This paper aims to provide a structured review of aging mechanisms that aect the battery performance and also some of the most relevant algorithms that were used in the recent literature to predict the actual health of the battery. Finally, and based on the dierent approaches that were studied evaluation criteria are proposed to help judge the performance of State Of Health (SOH) estimation algorithm.
Résumé
Battery Management System (BMS) is an essential component for lithium-ion battery-based devices. It provides a variety of func-tionalities that help improve the overall lifespan of the battery, including states estimation algorithms. An accurate state of health is one of the essential features an advanced BMS provides, in order to track long term performance and ensure reliable operation of the battery. This paper aims to provide a structured review of ageing mechanisms that affect the battery performance and also some of the most relevant algorithms that were used in the recent literature to predict the actual health of the battery. Finally, and based on the different approaches that were studied evaluation criteria are proposed to help judge the performance of State Of Health (SOH) estimation algorithm.
Domaines
Automatique / Robotique
Origine : Fichiers produits par l'(les) auteur(s)
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