Battery Aging Models Based on High-Current Incremental Capacity in Fast Charging

Ludovico Lombardi (1) , Brian Ospina Agudelo (1) , Walter Zamboni (1) , Eric Monmasson (2)

1 DIEM / UNISA - Dipartimento di Ingegneria dell'Informazione ed Elettrica e Matematica Applicata
2 SATIE - Systèmes et Applications des Technologies de l'Information et de l'Energie

This paper presents battery aging models based on high-current incremental capacity features in the presence of battery cycling profiles characterized by fast charging conditions. In particular, the main peak area under the incremental capacity graph is proposed as a capacity indicator. A dataset from the Toyota Research Institute is analyzed. Batteries’ cycling data are characterized by various single- or double-step fast charges in constant current to reach 80% of the battery state of charge; the remaining charge process is performed by a 1C charge. Depending on the battery, a linear or logarithmic model was identified as the best suitable for representing the capacity–peak area relationship. The generalization capabilities of the proposed models are evaluated by performing an inference analysis of the fitting results over groups of batteries. Finally, we evaluated the prediction performance of the models by adopting a cross-validation approach.

Mots clés: battery aging modeling; capacity degradation models; fast charging; incremental capacity; state-of-health; battery aging modeling capacity degradation models fast charging incremental capacity state-of-health; battery aging modeling

Domaines: Sciences de l'ingénieur [physics]; Matériaux; Mécanique [physics.med-ph]; Energie électrique

Ludovico Lombardi, Brian Ospina Agudelo, Walter Zamboni, Eric Monmasson. Battery Aging Models Based on High-Current Incremental Capacity in Fast Charging. Batteries, 2023, 9 (1), pp.1-15. ⟨10.3390/batteries9010002⟩. ⟨hal-04088247⟩