Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most...Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.展开更多
High-voltage power supply (HVPS) of Electron Cyclotron Resonance Heating (ECRH) for HT-7 and HT-7U is presently being constructed. The high voltage (100 kV) energy of HVPS is stored in the capacitor banks, and they ca...High-voltage power supply (HVPS) of Electron Cyclotron Resonance Heating (ECRH) for HT-7 and HT-7U is presently being constructed. The high voltage (100 kV) energy of HVPS is stored in the capacitor banks, and they can power one or two gyrotrons. All the operation of the charging system will be done by the control system, where the field signals are interfaced to programmable logic controller (PLC). The use of PLC not only simplifies the control system, but also enhances the reliability. The software written by using configuration software installed in the master computer allows for remote and multiple operator control, and the status and data information is also remotely available.展开更多
In industry development strategy of electric vehicles, apart from concerns on the development of electric vehicles, we also need to consider the issue of charging facilities construction. Firstly, through analysis, th...In industry development strategy of electric vehicles, apart from concerns on the development of electric vehicles, we also need to consider the issue of charging facilities construction. Firstly, through analysis, this paper discusses the importance of AC charging points for electric vehicle development. By studying existing AC charging points on the market, it presents a low-cost smart AC charging system to reduce the cost investigated by power companies and operational bodies when laying of a large number of AC charging points. Compared with the conventional one, the proposed system has prominent features of low cost, small footprint and low investment.展开更多
Recently,there has been a huge increase in the usage of fuel resources for automobiles which is severely affecting the climate and causing global warming.The use of electric vehicle(EV)is an effective way to protect t...Recently,there has been a huge increase in the usage of fuel resources for automobiles which is severely affecting the climate and causing global warming.The use of electric vehicle(EV)is an effective way to protect the environment and reduce travel costs.However,the EV charging system has a single charging source,and the charging rate is limited.In this paper,an EV wireless charging system based on dual source power supply has been developed.It realizes intelligent switching between 12 V photovoltaic output and 220 V AC dual source power,and has wireless transmission function.Based on the proposed power supply architecture,the micro wireless charging model is built,which enables the EV model to store power and realize static and mobile control through the wireless induction charging system.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
Electric Vehicle(EV)‘DC Fast Charging’systems directly connect an EV's battery to an external charger.A compromised EV charger may damage the EV or be used as part of a demand-side power grid attack.We show that...Electric Vehicle(EV)‘DC Fast Charging’systems directly connect an EV's battery to an external charger.A compromised EV charger may damage the EV or be used as part of a demand-side power grid attack.We show that the newest charging standard ISO 15118–20 is not sufficient to prevent charging attacks,as it provides no mechanism to verify charger integrity.We present system and threat models for the attack,before defining an extension to ISO 15118–20 that adds support for firmware integrity verification through remote attestation,while remaining interoperable with non-supporting devices.A proof of concept implementation demonstrates the security improvement by protecting against the specified attack while requiring only 85 bytes of secure storage,8 kB of working memory,and adding less than 0.5 s to the length of a charging session.Backwards compatibility with an implementation of the original standard is also demonstrated.展开更多
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
As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation c...As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.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
We proposed a strategy to address the issue by synthesizing MnO with half-filled 3 d electron orbitals.That is,MnO nanocubes with an edge length of 61.82 nm were successfully prepared through electros-pinning and one-...We proposed a strategy to address the issue by synthesizing MnO with half-filled 3 d electron orbitals.That is,MnO nanocubes with an edge length of 61.82 nm were successfully prepared through electros-pinning and one-step pyrolysis as the cathode electrode for Li-O_(2)batteries.It is observed that the intermediate LiMnO_(4)rather than Li_(2)O_(2)is formed when LiO_(2)interactes with MnO(111)during the discharge process.It is precisely because of LiMnO_(4)that reduces its charge overpotential to 0.29 V.The novel reaction mechanism dominated by LiMnO_(4)further facilitates the lower charge overpotential,thereby enhancing the energy efficiency of the batteries.展开更多
The wireless electric vehicle(EV) charging system is highly safe and flexible. To reduce the weight and cost of EVs, the wireless charging system, which simplifies the structure inside an EV and utilizes the transmitt...The wireless electric vehicle(EV) charging system is highly safe and flexible. To reduce the weight and cost of EVs, the wireless charging system, which simplifies the structure inside an EV and utilizes the transmitter-side control method, has become popular. This study investigates the transmitter-side control methods in a wireless EV charging system. First, a universal wireless charging system is introduced, and the function of its transfer power is derived. It is observed that the transfer power can be controlled by regulating either the phase-shift angle or the DC-link voltage. Further, the influence of the control variables is studied using numerical analysis. Additionally, the corresponding control methods, namely the phase-shift angle and the DC-link voltage control, are compared by calculation and simulation. It is found that:(1) the system efficiency is low with the phase-shift control method because of the converter switching loss;(2) the dynamic response is slow with the DC-link voltage control method because of the large inertia of the inductor and capacitor;(3) both the control methods have limitations in their adjustable power range. Therefore, a combined control method is proposed, with the advantages of high system efficiency, fast dynamic response, and wide adjustable power range. Finally, experiments are performed to verify the validity of the theoretical analysis and the effectiveness of the proposed method. This study provides a detailed and comprehensive analysis of the transmitter-side control methods in the wireless charging system, considering the sensitivity of parameters, converter losses, system efficiency,and dynamic performance, with the dead-time effect taken into consideration. Moreover, the proposed control method can be used to realize the optimal combination of the phase-shift angle and the DC-link voltage with good dynamic performance, and it is useful for the optimal operation of the wireless charging system.展开更多
A three-dimensional model was established by the discrete element method （DEM） to analyze the flow and segregation of particles in a charging process in detail. The simulation results of the burden falling trajector...A three-dimensional model was established by the discrete element method （DEM） to analyze the flow and segregation of particles in a charging process in detail. The simulation results of the burden falling trajectory obtained by the model were compared with the industrial charging measurements to validate the applicability of the model. The flow behavior of particles from the weighing hopper to the top layer of a blast furnace and the heaping behavior were analyzed using this model. A radial segregation index （RSI） was used to evaluate the extent of the size segregation in the charging process. In addition, the influence of the chute inclination angle on the size segregation and burden profile during the charging process was investigated.展开更多
Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV users.This paper proposes a multi-objective optimal operation...Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV users.This paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power grid.The proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,simultaneously.Afterwards,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling problem.Finally,simulation studies verify the effectiveness of the proposed multi-objective operation method.展开更多
The integration of the Internet of Vehicles(IoV)in future smart cities could help solve many traffic-related challenges,such as reducing traffic congestion and traffic accidents.Various congestion pricing and electric...The integration of the Internet of Vehicles(IoV)in future smart cities could help solve many traffic-related challenges,such as reducing traffic congestion and traffic accidents.Various congestion pricing and electric vehicle charging policies have been introduced in recent years.Nonetheless,the majority of these schemes emphasize penalizing the vehicles that opt to take the congested roads or charge in the crowded charging station and do not reward the vehicles that cooperate with the traffic management system.In this paper,we propose a novel dynamic traffic congestion pricing and electric vehicle charging management system for the internet of vehicles in an urban smart city environment.The proposed system rewards the drivers that opt to take alternative congested-free ways and congested-free charging stations.We propose a token management system that serves as a virtual currency,where the vehicles earn these tokens if they take alternative non-congested ways and charging stations and use the tokens to pay for the charging fees.The proposed system is designed for Vehicular Ad-hoc Networks(VANETs)in the context of a smart city environment without the need to set up any expensive toll collection stations.Through large-scale traffic simulation in different smart city scenarios,it is proved that the system can reduce the traffic congestion and the total charging time at the charging stations.展开更多
Efficient fast-charging technology is necessary for the extension of the driving range of electric vehicles.However,lithium-ion cells generate immense heat at high-current charging rates.In order to address this probl...Efficient fast-charging technology is necessary for the extension of the driving range of electric vehicles.However,lithium-ion cells generate immense heat at high-current charging rates.In order to address this problem,an efficient fast charging–cooling scheduling method is urgently needed.In this study,a liquid cooling-based thermal management system equipped with mini-channels was designed for the fastcharging process of a lithium-ion battery module.A neural network-based regression model was proposed based on 81 sets of experimental data,which consisted of three sub-models and considered three outputs:maximum temperature,temperature standard deviation,and energy consumption.Each sub-model had a desirable testing accuracy(99.353%,97.332%,and 98.381%)after training.The regression model was employed to predict all three outputs among a full dataset,which combined different charging current rates(0.5C,1C,1.5C,2C,and 2.5C(1C=5 A))at three different charging stages,and a range of coolant rates(0.0006,0.0012,and 0.0018 kg·s^(-1)).An optimal charging–cooling schedule was selected from the predicted dataset and was validated by the experiments.The results indicated that the battery module’s state of charge value increased by 0.5 after 15 min,with an energy consumption lower than 0.02 J.The maximum temperature and temperature standard deviation could be controlled within 33.35 and 0.8C,respectively.The approach described herein can be used by the electric vehicles industry in real fast-charging conditions.Moreover,optimal fast charging-cooling schedule can be predicted based on the experimental data obtained,that in turn,can significantly improve the efficiency of the charging process design as well as control energy consumption during cooling.展开更多
1.Introduction As one of the priorities for government subsidies and financial incentives,the global stock of electric buses(EBs)has exceeded 670,000 units by the end of 2021(IEA,2022).Despite recent achievements in p...1.Introduction As one of the priorities for government subsidies and financial incentives,the global stock of electric buses(EBs)has exceeded 670,000 units by the end of 2021(IEA,2022).Despite recent achievements in procuring EBs,it still represents less than 4%of the global fleet size.The large-scale implementation of this grid-dependent technology confronts two key challenges:(1)limited range combined with long charging time and(2)insufficient charging infrastructure(Perumal et al.,2021).These impediments are now being tackled by(1)high energy density and(2)the opportunity for fast charging.We are optimistic about battery technology,but the current experiments are still a long way from becoming commercially viable.Besides,the authors argue that the utilization of the pricey charging station/lane will be unexpectedly low.With two terminal chargers available for energy replenishment,the authors approximated the daily charging requirement for sixteen EBs on the fully electrified bus Line 16 in Gothenburg,Sweden.The result in Fig.1(a)indicates that the average daily occupancy was 10.3%,with Terminals 1 and 2 seeing 10%and 10.76%,respectively.We expect utilization to grow as the market and investor expectations mature.The amount of enhanced usage through shared charging stations will,however,be considerably constrained due to the particular position and access time of bus terminals.展开更多
Under an in-phase assumption, the complete charging for an energy harvesting system is studied, which consists of a piezoelectric energy harvester(PEH), a bridge rectifier, a filter capacitor, a switch, a controller a...Under an in-phase assumption, the complete charging for an energy harvesting system is studied, which consists of a piezoelectric energy harvester(PEH), a bridge rectifier, a filter capacitor, a switch, a controller and a rechargeable battery. For the transient charging, the results indicate that the voltage across the filter capacitor increases as the charging proceeds, which is consistent with that reported in the literature. However, a new finding shows that the charging rate and energy harvesting efficiency decrease over time after their respective peak values are acquired.For the steady-state charging, the results reveal that the energy harvesting efficiency can be adjusted by altering the critical charging voltage that controls the transition of the system. The optimal energy harvesting efficiency is limited by the optimal efficiency of the transient charging. Finally, the relationship between the critical charging voltage and the equivalent resistance of the controller and rechargeable battery is established explicitly.展开更多
文摘Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.
基金The project supported by the National Meg-science Engineering Project of the Chinese Government
文摘High-voltage power supply (HVPS) of Electron Cyclotron Resonance Heating (ECRH) for HT-7 and HT-7U is presently being constructed. The high voltage (100 kV) energy of HVPS is stored in the capacitor banks, and they can power one or two gyrotrons. All the operation of the charging system will be done by the control system, where the field signals are interfaced to programmable logic controller (PLC). The use of PLC not only simplifies the control system, but also enhances the reliability. The software written by using configuration software installed in the master computer allows for remote and multiple operator control, and the status and data information is also remotely available.
文摘In industry development strategy of electric vehicles, apart from concerns on the development of electric vehicles, we also need to consider the issue of charging facilities construction. Firstly, through analysis, this paper discusses the importance of AC charging points for electric vehicle development. By studying existing AC charging points on the market, it presents a low-cost smart AC charging system to reduce the cost investigated by power companies and operational bodies when laying of a large number of AC charging points. Compared with the conventional one, the proposed system has prominent features of low cost, small footprint and low investment.
基金supported in part by the National Natural Science Foundation of China(No.62371233)in part by the Aviation Science Foundation Project(Nos.2022Z024052003,20230058052001)。
文摘Recently,there has been a huge increase in the usage of fuel resources for automobiles which is severely affecting the climate and causing global warming.The use of electric vehicle(EV)is an effective way to protect the environment and reduce travel costs.However,the EV charging system has a single charging source,and the charging rate is limited.In this paper,an EV wireless charging system based on dual source power supply has been developed.It realizes intelligent switching between 12 V photovoltaic output and 220 V AC dual source power,and has wireless transmission function.Based on the proposed power supply architecture,the micro wireless charging model is built,which enables the EV model to store power and realize static and mobile control through the wireless induction charging system.
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.
文摘Electric Vehicle(EV)‘DC Fast Charging’systems directly connect an EV's battery to an external charger.A compromised EV charger may damage the EV or be used as part of a demand-side power grid attack.We show that the newest charging standard ISO 15118–20 is not sufficient to prevent charging attacks,as it provides no mechanism to verify charger integrity.We present system and threat models for the attack,before defining an extension to ISO 15118–20 that adds support for firmware integrity verification through remote attestation,while remaining interoperable with non-supporting devices.A proof of concept implementation demonstrates the security improvement by protecting against the specified attack while requiring only 85 bytes of secure storage,8 kB of working memory,and adding less than 0.5 s to the length of a charging session.Backwards compatibility with an implementation of the original standard is also demonstrated.
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.
基金supported by Science and Technology Project of China Southern Power Grid Company(036000KK52222007(GDKJXM20222121)).
文摘As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.
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Funded by the National Natural Science Foundation of China(No.22075035)the Technology Planning Project of Liaoning Province(No.2020JH2/10700008)the Dalian Science and Technology Innovation Fund Project(No.2022JJ11CG005)。
文摘We proposed a strategy to address the issue by synthesizing MnO with half-filled 3 d electron orbitals.That is,MnO nanocubes with an edge length of 61.82 nm were successfully prepared through electros-pinning and one-step pyrolysis as the cathode electrode for Li-O_(2)batteries.It is observed that the intermediate LiMnO_(4)rather than Li_(2)O_(2)is formed when LiO_(2)interactes with MnO(111)during the discharge process.It is precisely because of LiMnO_(4)that reduces its charge overpotential to 0.29 V.The novel reaction mechanism dominated by LiMnO_(4)further facilitates the lower charge overpotential,thereby enhancing the energy efficiency of the batteries.
基金supported by the International Science and Technology Cooperation Program of China(Grant No.2016YFE0102200)
文摘The wireless electric vehicle(EV) charging system is highly safe and flexible. To reduce the weight and cost of EVs, the wireless charging system, which simplifies the structure inside an EV and utilizes the transmitter-side control method, has become popular. This study investigates the transmitter-side control methods in a wireless EV charging system. First, a universal wireless charging system is introduced, and the function of its transfer power is derived. It is observed that the transfer power can be controlled by regulating either the phase-shift angle or the DC-link voltage. Further, the influence of the control variables is studied using numerical analysis. Additionally, the corresponding control methods, namely the phase-shift angle and the DC-link voltage control, are compared by calculation and simulation. It is found that:(1) the system efficiency is low with the phase-shift control method because of the converter switching loss;(2) the dynamic response is slow with the DC-link voltage control method because of the large inertia of the inductor and capacitor;(3) both the control methods have limitations in their adjustable power range. Therefore, a combined control method is proposed, with the advantages of high system efficiency, fast dynamic response, and wide adjustable power range. Finally, experiments are performed to verify the validity of the theoretical analysis and the effectiveness of the proposed method. This study provides a detailed and comprehensive analysis of the transmitter-side control methods in the wireless charging system, considering the sensitivity of parameters, converter losses, system efficiency,and dynamic performance, with the dead-time effect taken into consideration. Moreover, the proposed control method can be used to realize the optimal combination of the phase-shift angle and the DC-link voltage with good dynamic performance, and it is useful for the optimal operation of the wireless charging system.
基金the National Key Technology R&D Program in the 12th Five Year Plan of China(No.2011BAC01B02)for the financial support
文摘A three-dimensional model was established by the discrete element method （DEM） to analyze the flow and segregation of particles in a charging process in detail. The simulation results of the burden falling trajectory obtained by the model were compared with the industrial charging measurements to validate the applicability of the model. The flow behavior of particles from the weighing hopper to the top layer of a blast furnace and the heaping behavior were analyzed using this model. A radial segregation index （RSI） was used to evaluate the extent of the size segregation in the charging process. In addition, the influence of the chute inclination angle on the size segregation and burden profile during the charging process was investigated.
基金This work was supported by the Key Scientific and Technological Research Project of State Grid Corporation of China(No.5400-202022113A-0-0-00).
文摘Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV users.This paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power grid.The proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,simultaneously.Afterwards,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling problem.Finally,simulation studies verify the effectiveness of the proposed multi-objective operation method.
基金supported by the Fundamental Research Funds for Central Universities of China(No.FRF-GF-18-009B,No.FRF-BD-18-001A)the 111 Project(Grant No.B12012).
文摘The integration of the Internet of Vehicles(IoV)in future smart cities could help solve many traffic-related challenges,such as reducing traffic congestion and traffic accidents.Various congestion pricing and electric vehicle charging policies have been introduced in recent years.Nonetheless,the majority of these schemes emphasize penalizing the vehicles that opt to take the congested roads or charge in the crowded charging station and do not reward the vehicles that cooperate with the traffic management system.In this paper,we propose a novel dynamic traffic congestion pricing and electric vehicle charging management system for the internet of vehicles in an urban smart city environment.The proposed system rewards the drivers that opt to take alternative congested-free ways and congested-free charging stations.We propose a token management system that serves as a virtual currency,where the vehicles earn these tokens if they take alternative non-congested ways and charging stations and use the tokens to pay for the charging fees.The proposed system is designed for Vehicular Ad-hoc Networks(VANETs)in the context of a smart city environment without the need to set up any expensive toll collection stations.Through large-scale traffic simulation in different smart city scenarios,it is proved that the system can reduce the traffic congestion and the total charging time at the charging stations.
基金This work was supported by the Program for Huazhong University of Science and Technology(HUST)Academic Frontier Youth Team(2017QYTD04)the Program for HUST Graduate Innovation and Entrepreneurship Fund(2019YGSCXCY037)+2 种基金Authors acknowledge Grant DMETKF2018019 by State Key Laboratory of Digital Manufacturing Equipment and Technology,Huazhong University of Science and TechnologyThis study was also financially supported by the Guangdong Science and Technology Project(2016B020240001)the Guangdong Natural Science Foundation(2018A030310150).
文摘Efficient fast-charging technology is necessary for the extension of the driving range of electric vehicles.However,lithium-ion cells generate immense heat at high-current charging rates.In order to address this problem,an efficient fast charging–cooling scheduling method is urgently needed.In this study,a liquid cooling-based thermal management system equipped with mini-channels was designed for the fastcharging process of a lithium-ion battery module.A neural network-based regression model was proposed based on 81 sets of experimental data,which consisted of three sub-models and considered three outputs:maximum temperature,temperature standard deviation,and energy consumption.Each sub-model had a desirable testing accuracy(99.353%,97.332%,and 98.381%)after training.The regression model was employed to predict all three outputs among a full dataset,which combined different charging current rates(0.5C,1C,1.5C,2C,and 2.5C(1C=5 A))at three different charging stages,and a range of coolant rates(0.0006,0.0012,and 0.0018 kg·s^(-1)).An optimal charging–cooling schedule was selected from the predicted dataset and was validated by the experiments.The results indicated that the battery module’s state of charge value increased by 0.5 after 15 min,with an energy consumption lower than 0.02 J.The maximum temperature and temperature standard deviation could be controlled within 33.35 and 0.8C,respectively.The approach described herein can be used by the electric vehicles industry in real fast-charging conditions.Moreover,optimal fast charging-cooling schedule can be predicted based on the experimental data obtained,that in turn,can significantly improve the efficiency of the charging process design as well as control energy consumption during cooling.
基金supported by the National Natural Science Foundation of China(NSFC)(Grant Nos.52221005 and 52220105001).
文摘1.Introduction As one of the priorities for government subsidies and financial incentives,the global stock of electric buses(EBs)has exceeded 670,000 units by the end of 2021(IEA,2022).Despite recent achievements in procuring EBs,it still represents less than 4%of the global fleet size.The large-scale implementation of this grid-dependent technology confronts two key challenges:(1)limited range combined with long charging time and(2)insufficient charging infrastructure(Perumal et al.,2021).These impediments are now being tackled by(1)high energy density and(2)the opportunity for fast charging.We are optimistic about battery technology,but the current experiments are still a long way from becoming commercially viable.Besides,the authors argue that the utilization of the pricey charging station/lane will be unexpectedly low.With two terminal chargers available for energy replenishment,the authors approximated the daily charging requirement for sixteen EBs on the fully electrified bus Line 16 in Gothenburg,Sweden.The result in Fig.1(a)indicates that the average daily occupancy was 10.3%,with Terminals 1 and 2 seeing 10%and 10.76%,respectively.We expect utilization to grow as the market and investor expectations mature.The amount of enhanced usage through shared charging stations will,however,be considerably constrained due to the particular position and access time of bus terminals.
基金Supported by the National Natural Science Foundation of China(No.51205302)Fundamental Research Funds for the Central Universities(No.K5051304011)
文摘Under an in-phase assumption, the complete charging for an energy harvesting system is studied, which consists of a piezoelectric energy harvester(PEH), a bridge rectifier, a filter capacitor, a switch, a controller and a rechargeable battery. For the transient charging, the results indicate that the voltage across the filter capacitor increases as the charging proceeds, which is consistent with that reported in the literature. However, a new finding shows that the charging rate and energy harvesting efficiency decrease over time after their respective peak values are acquired.For the steady-state charging, the results reveal that the energy harvesting efficiency can be adjusted by altering the critical charging voltage that controls the transition of the system. The optimal energy harvesting efficiency is limited by the optimal efficiency of the transient charging. Finally, the relationship between the critical charging voltage and the equivalent resistance of the controller and rechargeable battery is established explicitly.
