Cargando…

A study of the influence of measurement timescale on internal resistance characterisation methodologies for lithium-ion cells

The power capability of a lithium ion battery is governed by its resistance, which changes with battery state such as temperature, state of charge, and state of health. Characterizing resistance, therefore, is integral in defining battery operational boundaries, estimating its performance and tracki...

Descripción completa

Detalles Bibliográficos
Autores principales: Barai, Anup, Uddin, Kotub, Widanage, W. D., McGordon, Andrew, Jennings, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5758786/
https://www.ncbi.nlm.nih.gov/pubmed/29311666
http://dx.doi.org/10.1038/s41598-017-18424-5
Descripción
Sumario:The power capability of a lithium ion battery is governed by its resistance, which changes with battery state such as temperature, state of charge, and state of health. Characterizing resistance, therefore, is integral in defining battery operational boundaries, estimating its performance and tracking its state of health. There are many techniques that have been employed for estimating the resistance of a battery, these include: using DC pulse current signals such as pulse power tests or Hybrid Pulse Power Characterization (HPPC) tests; using AC current signals, i.e., electrochemical impedance spectroscopy (EIS) and using pulse-multisine measurements. From existing literature, these techniques are perceived to yield differing values of resistance. In this work, we apply these techniques to 20 Ah LiFePO(4)/C(6) pouch cells and use the results to compare the techniques. The results indicate that the computed resistance is strongly dependent on the timescales of the technique employed and that when timescales match, the resistances derived via different techniques align. Furthermore, given that EIS is a perturbative characterisation technique, employing a spectrum of perturbation frequencies, we show that the resistance estimated from any technique can be identified – to a high level of confidence – from EIS by matching their timescales.