Critical Review of Ageing Mechanisms and State of Health Estimation Methods for Battery Performance

K Saqli (1) , H Bouchareb (1) , M Oudghiri (1) , N. M'Sirdi (2)

1 USMBA - Université Sidi Mohamed Ben Abdellah
2 LIS - Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon)

Battery Management System (BMS) is an essential component for lithium-ion battery-based devices. It provides a variety of functionalities that help to 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, 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

K Saqli, H Bouchareb, M Oudghiri, N. M'Sirdi. Critical Review of Ageing Mechanisms and State of Health Estimation Methods for Battery Performance. John Littlewood; Robert J. Howlett; Alfonso Capozzoli; Lakhmi C. Jain. Sustainability in Energy and Buildings. Proceedings of SEB 2019, 163, Springer, pp.506-518, 2019, Smart Innovation, Systems and Technologies, ⟨10.1007/978-981-32-9868-2_43⟩. ⟨hal-02480269⟩