Metal–organic frameworks(MOFs),which are generally considered to be crystalline materials comprising metal centers and organic ligands,have attracted growing attention because of their controllable structures and hig...Metal–organic frameworks(MOFs),which are generally considered to be crystalline materials comprising metal centers and organic ligands,have attracted growing attention because of their controllable structures and high porosity.MOFs based on transition metals(Fe,Co,Ni)are highly effi cient electrode materials for electrochemical energy storage.In this review,the characteristics of Fe-MOFs,Co-MOFs,Ni-MOFs,and their derivatives are summarized,and the relationships between the structures and performance are unveiled in depth.Additionally,their applications in lithium–ion batteries,lithium–sulfur batteries,and supercapacitors are discussed.This review sheds light on the development of MOFs and their derivatives to realize excellent electrochemical performance.展开更多
It is widely accepted that the variation of ambient temperature has great influence on the battery model parameters and state-of-charge(SOC) estimation, and the accurate SOC estimation is a significant issue for devel...It is widely accepted that the variation of ambient temperature has great influence on the battery model parameters and state-of-charge(SOC) estimation, and the accurate SOC estimation is a significant issue for developing the battery management system in electric vehicles. To address this problem, in this paper we propose an enhanced equivalent circuit model(ECM) considering the influence of different ambient temperatures on the open-circuit voltage for a lithium-ion battery. Based on this model, the exponential-function fitting method is adopted to identify the battery parameters according to the test data collected from the experimental platform. And then, the extended Kalman filter(EKF) algorithm is employed to estimate the battery SOC of this battery ECM. The performance of the proposed ECM is verified by using the test profiles of hybrid pulse power characterization(HPPC) and the standard US06 driving cycles(US06) at various ambient temperatures, and by comparing with the common ECM with a second-order resistance capacitor. The simulation and experimental results show that the enhanced battery ECM can improve the battery SOC estimation accuracy under different operating conditions.展开更多
基金supported by the National Natural Science Foundation of China (Nos. NSFC-U1904215)the Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (TAPP)+2 种基金the Natural Science Foundation of Jiangsu Province (No. BK20200044)Program for Young Changjiang Scholars of the Ministry of Education,China (No. Q2018270)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘Metal–organic frameworks(MOFs),which are generally considered to be crystalline materials comprising metal centers and organic ligands,have attracted growing attention because of their controllable structures and high porosity.MOFs based on transition metals(Fe,Co,Ni)are highly effi cient electrode materials for electrochemical energy storage.In this review,the characteristics of Fe-MOFs,Co-MOFs,Ni-MOFs,and their derivatives are summarized,and the relationships between the structures and performance are unveiled in depth.Additionally,their applications in lithium–ion batteries,lithium–sulfur batteries,and supercapacitors are discussed.This review sheds light on the development of MOFs and their derivatives to realize excellent electrochemical performance.
基金Project supported by the National Natural Science Foundation of China(Grant No.51675423)
文摘It is widely accepted that the variation of ambient temperature has great influence on the battery model parameters and state-of-charge(SOC) estimation, and the accurate SOC estimation is a significant issue for developing the battery management system in electric vehicles. To address this problem, in this paper we propose an enhanced equivalent circuit model(ECM) considering the influence of different ambient temperatures on the open-circuit voltage for a lithium-ion battery. Based on this model, the exponential-function fitting method is adopted to identify the battery parameters according to the test data collected from the experimental platform. And then, the extended Kalman filter(EKF) algorithm is employed to estimate the battery SOC of this battery ECM. The performance of the proposed ECM is verified by using the test profiles of hybrid pulse power characterization(HPPC) and the standard US06 driving cycles(US06) at various ambient temperatures, and by comparing with the common ECM with a second-order resistance capacitor. The simulation and experimental results show that the enhanced battery ECM can improve the battery SOC estimation accuracy under different operating conditions.
