by Europe and the United States.A significant challenge is the lack of industry standards,causing inconsistencies in charger types and payment systems.Efforts are underway,to ensure interoperability and reliability.Interoperability is crucial for the success of EV HPC infrastructure,ensuring seamless integration among charge points,management systems,and service providers.Despite the use of protocols like the OCPP(Open Charge Point Protocol),variations in implementation create complexities.Ensuring uniform standards across the ecosystem is essential for reliability and efficiency.Vendor-specific error codes,which are more detailed than standardized codes,are vital for diagnosing issues but lack standardization,adding complexity.Addressing these challenges is key to supporting widespread EV adoption and enhancing user experience.To provide a compelling driver value proposition,EV charging services must be reliable and seamless.The operations and maintenance of the HPC network must be cost-effective and leverage the intelligence of the integrated ecosystem.The technical complexity of managing high-power DC charging,combined with diverse authentication and payment systems,results in numerous potential issues.Moving from reactive to predictive maintenance is essential for undisrupted operations and a smooth driver experience.Shell’s Intelligent Operations Technology Strategy incorporates GenAI elements in its advanced analytics and operational performance management tools.By ingesting big data from multiple sources across the EV ecosystem,Shell engineers can perform detailed pattern recognition and targeted troubleshooting.Monitoring,configurable alerting,and remote fixing based on auto-healing and targeted auto-allocation enhance charger availability and reduce downtime.This automation has evolved Shell’s maintenance and operations strategy from reactive to predictive,improving overall charger performance and user satisfaction.Key achievements include transitioning to prescriptive and preventive asset management approaches,significantly improving uptime and charging experience,and increasing commercial value through cost reduction and enhanced revenue.Future challenges include evolving OCPP,integrating data from non-OCPP systems,and ensuring interoperability across diverse systems.Standardization and cross-collaboration within the industry are essential for smooth interoperability,higher uptime,and increased CSR(charging success rate).Technological innovations will further shape the industry,promoting stabilization and efficiency as it matures.展开更多
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
基金Supported by State Grid Corporation of China Science and Technology Project:Research on Key Technologies for Intelligent Carbon Metrology in Vehicle-to-Grid Interaction(Project Number:B3018524000Q).
文摘To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.
基金supported by the Shanghai Pilot Program for Basic Research(22T01400100-18)the National Natural Science Foundation of China(22278127 and 12447149)+1 种基金the Fundamental Research Funds for the Central Universities(2022ZFJH004)the Postdoctoral Fellowship Program of CPSF(GZB20250159).
文摘Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–discharge cycles and fixed-form physical constraints,which limit adaptability to different chemistries and real-world conditions.To address these issues,this study proposes an approach that extracts features from segmented state of charge(SOC)intervals and integrates them into an enhanced physics-informed neural network(PINN).Specifically,voltage data within the 25%–75%SOC range during charging are used to derive statistical,time–frequency,and mechanism-based features that capture degradation trends.A hybrid PINN-Lasso-Transformer-BiLSTM architecture is developed,where Lasso regression enables sparse feature selection,and a nonlinear empirical degradation model is embedded as a learnable physical term within a dynamically scaled composite loss.This design adaptively balances data-driven accuracy with physical consistency,thereby enhancing estimation precision,robustness,and generalization.The results show that the proposed method outperforms conventional neural networks across four battery chemistries,achieving root mean square error and mean absolute error below 1%.Notably,features from partial charging segments exhibit higher robustness than those from full cycles.Furthermore,the model maintains strong performance under high temperatures and demonstrates excellent generalization capacity in transfer learning across chemistries,temperatures,and C-rates.This work establishes a scalable and interpretable solution for accurate SOH estimation under diverse practical operating conditions.
文摘With the advances of our society,the application scope of energy storage technologies has expanded dramatically,spanning diverse scenarios.These include electric air vehicles(EAVs)that require instantaneous high-power bursts for takeoff and maneuvering,portable medical devices demanding rapid rechargeability,and grid-connected energy storage systems that must swiftly respond to load fluctuations[1].
基金financially supported by the National Natural Science Foundation of China (Grant No. 52372191)the National Natural Science Foundation of China (Grant No. 22271106)+2 种基金the National Science Foundation of China (Grant Nos. 52073286 (C.-Z.L.), 22275185 (C.-Z.L.))the Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(2021ZZ115 (C.-Z.L.)the XMIREM Autonomously Deployment Project (2023GG01 (C.-Z.L.))
文摘To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate electrolyte to form a dual-salt system.The optimization mechanism enhancing the fast-charging capability of LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)(NCM523)cathode is systematically explored.Molecular dynamics simulations and electrochemical characterization demonstrate the reconstruction of Li+solvation structures,expanding the voltage window and reducting Li^(+)desolvation barriers.In addition,the incorporation of LiDFOB induces the generation of a LiF/Li_(x)BO_(y)F_(z)-enriched cathode-electrolyte interphase,which effectively suppresses the dissolution of transition metals.In situ impedance measurements reveal the accelerated interfacial charge transfer kinetics.As expected,the NCM523 cathode achieves an 82%state-of-charge(SOC)in 12 min at 5 C(25°C)with 87%capacity retention after 100 cycles,and exhibits a 65%higher discharge capacity at 1 C than the baseline at−20°C.The 1 Ah pouch cells based on LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)cathodes,graphite anodes,and 0.5 wt%LiDFOB-modified electrolyte demonstrate fast-charging capabilities:charging 97%of the pouch cell capacity within 30 min(2 C)and 80%within 15 min(4 C)at 25°C.This study offers a practical electrolyte design strategy that enhances the fast-charging performance of lithium-ion batteries(LIBs)over a wide temperature range(from−20 to 25°C).
基金supported by the Leading Edge Technology of Jiangsu Province(BK20222009-X.Z.,BK20202008-X.Z.)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)National Undergraduate Innovation Training Program of NUAA(202410287179Y).
文摘Zn-based thermal charging devices,utilizing the synergistic effect of ion thermoextraction and thermodiffusion,are able to efficiently convert thermal energy into electrical energy and storage in the devices,making them a highly promising technology for low-grade heat recovery and utilization.However,the low output power density and energy conversion efficiency resulted by the slow diffusion kinetics of Zn^(2+)hinder their development.Herein,we present a highperformance thermal charging cell design using Zn^(2+)/NH_(4)^(+)hybrid ion electrolyte,which not only maintains the high output voltage of the Zn-based thermoelectric system,but also significantly enhances the output power density due to the fast diffusion kinetics of NH_(4)^(+).Based on this strategy,the thermal charging cell displays a high thermopower of 12.5 mV K^(-1)and an excellent normalized power density of 19.6 mW m^(-2)K^(-2)at a temperature difference of 35 K.The Carnot-relative efficiency is as high as 12.74%.Moreover,it can operate continuously for over 72 h when the temperature difference persists,achieving a balance between thermoelectric conversion and output.This work provides a simple and effective strategy for the design of high-performance thermal charging cells for low-grade heat conversion and utilization.
基金State Grid Henan Power Company Science and Technology Project‘Key Technology and Demonstration Application of Multi-Domain Electric Vehicle Aggregated Charging Load Dispatch’(5217L0240003).
文摘This paper introduces a method for modeling the entire aggregated electric vehicle(EV)charging process and analyzing its dispatchable capabilities.The methodology involves developing a model for aggregated EV charging at the charging station level,estimating its physical dispatchable capability,determining its economic dispatchable capability under economic incentives,modeling its participation in the grid,and investigating the effects of different scenarios and EV penetration on the aggregated load dispatch and dispatchable capability.The results indicate that using economic dispatchable capability reduces charging prices by 9.7%compared to physical dispatchable capability and 9.3%compared to disorderly charging.Additionally,the peak-to-valley difference is reduced by 64.6%when applying economic dispatchable capability with 20%EV penetration and residential base load,compared to disorderly charging.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.
基金the support of the National Natural Science Foundation of China(72325006,72488101,and 72293601)the Sze Family Foundationthe Climate Imperative Foundation(#2024-001465)
文摘In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including increased peak power demand and the need for substantial upgrades to power infrastruc-ture.Here,we introduce an integrated model to assess fast and ultrafast charging impacts for represen-tative charging stations in China,combining real-world charging patterns and detailed station optimization models.We find that larger stations with 12 or more chargers experience modest peak power increases of less than 30%when fast-charging power is doubled,primarily because shorter charg-ing sessions are less likely to overlap.For more typical stations(e.g.,8-9 chargers and 120 kW·charger^(−1)),upgrading chargers to 350-550 kW while allowing managed dynamic waiting strategies(of∼1 minute)can reduce overall charging times to∼9 minutes.At stations,deploying battery storage and/or expanding transformers can help manage future increases in station loads,yet the primary device cost of the former is∼4 times higher than that of the latter.Our results offer insights for charging infrastructure planning,EV-grid interactions,and associated policymaking.
基金funded by Science and Technology Project of SGCC(SGJLCC00KJJS2203595).
文摘Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles,this paper proposes a coordinated charging scheduling strategy for multiple types of electric vehicles based on the degree of urgency of vehicle use.First,considering the range loss characteristics,dynamic time-sharing tariff mechanism,and user incentive policy in the lowtemperature environment of northern winter,a differentiated charging model is constructed for four types of vehicles:family cars,official cars,buses,and cabs.Then,we innovatively introduce the urgency parameter of charging demand for multiple types of vehicles and dynamically divide the emergency and non-emergency charging modes according to the difference between the regular charging capacity and the user’s minimum power demand.When the conventional charging capacity is less than the minimum power demand of the vehicle within the specified time,it is the emergency vehicle demand,and this type of vehicle is immediately charged in fast charging mode after connecting to the grid.On the contrary,it is a non-emergency demand,and the vehicle is connected to the grid to choose the appropriate time to charge in conventional charging mode.Finally,by optimizing the objective function to minimize the peakto-valley difference between the grid and the vehicle owner’s charging cost,and designing the charging continuity constraints to avoid battery damage,it ensures that the vehicle is efficiently dispatched under the premise of meeting the minimum power demand.Simulation results show that the proposed charging strategy can reduce the charging cost of vehicle owners by 26.33%,reduce the peak-to-valley difference rate of the grid by 29.8%,and significantly alleviate the congestion problem during peak load hours,compared with the disordered charging mode,while ensuring that the electric vehicles are not overcharged and meet the electricity demand of vehicle owners.This paper solves the problems of the existing research on the singularity of vehicle models and the lack of environmental adaptability and provides both economic and practical solutions for the cooperative optimization of electric vehicles and power grids in multiple scenarios.
基金the National Natural Science Foundation of China(NSFC)(52076213)the 2115 Talent Development Program of China Agricultural University for the financial coverage of this work。
文摘High-power direct current fast charging(DC-HPC),particularly for megawatt-level charging currents(≥1000 A),is expected to significantly reduce charging time and improve electric vehicle durability,despite the risk of instantaneous thermal shocks.Conventional cooling methods,which separately transmit current and heat,struggle to achieve both flexible maneuverability and high-efficiency cooling.In this study,we present a synergetic cooling and transmission strategy using a gallium-based liquid metal flexible charging connector(LMFCC),which efficiently dissipates ultra-high heat flux while simultaneously carrying superhigh current.The LMFCC exhibits exceptional flexible operability(bending radius of 2 cm)and transmission stability even under significant deformation owing to the excellent liquidity and conductivity of liquid metal(LM).These properties are markedly better than those of solid metal connector.A compact induction electromagnet-driven method is optimized to significantly increase the LM flow rate and the active cooling capacity,resulting in sudden low temperature(<16℃at 1000 A).This synergetic cooling and charging strategy are expected to enable ultrahigh-heat-flux thermal management and accelerate development of the electric vehicle industry.
基金supported by the Lithium Resources and Lithium Materials Key Laboratory of Sichuan Province(LRMKF202405)the National Natural Science Foundation of China(52402226)+3 种基金the Natural Science Foundation of Sichuan Province(2024NSFSC1016)the Scientific Research Startup Foundation of Chengdu University of Technology(10912-KYQD2023-10240)the opening funding from Key Laboratory of Engineering Dielectrics and Its Application(Harbin University of Science and Technology)(KFM202507,Ministry of Education)the funding provided by the Alexander von Humboldt Foundation。
文摘The properties of electrolytes are critical for fast-charging and stable-cycling applications in lithium metal batteries(LMBs).However,the slow kinetics of Li^(+)transport and desolvation in commercial carbonate electrolytes,cou pled with the formation of unstable solid electrolyte interphases(SEI),exacerbate the degradation of LMB performance at high current densities.Herein,we propose a versatile electrolyte design strategy that incorporates cyclohexyl methyl ether(CME)as a co-solvent to reshape the Li^(+)solvation environment by the steric-hindrance effect of bulky molecules and their competitive coordination with other solvent molecules.Simulation calculations and spectral analysis demonstrate that the addition of CME molecules reduces the involvement of other solvent molecules in the Li solvation sheath and promotes the formation of Li^(+)-PF_(6)^(-)coordination,thereby accelerating Li^(+)transport kinetics.Additionally,this electrolyte composition improves Li^(+)desolvation kinetics and fosters the formation of inorganic-rich SEI,ensuring cycle stability under fast charging.Consequently,the Li‖LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)battery with the modified electrolyte retains 82% of its initial capacity after 463 cycles at 1 C.Even under the extreme fast-charging condition of 5 C,the battery can maintain 80% capacity retention after 173 cycles.This work provides a promising approach for the development of highperformance LMBs by modulating solvation environment of electrolytes.
基金supported by the project of the Exploration Department of the Huabei Oilfield Company of Sinopec(No.34550008-20-ZC0609-0031).
文摘The origin of tight reservoirs in the Yanchang Formation of the Ordos Basin and their relationship with hydrocarbon charging remain unclear.Based on petrological observations,physical property analysis,fluid inclusion system analysis and in situ U-Pb dating,the sequence of tight sandstone reservoir densification and oil charging was determined.Through petrological observations,fluid inclusion analysis and physical property analysis,it is concluded that compaction and cementation are the primary causes of reservoir densification.When the content of calcite cement is less than or equal to 7%,compaction dominates densification;otherwise,cementation becomes more significant.However,determining the exact timing of compaction densification proved challenging.Microscopic observations revealed that oil charging likely occurred either before or during the densification of the reservoir.According to in situ U-Pb dating and the porosity evolution curve,cementation densification occurred between 167.0±20.0 Ma and 151.8 Ma.Temperature measurements of the aqueous inclusions indicate that oil charging occurred between 125.0 and 96.0 Ma,suggesting that densification preceded oil charging.This study provides valuable insights for the future exploration of tight oil reservoirs in the Ordos Basin.
基金supported by the National Key Research and Development Project of China(No.2023YFB3709605)the National Natural Science Foundation of China(No.62073193)the National College Student Innovation Training Program(No.202310422122)。
文摘Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
基金supported from Science and Technology Development Program of Jilin Province(Nos.20240101128JC,20230402058GH)National Natural Science Foundation of China(No.52130101).
文摘Sodium-ion batteries have emerged as competitive substitutes for low-temperature applications due to severe capacity loss and safety concerns of lithium-ion batteries at−20°C or lower.However,the key capability of ultrafast charging at ultralow temperature for SIBs is rarely reported.Herein,a hybrid of Bi nanoparticles embedded in carbon nanorods is demonstrated as an ideal material to address this issue,which is synthesized via a high temperature shock method.Such a hybrid shows an unprecedented rate performance(237.9 mAh g^(−1) at 2 A g^(−1))at−60℃,outperforming all reported SIB anode materials.Coupled with a Na_(3)V_(2)(PO_(4))_(3)cathode,the energy density of the full cell can reach to 181.9 Wh kg^(−1) at−40°C.Based on this work,a novel strategy of high-rate activation is proposed to enhance performances of Bi-based materials in cryogenic conditions by creating new active sites for interfacial reaction under large current.
文摘Lithium-ion batteries(LIBs)are an electrochemical energy storage technology that has been widely used for portable electrical devices,electric vehicles,and grid storage,etc.To satisfy the demand for user convenience especially for electric vehicles,the development of a fast-charging technology for LIBs has become a critical focus.In commercial LIBs,the slow kinetics of Li+intercalation into the graphite anode from the electrolyte solution is known as the main restriction for fast-charging.We summarize the recent advances in obtaining fast-charging graphite-based anodes,mainly involving modifications of the electrolyte solution and graphite anode.Specifically,strategies for increasing the ionic conductivity and regulating the Li+solvation/desolvation state in the electrolyte solution,as well as optimizing the fabrication and the intrinsic activity of graphite-based anodes are discussed in detail.This review considers practical ways to obtain fast Li+intercalation kinetics into a graphite anode from the electrolyte as well as analysing progress in the commercialization of fast-charging LIBs.
基金supported by the National Natural Science Foundation of China(No.52002170)the Central Guidance Fund Project for Local Scientific and Technological Development in Qinghai Province(No.2024ZY013)+1 种基金the Foundation of Key Laboratory of Flexible Electronics of Zhejiang Province(No.2023FE011)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX24_1635).
文摘Developing fast-charging lithium-ion batteries(LIBs)that feature high energy density is critical for the scalable application of electric vehicles.Iron vanadate(FVO)holds great potential as anode material in fast-charging LIBs because of its high theoretical specific capacity and the high natural abundance of its constituents.However,the capacity of FVO rapidly decays due to its low electrical conductivity.Herein,uniform FVO nanoparticles are grown in situ on ordered mesoporous carbon(CMK-3)support,forming a highly electrically conductive porous network,FVO/CMK-3.The structure of CMK-3 helps prevent agglomeration of FVO particles.The electrically conductive nature of CMK-3 can further enhance the electrical conductivity of FVO/CMK-3 and buffer the volume expansion of FVO particles during cycling processes.As a result,the FVO/CMK-3 displays excellent fast-charging performance of 364.6 mAh·g^(-1)capacity for 2500 cycles at 10 A·g^(-1)(with an ultralow average capacity loss per cycle of 0.003%)through a pseudocapacitive-dominant process.Moreover,the LiCoO_(2)//FVO/CMK-3 full cell achieves a high capacity of 100.2 mAh·g^(-1)and a high capacity retention(96.2%)after 200 cycles.The superior electrochemical performance demonstrates that FVO/CMK-3 is an ideal anode material candidate for fast-charging,stable LIBs with high energy density.
基金Swinburne University of Technology Sarawak Campus and Birmingham City University.
文摘In this article,a hybrid energy storage system powered by renewable energy sources is suggested,which is connected to a grid-tied electric vehicle charging bay(EVCB)in Sarawak and is examined for its techno-economic effects.With a focus on three renewable energy sources,namely hydrokinetic power,solar power,and hydrogen fuel cells,the study seeks to minimize reliance on the electrical grid while meeting the growing demand from the growing electric vehicle(EV)infrastructure.A hybrid renewable energy storage system that combines solar power,hydrogen fuel cells,hydrokinetic power,and the grid was simulated and analyzed.The system design leverages Kuching,Sarawak's unique geographical and renewable source profile,including abundant hydro and solar potential as well as supportive regional energy policies,to optimize economic and environmental performance.The findings showed that the technoeconomic evaluation of the hydrogen storage-integrated EVCB system in Kuching,Sarawak,demonstrates promising performance under current market conditions.The system successfully meets charging demand while generating an annual profit of approximately$5l,104.30 through excess energy sales to the grid.Hydrokinetic power dominates generation,contributing 81.4%of the total output,with the hydrogen fuel cell adding a modest 2.84%.The system achieves a cost of electricity of$0.0617/kWh and a Levelized Cost of Hydrogen of approximately$7.33/kg,confirming its economic feasibility.With a total investment of approximately$2.43 million,the hydrogen storage subsystem represents the largest cost share at 55.2%($1.34 million).A high renewable fraction of 97.2%enhances the system's sustainability,which is further supported by significant annual emissions reductions of approximately 102,209 kg of carbon dioxide,8.48 kg of sulfur dioxide,and 43.1 kg of nitrogen oxides.These results demonstrate that the proposed hybrid EVCB exhibits excellent economic and environmental sustainability,making it a viable option for Sarawak's sustainable electric vehicle charging infrastructure.
基金supported by the National Natural Science Foundation of China(W2412060 and 22325902)the Natural Science Foundation of Tianjin City(24ZXZSSS00310 and 24JCZXJC00170)the NCC Fund(NCC2022FH03)。
文摘Carbonate electrolytes have been widely applied in sodium-ion batteries(SIBs);however,the strong Na^(+) -solvent coordination induces sluggish desolvation kinetics and severe parasitic reactions at hard carbon(HC)anodes.Herein,tris(2,2,2-trifluoroethyl)phosphite(TFEPi)is introduced into a propylene carbonate/diethyl carbonate electrolyte(PDT,PC/DEC/TFEPi in a volume ratio of 5:4:1)to enhance the coordination of Na^(+)-PF_(6)^(-)for fast-charging SIBs.The electron-withdrawing CF_(3)groups in TFEPi reduce the electrondonating ability of carbonate solvents to weaken Na^(+) -solvent interactions and enrich PF_(6)^(-)in the first solvation sheath.This lowers Na^(+) desolvation energy from 68.1 kJ mol^(-1)in PC/DEC with a volume ratio of 5:5 to 54.1 kJ mol^(-1)in PDT.The anion-dominated solvation structure of PDT promotes its preferential adsorption on the HC anode,forming a NaF/Na_(3)PO_(4)-rich solid electrolyte interphase with enhanced Na^(+) transport and mechanical stability.Moreover,the phosphite group of TFEPi scavenges H/OH radicals to suppress combustion chain reactions,endowing PDT with exceptional flame retardancy with selfextinguishing time<1 s g^(-1).It is demonstrated that Na//HC half cell retains 80.6%and 61.7%of HC capacity at 200 and 500 mA g^(-1),respectively,and HC//Na_(3)V_(2)(PO_(4))_(2)F_(3)(NVPF)full cell shows 80%charge capacity of NVPF within 5 min at 1000 mA g^(-1)at 25℃ and maintains stable operation from -20 to 60℃.This work provides new insights into electrolyte solvation engineering for high chargeability and safety of SIBs.
文摘The global public HPC(high-power charging)network for EVs(electric vehicles)is rapidly expanding.This growth is crucial for supporting the increasing adoption of EVs but highlights the industry’s early stage.Regional maturity varies,with China leading due to strong government support,followed by Europe and the United States.A significant challenge is the lack of industry standards,causing inconsistencies in charger types and payment systems.Efforts are underway,to ensure interoperability and reliability.Interoperability is crucial for the success of EV HPC infrastructure,ensuring seamless integration among charge points,management systems,and service providers.Despite the use of protocols like the OCPP(Open Charge Point Protocol),variations in implementation create complexities.Ensuring uniform standards across the ecosystem is essential for reliability and efficiency.Vendor-specific error codes,which are more detailed than standardized codes,are vital for diagnosing issues but lack standardization,adding complexity.Addressing these challenges is key to supporting widespread EV adoption and enhancing user experience.To provide a compelling driver value proposition,EV charging services must be reliable and seamless.The operations and maintenance of the HPC network must be cost-effective and leverage the intelligence of the integrated ecosystem.The technical complexity of managing high-power DC charging,combined with diverse authentication and payment systems,results in numerous potential issues.Moving from reactive to predictive maintenance is essential for undisrupted operations and a smooth driver experience.Shell’s Intelligent Operations Technology Strategy incorporates GenAI elements in its advanced analytics and operational performance management tools.By ingesting big data from multiple sources across the EV ecosystem,Shell engineers can perform detailed pattern recognition and targeted troubleshooting.Monitoring,configurable alerting,and remote fixing based on auto-healing and targeted auto-allocation enhance charger availability and reduce downtime.This automation has evolved Shell’s maintenance and operations strategy from reactive to predictive,improving overall charger performance and user satisfaction.Key achievements include transitioning to prescriptive and preventive asset management approaches,significantly improving uptime and charging experience,and increasing commercial value through cost reduction and enhanced revenue.Future challenges include evolving OCPP,integrating data from non-OCPP systems,and ensuring interoperability across diverse systems.Standardization and cross-collaboration within the industry are essential for smooth interoperability,higher uptime,and increased CSR(charging success rate).Technological innovations will further shape the industry,promoting stabilization and efficiency as it matures.
