Direct current internal resistance decomposition model for accurate parameters acquisition and application in commercial high voltage LiCoO2 battery

Ren-ping, XU; Wang, Ding; Duan, Jianguo; Guo, Huajun; Wang, Jiexi; Wang, Zhixing; Li, Xinhai; Li, Guangchao

doi:10.1016/j.est.2023.108100

Cited by 6 publications

(1 citation statement)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Experimental tests involve the application of known inputs to the battery and measurement of its responses. These data are then fitted to appropriate mathematical models to extract the relevant parameters [89,90]. However, since temperature and aging can impact the cell's behaviour, some approaches adapt the measured data to these two factors.…”

Section: Parametersmentioning

confidence: 99%

Modelling and Estimation in Lithium-Ion Batteries: A Literature Review

Martí-Florences,

Cecilia,

Costa-Castelló

2023

Energies

View full text Add to dashboard Cite

Lithium-ion batteries are widely recognised as the leading technology for electrochemical energy storage. Their applications in the automotive industry and integration with renewable energy grids highlight their current significance and anticipate their substantial future impact. However, battery management systems, which are in charge of the monitoring and control of batteries, need to consider several states, like the state of charge and the state of health, which cannot be directly measured. To estimate these indicators, algorithms utilising mathematical models of the battery and basic measurements like voltage, current or temperature are employed. This review focuses on a comprehensive examination of various models, from complex but close to the physicochemical phenomena to computationally simpler but ignorant of the physics; the estimation problem and a formal basis for the development of algorithms; and algorithms used in Li-ion battery monitoring. The objective is to provide a practical guide that elucidates the different models and helps to navigate the different existing estimation techniques, simplifying the process for the development of new Li-ion battery applications.

show abstract

Section: Parametersmentioning

confidence: 99%

Modelling and Estimation in Lithium-Ion Batteries: A Literature Review

Martí-Florences,

Cecilia,

Costa-Castelló

2023

Energies

View full text Add to dashboard Cite

show abstract

Three‐Dimensional Self‐Supported Ge Anode for Advanced Lithium‐Ion Batteries

Fang,

Jiang,

Yue

et al. 2024

Chemistry A European J

View full text Add to dashboard Cite

Three‐dimensional (3D) self‐supported Ge anode is one of the promising candidates to replace the traditional graphite anode material for high‐performance binder‐free lithium‐ion batteries (LIBs). The enlarged surface area and the shorted ions/electrons transporting path length of the 3D electrode would greatly facilitate the rapid transfer of abundant lithium ions during cycling, thus achieve enhanced energy and power density during cycling. Cycle stability of the 3D self‐supported Ge electrode would also be improved due to the obtained enough space could effectively accommodate the large volume expansion of the Ge anode. In this review, we first describe the electrochemical properties and Li ions storage mechanism of Ge anode. Moreover, the recent advances in the 3D self‐supported Ge anode architectures design are majorly illustrated and discussed. Challenges and prospects of the 3D self‐supported Ge electrode are finally provided, which shed light on ways to design more reliable 3D Ge‐based electrodes in energy storage systems.

show abstract

Can Electrochemical Impedance Spectroscopy be Replaced by Direct Current Techniques in Battery Diagnosis?

Guo,

Xu,

et al. 2024

ChemPhysChem

View full text Add to dashboard Cite

Electrochemical impedance spectroscopy (EIS), a conventional and alternating‐current‐(AC)‐based technique for impedance measurement, is commonly used in battery diagnosis. However, it requires expensive equipment and demanding operating conditions and is complex and model‐dependent in data analysis. Recently, novel direct current (DC) analytics have emerged as an alternative to EIS. They are simple yet powerful, being capable of revealing impedance information that traditionally could only be obtained through EIS and determining Li‐ion diffusion coefficient. Besides, a complete EIS spectrum can be predicted based on constant current charging curves in the support of machine learning methods. This work highlights the similarities and discrepancies between DC techniques and EIS in the electrochemical analysis of Liion batteries. Looking ahead, DC techniques may be a promising substitute for EIS in future battery diagnosis, requiring simplified equipment while offering a deep understanding of battery impedance and its underlying electrochemical processes.

show abstract

Direct current internal resistance decomposition model for accurate parameters acquisition and application in commercial high voltage LiCoO2 battery

Cited by 6 publications

References 43 publications

Modelling and Estimation in Lithium-Ion Batteries: A Literature Review

Modelling and Estimation in Lithium-Ion Batteries: A Literature Review

Three‐Dimensional Self‐Supported Ge Anode for Advanced Lithium‐Ion Batteries

Can Electrochemical Impedance Spectroscopy be Replaced by Direct Current Techniques in Battery Diagnosis?

Contact Info

Product

Resources

About