Abstract
This article, based on the state of charge (SoC) and state of health (SoH) of lithium-ion batteries, highlights the importance of these parameters for battery performance and durability. It explores advanced simulation methods, including intelligent algorithms. These methods are presented as essential tools for estimating and anticipating SoC and SoH, thus offering proactive management. It highlights the integration of these approaches into Li-ion battery management to support the ongoing development of electrical technologies and improve the sustainability of energy storage applications. This paper presents a description of the different SoC and SoH estimation methods. In addition to the use of the Kalman filter to establish a comparison between real and estimated SoC and the determination of SoH.
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