2026-04-07T13:34:19Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/68232026-04-01T07:34:10Zcom_20.500.11984_1143col_20.500.11984_1148

00925njm 22002777a 4500 dc Fernandez Gonzalez, Sergio author Lopetegi Tapia, Iker author Oca, Laura author Yeregui, Josu author GARAYALDE, ERIK author IRAOLA, UNAI author 2024 Battery ageing is one of the main concerns in most battery applications. To reduce this degradation rate, it is key to understand how batteries age. However, the diagnosis of battery ageing is very challenging due to the little information that can be obtained without disassembling the battery cells. This paper presents a tool for battery degradation diagnosis. By a multi-objective optimisation algorithm, the tool estimates three degradation modes that lead to capacity fade: the loss of active material (LAM) of each electrode, and the loss of lithium inventory (LLI). The stepwise methodology tool is exposed and proved on three different degradation scenarios and battery cell chemistries. Two of the scenarios were simulated using a physics-based model (PBM), and the other scenario was obtained from an experimental degradation study. The results demonstrate accuracy and robustness of the tool while offering great simplicity and intuitiveness compared to other tools reported in the literature. 979-8-3503-6444-6 https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=178705 https://hdl.handle.net/20.500.11984/6823 Degradation Modes Battery aging Open-circuit-potential Differential voltage analysis ODS 7 Energía asequible y no contaminante ODS 12 Producción y consumo responsables ODS 13 Acción por el clima Intuitive Degradation Mode Estimation Tool: ModEst