Data: State-of-health estimation of lithium-ion batteries subjected to different ageing conditions via electrochemical impedance spectroscopy and machine learning

Ezeoba, Emmanuel Onyeka; Stahl, Gereon Karsten; Celik, Sehriban; Sauer, Dirk Uwe

doi:10.18154/RWTH-2026-10225

Data: State-of-health estimation of lithium-ion batteries subjected to different ageing conditions via electrochemical impedance spectroscopy and machine learning

Ezeoba, Emmanuel Onyeka^RWTH* ; Celik, Sehriban^RWTH* ; Stahl, Gereon Karsten^RWTH* ; Sauer, Dirk Uwe^RWTH*

2026

Online
DOI: 10.18154/RWTH-2026-10225
URL: https://publications.rwth-aachen.de/record/1045352/files/EIS_measurement_data.zip
URL: https://publications.rwth-aachen.de/record/1045352/files/Data_description.pdf

Einrichtungen

Projekte

BMBF 03XP0389E - DAFODIL - Datenbasierte Fertigungsoptimierung von Batteriezellen auf Basis von End-of-line-Daten durch massiven Einsatz von Machine Learning-Algorithmen und inline Analytik (03XP0389E) (03XP0389E)

Inhaltliche Beschreibung (Schlagwörter)
Li-ion battery (frei) ; state-of-health (frei) ; equivalent circuit model (frei) ; electrochemical impedance spectroscopy (frei)

Kurzfassung
This dataset includes raw data files from electrochemical impedance spectroscopy (EIS) measurements and electrical cycling data under different temperature, current rate, and rest-time conditions for a 1 Ah NMC622-graphite lithium-ion battery cell. For further details, please refer to the attached document "Data_description.pdf."

OpenAccess:
ZIP
PDF
(zusätzliche Dateien)