Dear Editor,State of health(SOH)estimation is critical for the management of lithium-ion batteries(LIBs).Data-driven estimation methods are appealing with the availability of real-world battery data.However,time-and d...Dear Editor,State of health(SOH)estimation is critical for the management of lithium-ion batteries(LIBs).Data-driven estimation methods are appealing with the availability of real-world battery data.However,time-and data-costly training for batteries with different chemistries and models barriers their efficient deployment.展开更多
Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack ca...Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack capacity utilization,and poses major safety hazards to energy storage systems.To solve this problem,a maximum capacity utilization scheme based on a path planning algorithm is proposed.Specifically,the reconfigurable topology proposed is highly flexible and fault-tolerant,enabling battery pack consistency through alternating cell discharge and reducing the increased risk of short circuits due to relay error.The Dijkstra algorithm is used to find the optimal energy path,which can effectively remove faulty cells and find the current path with the best consistency of the battery pack and the lowest relay loss.Finally,the effectiveness of the scheme is verified by hardware-in-the-loop experiments,and the experimental results show that the state-of-charge SOC consistency of the battery pack at the end of discharge is increased by 34.18%,the relay energy loss is reduced by 0.16%,and the fault unit is effectively isolated.展开更多
Technologies that accelerate the delivery of reliable battery-based energy storage will not only contribute to decarbonization such as transportation electrification,smart grid,but also strengthen the battery supply c...Technologies that accelerate the delivery of reliable battery-based energy storage will not only contribute to decarbonization such as transportation electrification,smart grid,but also strengthen the battery supply chain.As battery inevitably ages with time,losing its capacity to store charge and deliver it efficiently.This directly affects battery safety and efficiency,making related health management necessary.Recent advancements in automation science and engineering raised interest in AI-based solutions to prolong battery lifetime from both manufacturing and management perspectives.This paper aims at presenting a critical review of the state-of-the-art AI-based manufacturing and management strategies towards long lifetime battery.First,AI-based battery manufacturing and smart battery to benefit battery health are showcased.Then the most adopted AI solutions for battery life diagnostic including state-of-health estimation and ageing prediction are reviewed with a discussion of their advantages and drawbacks.Efforts through designing suitable AI solutions to enhance battery longevity are also presented.Finally,the main challenges involved and potential strategies in this field are suggested.This work will inform insights into the feasible,advanced AI for the health-conscious manufacturing,control and optimization of battery on different technology readiness levels.展开更多
With the development of fuel cells,multi-stack fuel cell system(MFCS)for high power application has shown tremendous development potential owing to their obvious advantages including high efficiency,durability,reliabi...With the development of fuel cells,multi-stack fuel cell system(MFCS)for high power application has shown tremendous development potential owing to their obvious advantages including high efficiency,durability,reliability,and pollution-free.Accordingly,the state-of-the-art of MFCS is summarized and analyzed to advance its research.Firstly,the MFCS applications are presented in high-power scenarios,especially in transportation applications.Then,to further investigate the MFCS,MFCS including hydrogen and air subsystem,thermal and water subsystem,multi-stack architecture,and prognostics and health monitoring are reviewed.It is noted that prognostics and health monitoring are investigated rarely in MFCS compared with previous research.In addition,the efficiency and durability of MFCS are not only related to the application field and design principle but also the energy management strategy(EMS).The reason is that the EMS is crucial for lifespan,cost,and efficiency in the multi-stack fuel cell system.Finally,the challenge and development potential of MFCS is proposed to provide insights and guidelines for future research.展开更多
This paper proposes a hierarchical sizing method and a power distribution strategy of a hybrid energy storage system for plug-in hybrid electric vehicles(PHEVs),aiming to reduce both the energy consumption and battery...This paper proposes a hierarchical sizing method and a power distribution strategy of a hybrid energy storage system for plug-in hybrid electric vehicles(PHEVs),aiming to reduce both the energy consumption and battery degradation cost.As the optimal size matching is significant to multi-energy systems like PHEV with both battery and supercapacitor(SC),this hybrid system is adopted herein.First,the hierarchical optimization is conducted,when the optimal power of the internal combustion engine is calculated based on dynamic programming,and a wavelet transformer is introduced to distribute the power between the battery and the SC.Then,the fuel economy and battery degradation are evaluated to return feedback value to each sizing point within the hybrid energy storage system sizing space,obtaining the optimal sizes for the battery and the SC by comparing all the values in the whole sizing space.Finally,an all-hardware test platform is established with a fully active power conversion topology,on which the real-time control capability of the wavelet transformer method and the size matching between the battery and the SC are verified in both short and long time spans.展开更多
Developing new energy vehicles has been a worldwide consensus,and developing new energy vehicles characterized by pure electric drive has been China's national strategy.After more than 20 years of high-quality dev...Developing new energy vehicles has been a worldwide consensus,and developing new energy vehicles characterized by pure electric drive has been China's national strategy.After more than 20 years of high-quality development of China's electric vehicles(EVs),a technological R&D layout of“Three Verticals and Three Horizontals”has been created,and technological advantages have been accumulated.As a result,China's new energy vehicle market has ranked first in the world since 2015.To systematically solve the key problems of battery electric vehicles(BEVs)such as“driving range anxiety,long battery charging time,and driving safety hazards”,China took the lead in putting forward a“system engineering-based technology system architecture for BEVs”and clarifying its connotation.This paper analyzes the research status and progress of the three core components of this architecture,namely,“BEV platform,charging/swapping station,and real-time operation monitoring platform”,and their key technological points.The three major demonstration projects of the 2008 Beijing Olympic Games,the 2022 Beijing Winter Olympics,and the intelligent and connected autonomous battery electric bus project are discussed to specify the applications of BEVs in China.The key research directions for upgrading BEV technologies remain to be further improving the vehicle-level all-climate environmental adaptability and all-day safety of BEVs,systematically solving the charging problem of BEVs and improving their application convenience,and safeguarding safety with early warning and implementing active/passive safety protection for the whole life cycle of power batteries on the basis of BEVs'operation big data.BEVs have acquired new technological features such as intelligent and networked technology empowerment,extensive integration of control-by-wire systems,a platform of chassis hardware,and modularization of functional software.展开更多
Internal short circuit(ISC)is a critical cause for the dangerous thermal runaway of lithium-ion battery(LIB);thus,the accurate early-stage detection of the ISC failure is critical to improving the safety of electric v...Internal short circuit(ISC)is a critical cause for the dangerous thermal runaway of lithium-ion battery(LIB);thus,the accurate early-stage detection of the ISC failure is critical to improving the safety of electric vehicles.In this paper,a model-based and self-diagnostic method for online ISC detection of LIB is proposed using the measured load current and terminal voltage.An equivalent circuit model is built to describe the characteristics of ISC cell.A discrete-time regression model is formulated for the faulty cell model through the system transfer function,based on which the electrical model parameters are adapted online to keep the model accurate.Furthermore,an online ISC detection method is exploited by incorporating an extended Kalman filter-based state of charge estimator,an abnormal charge depletion-based ISC current estimator,and an ISC resistance estimator based on the recursive least squares method with variant forgetting factor.The proposed method shows a self-diagnostic merit relying on the single-cell measurements,which makes it free from the extra uncertainty caused by other cells in the system.Experimental results suggest that the online parameterized model can accurately predict the voltage dynamics of LIB.The proposed diagnostic method can accurately identify the ISC resistance online,thereby contributing to the early-stage detection of ISC fault in the LIB.展开更多
The dynamic response of fuel cell vehicle is greatly affected by the pressure of reactants.Besides,the pressure difference between anode and cathode will also cause mechanical damage to proton exchange membrane.For ma...The dynamic response of fuel cell vehicle is greatly affected by the pressure of reactants.Besides,the pressure difference between anode and cathode will also cause mechanical damage to proton exchange membrane.For maintaining the relative stability of anode pressure,this study proposes a decentralized model predictive controller(DMPC)to control the anodic supply system composed of a feeding and returning ejector assembly.Considering the important influence of load current on the system,the piecewise linearization approach and state space with current-induced disturbance compensation are com-paratively analyzed.Then,an innovative switching strategy is proposed to prevent frequent switching of the sub-model-based controllers and to ensure the most appropriate predictive model is applied.Finally,simulation results demonstrate the better stability and robustness of the proposed control schemes compared with the traditional proportion integration differentia-tion controller under the step load current,variable target and purge disturbance conditions.In particular,in the case of the DC bus load current of a fuel cell hybrid vehicle,the DMPC controller with current-induced disturbance compensation has better stability and target tracking performance with an average error of 0.15 kPa and root mean square error of 1.07 kPa.展开更多
基金partially supported by the Shenzhen Municipal Science and Technology Innovation Committee(RCBS20210609104423057)Fujian Key Laboratory of New Energy Generation and Power Conversion(KLIF-202104)the National Natural Science Foundation of China(52072038)。
文摘Dear Editor,State of health(SOH)estimation is critical for the management of lithium-ion batteries(LIBs).Data-driven estimation methods are appealing with the availability of real-world battery data.However,time-and data-costly training for batteries with different chemistries and models barriers their efficient deployment.
基金supported in part by the National Natural Science Foundation of China(62203352,U2003110)in part by the Key Laboratory Project of Shaanxi Provincial Department of Education(20JS110)in part by the Thousand Talents Plan of Shaanxi Province for Young Professionals。
文摘Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack capacity utilization,and poses major safety hazards to energy storage systems.To solve this problem,a maximum capacity utilization scheme based on a path planning algorithm is proposed.Specifically,the reconfigurable topology proposed is highly flexible and fault-tolerant,enabling battery pack consistency through alternating cell discharge and reducing the increased risk of short circuits due to relay error.The Dijkstra algorithm is used to find the optimal energy path,which can effectively remove faulty cells and find the current path with the best consistency of the battery pack and the lowest relay loss.Finally,the effectiveness of the scheme is verified by hardware-in-the-loop experiments,and the experimental results show that the state-of-charge SOC consistency of the battery pack at the end of discharge is increased by 34.18%,the relay energy loss is reduced by 0.16%,and the fault unit is effectively isolated.
基金This work was supported by the UK HVM Catapult project(8248 CORE)the National Natural Science Foundation of China(52072038,62122041).
文摘Technologies that accelerate the delivery of reliable battery-based energy storage will not only contribute to decarbonization such as transportation electrification,smart grid,but also strengthen the battery supply chain.As battery inevitably ages with time,losing its capacity to store charge and deliver it efficiently.This directly affects battery safety and efficiency,making related health management necessary.Recent advancements in automation science and engineering raised interest in AI-based solutions to prolong battery lifetime from both manufacturing and management perspectives.This paper aims at presenting a critical review of the state-of-the-art AI-based manufacturing and management strategies towards long lifetime battery.First,AI-based battery manufacturing and smart battery to benefit battery health are showcased.Then the most adopted AI solutions for battery life diagnostic including state-of-health estimation and ageing prediction are reviewed with a discussion of their advantages and drawbacks.Efforts through designing suitable AI solutions to enhance battery longevity are also presented.Finally,the main challenges involved and potential strategies in this field are suggested.This work will inform insights into the feasible,advanced AI for the health-conscious manufacturing,control and optimization of battery on different technology readiness levels.
基金This paper is supported in part by funding from State Key Laboratory of Mechanical transmission in Chongqing University(No.:SKLMT-ZZKT-2022R02,No.:2022CDJDX-004 and No.:SKLMT-ZZKT-2022M085)Chongqing Postdoctoral Research Project(Special Grant:2021XM3107)the key technological research funding of Sichuan Province(2021YFG0071).
文摘With the development of fuel cells,multi-stack fuel cell system(MFCS)for high power application has shown tremendous development potential owing to their obvious advantages including high efficiency,durability,reliability,and pollution-free.Accordingly,the state-of-the-art of MFCS is summarized and analyzed to advance its research.Firstly,the MFCS applications are presented in high-power scenarios,especially in transportation applications.Then,to further investigate the MFCS,MFCS including hydrogen and air subsystem,thermal and water subsystem,multi-stack architecture,and prognostics and health monitoring are reviewed.It is noted that prognostics and health monitoring are investigated rarely in MFCS compared with previous research.In addition,the efficiency and durability of MFCS are not only related to the application field and design principle but also the energy management strategy(EMS).The reason is that the EMS is crucial for lifespan,cost,and efficiency in the multi-stack fuel cell system.Finally,the challenge and development potential of MFCS is proposed to provide insights and guidelines for future research.
基金This work was supported by the Nature Science Foundation of China with Grant No.51807008 and China Association for Science and Technology Youth Talent Promotion Project.
文摘This paper proposes a hierarchical sizing method and a power distribution strategy of a hybrid energy storage system for plug-in hybrid electric vehicles(PHEVs),aiming to reduce both the energy consumption and battery degradation cost.As the optimal size matching is significant to multi-energy systems like PHEV with both battery and supercapacitor(SC),this hybrid system is adopted herein.First,the hierarchical optimization is conducted,when the optimal power of the internal combustion engine is calculated based on dynamic programming,and a wavelet transformer is introduced to distribute the power between the battery and the SC.Then,the fuel economy and battery degradation are evaluated to return feedback value to each sizing point within the hybrid energy storage system sizing space,obtaining the optimal sizes for the battery and the SC by comparing all the values in the whole sizing space.Finally,an all-hardware test platform is established with a fully active power conversion topology,on which the real-time control capability of the wavelet transformer method and the size matching between the battery and the SC are verified in both short and long time spans.
文摘Developing new energy vehicles has been a worldwide consensus,and developing new energy vehicles characterized by pure electric drive has been China's national strategy.After more than 20 years of high-quality development of China's electric vehicles(EVs),a technological R&D layout of“Three Verticals and Three Horizontals”has been created,and technological advantages have been accumulated.As a result,China's new energy vehicle market has ranked first in the world since 2015.To systematically solve the key problems of battery electric vehicles(BEVs)such as“driving range anxiety,long battery charging time,and driving safety hazards”,China took the lead in putting forward a“system engineering-based technology system architecture for BEVs”and clarifying its connotation.This paper analyzes the research status and progress of the three core components of this architecture,namely,“BEV platform,charging/swapping station,and real-time operation monitoring platform”,and their key technological points.The three major demonstration projects of the 2008 Beijing Olympic Games,the 2022 Beijing Winter Olympics,and the intelligent and connected autonomous battery electric bus project are discussed to specify the applications of BEVs in China.The key research directions for upgrading BEV technologies remain to be further improving the vehicle-level all-climate environmental adaptability and all-day safety of BEVs,systematically solving the charging problem of BEVs and improving their application convenience,and safeguarding safety with early warning and implementing active/passive safety protection for the whole life cycle of power batteries on the basis of BEVs'operation big data.BEVs have acquired new technological features such as intelligent and networked technology empowerment,extensive integration of control-by-wire systems,a platform of chassis hardware,and modularization of functional software.
基金This work is supported by the National Key R&D Program of China(No.2017YFB0103802).
文摘Internal short circuit(ISC)is a critical cause for the dangerous thermal runaway of lithium-ion battery(LIB);thus,the accurate early-stage detection of the ISC failure is critical to improving the safety of electric vehicles.In this paper,a model-based and self-diagnostic method for online ISC detection of LIB is proposed using the measured load current and terminal voltage.An equivalent circuit model is built to describe the characteristics of ISC cell.A discrete-time regression model is formulated for the faulty cell model through the system transfer function,based on which the electrical model parameters are adapted online to keep the model accurate.Furthermore,an online ISC detection method is exploited by incorporating an extended Kalman filter-based state of charge estimator,an abnormal charge depletion-based ISC current estimator,and an ISC resistance estimator based on the recursive least squares method with variant forgetting factor.The proposed method shows a self-diagnostic merit relying on the single-cell measurements,which makes it free from the extra uncertainty caused by other cells in the system.Experimental results suggest that the online parameterized model can accurately predict the voltage dynamics of LIB.The proposed diagnostic method can accurately identify the ISC resistance online,thereby contributing to the early-stage detection of ISC fault in the LIB.
基金supported in part by the Technological Innovation and Application Demonstration in Chongqing(Major Themes of Industry:cstc2019jscx-zdztzxX0033,cstc2019jscx-fxyd0158).
文摘The dynamic response of fuel cell vehicle is greatly affected by the pressure of reactants.Besides,the pressure difference between anode and cathode will also cause mechanical damage to proton exchange membrane.For maintaining the relative stability of anode pressure,this study proposes a decentralized model predictive controller(DMPC)to control the anodic supply system composed of a feeding and returning ejector assembly.Considering the important influence of load current on the system,the piecewise linearization approach and state space with current-induced disturbance compensation are com-paratively analyzed.Then,an innovative switching strategy is proposed to prevent frequent switching of the sub-model-based controllers and to ensure the most appropriate predictive model is applied.Finally,simulation results demonstrate the better stability and robustness of the proposed control schemes compared with the traditional proportion integration differentia-tion controller under the step load current,variable target and purge disturbance conditions.In particular,in the case of the DC bus load current of a fuel cell hybrid vehicle,the DMPC controller with current-induced disturbance compensation has better stability and target tracking performance with an average error of 0.15 kPa and root mean square error of 1.07 kPa.
