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Communication Dans Un Congrès Année : 2023

Onto-SoC: An ontology-based approach to battery pack SoC estimation

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A critical aspect of managing lithium-ion battery packs in electric vehicle applications is accurately determining the State of Charge (SoC). There are several methods available to estimate it, including coulomb counting with direct evaluation, Open circuit voltage, kalman filter with adaptive approach, particle flter, as well as fuzzy logic and data-based approach. In this paper, we use the state of charge data already computed by a data-driven approach and combine it with an ontology of a battery pack. The built ontology models the battery pack, taking into account the topology, types of cells and their organization inside. To make an exact estimation, different strategies of balance control of the cells are considered. SWRL rules are used to compute the state of charge of the whole battery pack. Matlab Simulink multi-physics model of a lithium-ion battery is used to provide simulated data for the experiments. The given model is evaluated based on regression metrics showing its performance.
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hal-04236470 , version 1 (08-07-2024)

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Ala Eddine Hamouni, Franco Giustozzi, Ahmed Samet, Ali Ayadi, Slimane Arbaoui, et al.. Onto-SoC: An ontology-based approach to battery pack SoC estimation. 27th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES 2023), Sep 2023, Athènes, Greece. pp.2254-2263, ⟨10.1016/j.procs.2023.10.216⟩. ⟨hal-04236470⟩
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