For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery packs.However,existing m...For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery packs.However,existing methods often rely on lengthy battery charging/discharging data or extensive training samples,which hinders their implementation in practical scenarios.To address this issue,a rapid health estimation method based on short-time charging data and limited labels for in-service battery packs is proposed in this paper.First,a digital twin of battery pack is established to emulate its dynamic behavior across various aging levels and inconsistency degrees.Then,increment capacity sequences(△Q)within a short voltage span are extracted from charging process to indicate battery health.Furthermore,data-driven models based on deep convolutional neural network(DCNN)are constructed to estimate battery state of health(SOH),where the synthetic data is employed to pre-train the models,and transfer learning strategies by using fine-tuning and domain adaptation are utilized to enhance the model adaptability.Finally,field data of 10 EVs exhibiting different SOHs are used to verify the proposed methods.By using the△Q with 100 m V voltage change,the SOH of battery packs can be accurately estimated with an error around 3.2%.展开更多
Laser writing is a fast and efficient technology that can produce graphene with a high surface area,whereas laser-induced graphene(LIG)has been widely used in both physics and chemical device application.It is necessa...Laser writing is a fast and efficient technology that can produce graphene with a high surface area,whereas laser-induced graphene(LIG)has been widely used in both physics and chemical device application.It is necessary to update this important progress because it may provide a clue to consider the current challenges and possible future directions.In this review,the basic principles of LIG fabrication are first briefly described for a detailed understanding of the lasing process.Sub-sequently,we summarize the physical device applications of LIGs and describe their advantages,including flexible electronics and energy harvesting.Then,chemical device applications are categorized into chemical sensors,supercapacitors,batteries,and electrocatalysis,and a detailed interpretation is provided.Finally,we present our vision of future developments and challenges in this exciting research field.展开更多
While high-hydrostatic pressure(HHP)has successfully been applied to the pasteurization of fruit and vegetable juice beverages,their qualitystable shelf life during storage has not been fully elucidated.Therefore,we i...While high-hydrostatic pressure(HHP)has successfully been applied to the pasteurization of fruit and vegetable juice beverages,their qualitystable shelf life during storage has not been fully elucidated.Therefore,we investigated the effect of HHP(550 MPa/10 min)treatment on polyphenols,carotenoids,ascorbic acids,and antioxidant capacity in tomato juice and their changes during 4-week refrigerated storage.Hightemperature short-time(HTST,110°C/8.6 s)treatment was used as a control.The results revealed a significantly greater presence of polyphenols,carotenoids,ascorbic acid content,and antioxidant capacity in tomato juice after HHP processing than after HTST processing.However,the total carotenoids and total phenolic content in HHP-treated tomato juice decreased dramatically and approached that in the HTST-treated tomato juice after 1 week of storage.Therefore,HHP’s advantage in maintaining antioxidant compounds and capacity was only evident during the first week of storage in tomato juice.Nevertheless,the post-storage caffeic acid,quercetin,ferulic acid,and p-coumaric acid concentrations were 8.31,4.77,1.86,and 6.84μg/g higher in the HHP-treated than in HTST-treated tomato juice,respectively.This study provides a new perspective for predicting HHP products'quality-stable shelf life.展开更多
Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region.This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination...Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region.This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination of transferred deep learning and Gaussian process regression.General health indicators are extracted from the partial discharge process.The sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation prediction.The future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a comprehensive lifetime prognostic.Besides,only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model construction.Experimental results show that the lifetime prediction errors are less than 25 cycles for the battery pack,even with only 50 cycles for model fine-tuning,which can save about 90%time for the aging experiment.Thus,it largely reduces the time and labor for battery pack investigation.The predicted capacity trends of the battery cells connected in the battery pack accurately reflect the actual degradation of each battery cell,which can reveal the weakest cell for maintenance in advance.展开更多
The exploitation of renewable energy as well as the elimination of the harmful impact of excessive carbon emission are worldwide concerns for sustainable development of the ecological environment on earth.To address t...The exploitation of renewable energy as well as the elimination of the harmful impact of excessive carbon emission are worldwide concerns for sustainable development of the ecological environment on earth.To address that,the technologies regarding energy conversion systems,such as water splitting and electroreduction of carbon dioxide,have attracted significant attention for a few decades.Yet,to date,the production of green fuels and/or high energy density chemicals like hydrogen,methane,and ethanol,are still suffering from many drawbacks including high energy consumption,low selectivity,and sluggish reaction rate.In this regard,nanostructured bimetallic materials that is capable of taking the full benefits of the coupling effects between different elements/components with structure modification in nanoscale are considered as a promising strategy for high-performance electrocatalysts.Herein,this review aims to outline the important progress of these nanostructured bimetallic electrocatalysts.It starts with the introduction of some important fundamental background knowledge about the reaction mechanism to understand how these reactions happen.Subsequently,we summarize the most recent progress regarding how the nanostructured bimetallic electrocatalysts manipulate the activity and selectivity of catalytic reactions in the order of bimetallic alloying effect,interface/substrate effect of bi-component electrocatalyst,and nanostructuring effect.展开更多
A randomized,double-blind,placebo-controlled multicenter trial was conducted in healthy Chinese infants to assess the efficacy and safety of a hexavalent live human-bovine reassortant rotavirus vaccine(HRV)against rot...A randomized,double-blind,placebo-controlled multicenter trial was conducted in healthy Chinese infants to assess the efficacy and safety of a hexavalent live human-bovine reassortant rotavirus vaccine(HRV)against rotavirus gastroenteritis(RVGE).A total of 6400 participants aged 6-12 weeks were enrolled and randomly assigned to either HRV(n?3200)or placebo(n?3200)group.All the subjects received three oral doses of vaccine four weeks apart.The vaccine efficacy(VE)against RVGE caused by rotavirus serotypes contained in HRV was evaluated from 14 days after three doses of administration up until the end of the second rotavirus season.VE against severe RVGE,VE against RVGE hospitalization caused by serotypes contained in HRV,and VE against RVGE,severe RVGE,and RVGE hospitalization caused by natural infection of any serotype of rotavirus were also investigated.All adverse events(AEs)were collected for 30 days after each dose.Serious AEs(SAEs)and intussusception cases were collected during the entire study.Our data showed that VE against RVGE caused by serotypes contained in HRV was 69.21%(95%CI:53.31-79.69).VE against severe RVGE and RVGE hospitalization caused by serotypes contained in HRV were 91.36%(95%CI:78.45-96.53)and 89.21%(95%CI:64.51-96.72)respectively.VE against RVGE,severe RVGE,and RVGE hospitalization caused by natural infection of any serotype of rotavirus were 62.88%(95%CI:49.11-72.92),85.51%(95%CI:72.74-92.30)and 83.68%(95%CI:61.34-93.11).Incidences of AEs from the first dose to one month post the third dose in HRV and placebo groups were comparable.There was no significant difference in incidences of SAEs in HRV and placebo groups.This study shows that this hexavalent reassortant rotavirus vaccine is an effective,well-tolerated,and safe vaccine for Chinese infants.展开更多
In this paper,we propose a benchmark problem for the challengers aiming to energy efficiency control of hybrid electric vehicles(HEVs)on a road with slope.Moreover,it is assumed that the targeted HEVs are in the conne...In this paper,we propose a benchmark problem for the challengers aiming to energy efficiency control of hybrid electric vehicles(HEVs)on a road with slope.Moreover,it is assumed that the targeted HEVs are in the connected environment with the obtainment of real-time information of vehicle-to-everything(V2X),including geographic information,vehicle-to-infrastructure(V2I)information and vehicle-to-vehicle(V2V)information.The provided simulator consists of an industrial-level HEV model and a traffic scenario database obtained through a commercial traffic simulator,where the running route is generated based on real-world data with slope and intersection position.The benchmark problem to be solved is the HEVs powertrain control using traffic information to fulfill fuel economy improvement while satisfying the constraints of driving safety and travel time.To show the HEV powertrain characteristics,a case study is given with the speed planning and energy management strategy.展开更多
Battery packs are applied in various areas(e.g.,electric vehicles,energy storage,space,mining,etc.),which requires the state of health(SOH)to be accurately estimated.Inconsistency,also known as cell variation,is consi...Battery packs are applied in various areas(e.g.,electric vehicles,energy storage,space,mining,etc.),which requires the state of health(SOH)to be accurately estimated.Inconsistency,also known as cell variation,is considered a significant evaluation index that greatly affects the degradation of battery pack.This paper proposes a novel joint inconsistency and SOH estimation method under cycling,which fills the gap of joint estimation based on the fast-charging process for electric vehicles.First,fifteen features are extracted from current change points during the partial charging process.Then,a joint estimation system is designed,where fusion weights are obtained by the analytic hierarchy process and multi-scale sample entropy to evaluate inconsistency.A wrapper is used to select the optimal feature subset,and Gaussian process regression is implemented to estimate the SOH.Finally,the estimation performance is assessed by the test data.The results show that the inconsistency evaluation can reflect the aging conditions,and the inconsistency does affect the aging process.The wrapper selection method improves the accuracy of SOH estimation by about 75.8%compared to the traditional filter method when only 10%of data is used for model training.The maximum absolute error and root mean square error are 2.58%and 0.93%,respectively.展开更多
With the growing demand for energy resources and rising environmental risks,the deployment of electric vehicles has been recognized as effective countermeasures to the global energy crisis and climate change.Lithium-i...With the growing demand for energy resources and rising environmental risks,the deployment of electric vehicles has been recognized as effective countermeasures to the global energy crisis and climate change.Lithium-ion batteries,thanks to their high efficiency,high energy/power density,and long lifespan,are widely used as critical energy storage devices for electric vehicles.Meanwhile,traction batteries play a deciduous role in the reliability,availability,maintainability,and safety of electric vehicles.Therefore,they should be meticulously designed and managed.展开更多
基金supported in part by the National Natural Science Foundation of China,China(Grant No.52102420)the National Key Research and Development Program of China,China(Grant No.2022YFE0102700)the China Postdoctoral Science Foundation,China(Grant No.2023T160085)。
文摘For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery packs.However,existing methods often rely on lengthy battery charging/discharging data or extensive training samples,which hinders their implementation in practical scenarios.To address this issue,a rapid health estimation method based on short-time charging data and limited labels for in-service battery packs is proposed in this paper.First,a digital twin of battery pack is established to emulate its dynamic behavior across various aging levels and inconsistency degrees.Then,increment capacity sequences(△Q)within a short voltage span are extracted from charging process to indicate battery health.Furthermore,data-driven models based on deep convolutional neural network(DCNN)are constructed to estimate battery state of health(SOH),where the synthetic data is employed to pre-train the models,and transfer learning strategies by using fine-tuning and domain adaptation are utilized to enhance the model adaptability.Finally,field data of 10 EVs exhibiting different SOHs are used to verify the proposed methods.By using the△Q with 100 m V voltage change,the SOH of battery packs can be accurately estimated with an error around 3.2%.
基金financially supported by the National Natural Science Foundation of China(NSFC,52003225)Open Fund of Jiangsu Key Laboratory of Nano Devices(21SZ01).
文摘Laser writing is a fast and efficient technology that can produce graphene with a high surface area,whereas laser-induced graphene(LIG)has been widely used in both physics and chemical device application.It is necessary to update this important progress because it may provide a clue to consider the current challenges and possible future directions.In this review,the basic principles of LIG fabrication are first briefly described for a detailed understanding of the lasing process.Sub-sequently,we summarize the physical device applications of LIGs and describe their advantages,including flexible electronics and energy harvesting.Then,chemical device applications are categorized into chemical sensors,supercapacitors,batteries,and electrocatalysis,and a detailed interpretation is provided.Finally,we present our vision of future developments and challenges in this exciting research field.
基金This work was supported by National Key Technologies R&D Programs,China(grant numbers:2017YFD0400705 and 2018YFC1602202).
文摘While high-hydrostatic pressure(HHP)has successfully been applied to the pasteurization of fruit and vegetable juice beverages,their qualitystable shelf life during storage has not been fully elucidated.Therefore,we investigated the effect of HHP(550 MPa/10 min)treatment on polyphenols,carotenoids,ascorbic acids,and antioxidant capacity in tomato juice and their changes during 4-week refrigerated storage.Hightemperature short-time(HTST,110°C/8.6 s)treatment was used as a control.The results revealed a significantly greater presence of polyphenols,carotenoids,ascorbic acid content,and antioxidant capacity in tomato juice after HHP processing than after HTST processing.However,the total carotenoids and total phenolic content in HHP-treated tomato juice decreased dramatically and approached that in the HTST-treated tomato juice after 1 week of storage.Therefore,HHP’s advantage in maintaining antioxidant compounds and capacity was only evident during the first week of storage in tomato juice.Nevertheless,the post-storage caffeic acid,quercetin,ferulic acid,and p-coumaric acid concentrations were 8.31,4.77,1.86,and 6.84μg/g higher in the HHP-treated than in HTST-treated tomato juice,respectively.This study provides a new perspective for predicting HHP products'quality-stable shelf life.
基金Supported by National Natural Science Foundation of China(Grant Nos.51875054,U1864212)Graduate Research and Innovation Foundation of Chongqing+2 种基金China(Grant No.CYS20018)Chongqing Municipal Natural Science Foundation for Distinguished Young Scholars of China(Grant No.cstc2019jcyjjq X0016)Chongqing Science and Technology Bureau of China。
文摘Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region.This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination of transferred deep learning and Gaussian process regression.General health indicators are extracted from the partial discharge process.The sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation prediction.The future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a comprehensive lifetime prognostic.Besides,only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model construction.Experimental results show that the lifetime prediction errors are less than 25 cycles for the battery pack,even with only 50 cycles for model fine-tuning,which can save about 90%time for the aging experiment.Thus,it largely reduces the time and labor for battery pack investigation.The predicted capacity trends of the battery cells connected in the battery pack accurately reflect the actual degradation of each battery cell,which can reveal the weakest cell for maintenance in advance.
文摘The exploitation of renewable energy as well as the elimination of the harmful impact of excessive carbon emission are worldwide concerns for sustainable development of the ecological environment on earth.To address that,the technologies regarding energy conversion systems,such as water splitting and electroreduction of carbon dioxide,have attracted significant attention for a few decades.Yet,to date,the production of green fuels and/or high energy density chemicals like hydrogen,methane,and ethanol,are still suffering from many drawbacks including high energy consumption,low selectivity,and sluggish reaction rate.In this regard,nanostructured bimetallic materials that is capable of taking the full benefits of the coupling effects between different elements/components with structure modification in nanoscale are considered as a promising strategy for high-performance electrocatalysts.Herein,this review aims to outline the important progress of these nanostructured bimetallic electrocatalysts.It starts with the introduction of some important fundamental background knowledge about the reaction mechanism to understand how these reactions happen.Subsequently,we summarize the most recent progress regarding how the nanostructured bimetallic electrocatalysts manipulate the activity and selectivity of catalytic reactions in the order of bimetallic alloying effect,interface/substrate effect of bi-component electrocatalyst,and nanostructuring effect.
基金supported by National Health Commission of the People’s Republic of China (grant number:2019ZX09302059)sponsored and funded by Wuhan Institute of Biological Products Co.,Ltd.,Hubei,China
文摘A randomized,double-blind,placebo-controlled multicenter trial was conducted in healthy Chinese infants to assess the efficacy and safety of a hexavalent live human-bovine reassortant rotavirus vaccine(HRV)against rotavirus gastroenteritis(RVGE).A total of 6400 participants aged 6-12 weeks were enrolled and randomly assigned to either HRV(n?3200)or placebo(n?3200)group.All the subjects received three oral doses of vaccine four weeks apart.The vaccine efficacy(VE)against RVGE caused by rotavirus serotypes contained in HRV was evaluated from 14 days after three doses of administration up until the end of the second rotavirus season.VE against severe RVGE,VE against RVGE hospitalization caused by serotypes contained in HRV,and VE against RVGE,severe RVGE,and RVGE hospitalization caused by natural infection of any serotype of rotavirus were also investigated.All adverse events(AEs)were collected for 30 days after each dose.Serious AEs(SAEs)and intussusception cases were collected during the entire study.Our data showed that VE against RVGE caused by serotypes contained in HRV was 69.21%(95%CI:53.31-79.69).VE against severe RVGE and RVGE hospitalization caused by serotypes contained in HRV were 91.36%(95%CI:78.45-96.53)and 89.21%(95%CI:64.51-96.72)respectively.VE against RVGE,severe RVGE,and RVGE hospitalization caused by natural infection of any serotype of rotavirus were 62.88%(95%CI:49.11-72.92),85.51%(95%CI:72.74-92.30)and 83.68%(95%CI:61.34-93.11).Incidences of AEs from the first dose to one month post the third dose in HRV and placebo groups were comparable.There was no significant difference in incidences of SAEs in HRV and placebo groups.This study shows that this hexavalent reassortant rotavirus vaccine is an effective,well-tolerated,and safe vaccine for Chinese infants.
文摘In this paper,we propose a benchmark problem for the challengers aiming to energy efficiency control of hybrid electric vehicles(HEVs)on a road with slope.Moreover,it is assumed that the targeted HEVs are in the connected environment with the obtainment of real-time information of vehicle-to-everything(V2X),including geographic information,vehicle-to-infrastructure(V2I)information and vehicle-to-vehicle(V2V)information.The provided simulator consists of an industrial-level HEV model and a traffic scenario database obtained through a commercial traffic simulator,where the running route is generated based on real-world data with slope and intersection position.The benchmark problem to be solved is the HEVs powertrain control using traffic information to fulfill fuel economy improvement while satisfying the constraints of driving safety and travel time.To show the HEV powertrain characteristics,a case study is given with the speed planning and energy management strategy.
基金This work was supported in part by the National Natural Science Foundation of China(Grant No.51875054 and Grant No.U1864212)Graduate research and innovation foundation of Chongqing,China(Grant No.CYS20018)Chongqing Natural Science Foundation for Distinguished Young Scholars(Grant No.cstc2019jcyjjq0010),and Chongqing Science and Technology Bureau,China.
文摘Battery packs are applied in various areas(e.g.,electric vehicles,energy storage,space,mining,etc.),which requires the state of health(SOH)to be accurately estimated.Inconsistency,also known as cell variation,is considered a significant evaluation index that greatly affects the degradation of battery pack.This paper proposes a novel joint inconsistency and SOH estimation method under cycling,which fills the gap of joint estimation based on the fast-charging process for electric vehicles.First,fifteen features are extracted from current change points during the partial charging process.Then,a joint estimation system is designed,where fusion weights are obtained by the analytic hierarchy process and multi-scale sample entropy to evaluate inconsistency.A wrapper is used to select the optimal feature subset,and Gaussian process regression is implemented to estimate the SOH.Finally,the estimation performance is assessed by the test data.The results show that the inconsistency evaluation can reflect the aging conditions,and the inconsistency does affect the aging process.The wrapper selection method improves the accuracy of SOH estimation by about 75.8%compared to the traditional filter method when only 10%of data is used for model training.The maximum absolute error and root mean square error are 2.58%and 0.93%,respectively.
文摘With the growing demand for energy resources and rising environmental risks,the deployment of electric vehicles has been recognized as effective countermeasures to the global energy crisis and climate change.Lithium-ion batteries,thanks to their high efficiency,high energy/power density,and long lifespan,are widely used as critical energy storage devices for electric vehicles.Meanwhile,traction batteries play a deciduous role in the reliability,availability,maintainability,and safety of electric vehicles.Therefore,they should be meticulously designed and managed.
