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Hystimator: DRT‐based hysteresis modelling for accurate SoC estimation in LFP battery cells.

Authors :
Thenaisie, Guillaume
Brivio, Claudio
Source :
IET Renewable Power Generation (Wiley-Blackwell); 2024 Suppl 1, Vol. 18, p4387-4398, 12p
Publication Year :
2024

Abstract

State of Charge (SoC) estimation for Lithium‐Iron Phosphate (LFP) batteries is challenging due to a flat Open Circuit Voltage (OCV) curve and a well‐known hysteresis effect. The authors built upon a previous study, which has shown that hysteresis in LFP is not an inherent characteristic but a very slow relaxation process when compared to other battery chemistries. Distribution of Relaxation Times (DRT) is used to deconvolve Electro‐Impedance Spectroscopy (EIS) measurements and model the hysteresis effect. The extracted DRT parameters show good agreement at low frequencies with previous thermodynamic studies in both fresh and aged cell conditions. The proposed model, called hystimator, integrates the hysteresis characteristics into a physics‐based Electro‐Chemical Model (ECM). The validation results show a significant reduction in the Root Mean Square Error (RMSE) during real‐world laboratory testing. This approach holds promise for SoC estimation in LFP battery cells, especially in embedded Battery Management System (BMS). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17521416
Volume :
18
Database :
Complementary Index
Journal :
IET Renewable Power Generation (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
181825336
Full Text :
https://doi.org/10.1049/rpg2.13130