Abstract
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.
Funder
Holistic approach to EneRgy-efficient smart nanOGRIDS—HEROGRIDS
FARB funds of the University of Salerno
French National Research Agency
Subject
Electrical and Electronic Engineering,Electrochemistry,Energy Engineering and Power Technology
Cited by
1 articles.
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