Elbows of Internal Resistance Rise Curves in Li-Ion Cells

Calum Strange, Shawn Li, Richard Gilchrist and Gonçalo dos Reis
Additional contact information
Calum Strange: School of Mathematics, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK
Shawn Li: School of Mathematics, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK
Richard Gilchrist: School of Mathematics, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK
Gonçalo dos Reis: School of Mathematics, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK

Energies, 2021, vol. 14, issue 4, 1-15

Abstract: The degradation of lithium-ion cells with respect to increases of internal resistance (IR) has negative implications for rapid charging protocols, thermal management and power output of cells. Despite this, IR receives much less attention than capacity degradation in Li-ion cell research. Building on recent developments on ‘knee’ identification for capacity degradation curves, we propose the new concepts of ‘elbow-point’ and ‘elbow-onset’ for IR rise curves, and a robust identification algorithm for those variables. We report on the relations between capacity’s knees, IR’s elbows and end of life for the large dataset of the study. We enhance our discussion with two applications. We use neural network techniques to build independent state of health capacity and IR predictor models achieving a mean absolute percentage error (MAPE) of 0.4% and 1.6%, respectively, and an overall root mean squared error below 0.0061 . A relevance vector machine, using the first 50 cycles of life data, is employed for the early prediction of elbow-points and elbow-onsets achieving a MAPE of 11.5% and 14.0%, respectively.

Keywords: elbow-points; early prediction; lithium-ion battery; internal resistance; parameter identification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/4/1206/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/4/1206/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:4:p:1206-:d:504387

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().