The insulating paper of the transformer is affected by many factors during the operation,meanwhile,the surface texture of the paper is easy to change.To explore the relationship between the aging state and surface tex...The insulating paper of the transformer is affected by many factors during the operation,meanwhile,the surface texture of the paper is easy to change.To explore the relationship between the aging state and surface texture change of insulating paper,firstly,the thermal aging experiment of insulating paper is carried out,and the insulating paper samples with different aging times are obtained.After then,the images of the aged insulating paper samples are collected and pre-processed.The pre-processing effect is verified by constructing and calculating the gray surface of the sample.Secondly,the texture features of the insulating paper image are extracted by box dimension and multifractal spectrum.Based on that,the extreme learning machine(ELM)is taken as the classification tool with texture features and aging time as the input and output,to train the algorithm and construct the corresponding relationship between the texture feature and the aging time.After then,the insulating paper with unknown aging time is predicted with a trained ELMalgorithm.The numerical test results show that the texture features extracted from the fractal dimension of the micro image can effectively characterize the aging state of insulating paper,the average accuracy can reach 91.6%.It proves that the fractal dimension theory can be utilized for assessing the aging state of insulating paper for onsite applications.展开更多
This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles(ICEVs).First,the functional characteristics of batterie...This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles(ICEVs).First,the functional characteristics of batteries in ICEVs are investigated.Then,an adaptive functional state model is proposed to represent battery aging throughout the entire battery service life.A battery protection scheme is developed,including over-discharge and graded over-current protection to improve battery safety.A model-based energy management strategy is synthesized to comprehensively optimize fuel economy,battery life preservation,and vehicle performance.The performance of the proposed scheme was examined under comprehensive test scenarios based on field and bench tests.The results show that the proposed energy management algorithm can effectively improve fuel economy.展开更多
Lithium-ion batteries(LIBs), as the first choice for green batteries, have been widely used in energy storage, electric vehicles, 3C devices, and other related fields, and will have greater application prospects in th...Lithium-ion batteries(LIBs), as the first choice for green batteries, have been widely used in energy storage, electric vehicles, 3C devices, and other related fields, and will have greater application prospects in the future. However, one of the obstacles hindering the future development of battery technology is how to accurately evaluate and monitor battery health, which affects the entire lifespan of battery use. It is not enough to assess battery health comprehensively through the state of health(SoH) alone, especially when nonlinear aging occurs in onboard applications. Here, for the first time, we propose a brand-new health evaluation indicator—state of nonlinear aging(SoNA) to explain the nonlinear aging phenomenon that occurs during the battery use, and also design a knee-point identification method and two SoNA quantitative methods. We apply our health evaluation indicator to build a complete LIB full-lifespan grading evaluation system and a ground-to-cloud service framework, which integrates multi-scenario data collection, multi-dimensional data-based grading evaluation, and cloud management functions. Our works fill the gap in the LIBs’ health evaluation of nonlinear aging, which is of great significance for the health and safety evaluation of LIBs in the field of echelon utilization such as vehicles and energy storage. In addition, this comprehensive evaluation system and service framework are expected to be extended to other battery material systems other than LIBs, yet guiding the design of new energy ecosystem.展开更多
基金This work was supported by the Tianyou Youth Talent Lift Program of Lanzhou Jiaotong University,the Youth Science Foundation of Lanzhou Jiaotong University(No.2019029)the University Innovation Fund Project of Gansu Provincial Department of Education(No.2020A-036)the Young Doctor Foundation of JYT.GANSU.GOV.CN(No.2021QB-060).
文摘The insulating paper of the transformer is affected by many factors during the operation,meanwhile,the surface texture of the paper is easy to change.To explore the relationship between the aging state and surface texture change of insulating paper,firstly,the thermal aging experiment of insulating paper is carried out,and the insulating paper samples with different aging times are obtained.After then,the images of the aged insulating paper samples are collected and pre-processed.The pre-processing effect is verified by constructing and calculating the gray surface of the sample.Secondly,the texture features of the insulating paper image are extracted by box dimension and multifractal spectrum.Based on that,the extreme learning machine(ELM)is taken as the classification tool with texture features and aging time as the input and output,to train the algorithm and construct the corresponding relationship between the texture feature and the aging time.After then,the insulating paper with unknown aging time is predicted with a trained ELMalgorithm.The numerical test results show that the texture features extracted from the fractal dimension of the micro image can effectively characterize the aging state of insulating paper,the average accuracy can reach 91.6%.It proves that the fractal dimension theory can be utilized for assessing the aging state of insulating paper for onsite applications.
基金supported by National Natural Science Foundation of China(Grant No.52002209)Beijing Nova Program,and the State Key Laboratory of Automotive Safety and Energy(Grant No.KFY2210).
文摘This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles(ICEVs).First,the functional characteristics of batteries in ICEVs are investigated.Then,an adaptive functional state model is proposed to represent battery aging throughout the entire battery service life.A battery protection scheme is developed,including over-discharge and graded over-current protection to improve battery safety.A model-based energy management strategy is synthesized to comprehensively optimize fuel economy,battery life preservation,and vehicle performance.The performance of the proposed scheme was examined under comprehensive test scenarios based on field and bench tests.The results show that the proposed energy management algorithm can effectively improve fuel economy.
基金financially supported by the National Natural Science Foundation of China(NSFC,U20A20310,52107230,52176199,52102470)the support of the research project Model2Life(03XP0334),funded by the German Federal Ministry of Education and Research(BMBF)。
文摘Lithium-ion batteries(LIBs), as the first choice for green batteries, have been widely used in energy storage, electric vehicles, 3C devices, and other related fields, and will have greater application prospects in the future. However, one of the obstacles hindering the future development of battery technology is how to accurately evaluate and monitor battery health, which affects the entire lifespan of battery use. It is not enough to assess battery health comprehensively through the state of health(SoH) alone, especially when nonlinear aging occurs in onboard applications. Here, for the first time, we propose a brand-new health evaluation indicator—state of nonlinear aging(SoNA) to explain the nonlinear aging phenomenon that occurs during the battery use, and also design a knee-point identification method and two SoNA quantitative methods. We apply our health evaluation indicator to build a complete LIB full-lifespan grading evaluation system and a ground-to-cloud service framework, which integrates multi-scenario data collection, multi-dimensional data-based grading evaluation, and cloud management functions. Our works fill the gap in the LIBs’ health evaluation of nonlinear aging, which is of great significance for the health and safety evaluation of LIBs in the field of echelon utilization such as vehicles and energy storage. In addition, this comprehensive evaluation system and service framework are expected to be extended to other battery material systems other than LIBs, yet guiding the design of new energy ecosystem.
