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Estimating the Health Status of Li-ion NMC Batteries From Energy Characteristics for EV Applications

Estimating the Health Status of Li-ion NMC Batteries From Energy Characteristics for EV Applications

Authors :
Hammou, Abdelilah
Petrone, Raffaele
Diallo, Demba
Gualous, Hamid
Source :
IEEE Transactions on Energy Conversion; September 2023, Vol. 38 Issue: 3 p2160-2168, 9p
Publication Year :
2023

Abstract

Capacity and Direct Current Internal Resistance are good health indicators for Li-ion batteries. But they cannot be measured. This work proposes to estimate these indicators from already available current and voltage measurements. The estimators are based on third-order polynomials and energy features extracted during partial discharge and different depths of discharge under a dynamic profile (World harmonized Light vehicles Test Cycles). The estimations are validated with experimental measurements obtained from cycling three Lithium-Nickel-Manganese-Cobalt-Oxide/Graphite cells at a controlled temperature. The mean relative error for the Direct Current Internal Resistance estimation is less than 5% when the depth of discharge lies between 25% and 40%. It is lower than 2% for the capacity estimation. The method is simple and suitable for embedded battery monitoring as it uses already available voltage and current measurements.

Details

Language :
English
ISSN :
08858969 and 15580059
Volume :
38
Issue :
3
Database :
Supplemental Index
Journal :
IEEE Transactions on Energy Conversion
Publication Type :
Periodical
Accession number :
ejs63809257
Full Text :
https://doi.org/10.1109/TEC.2023.3259744