State of health estimation of lithium-ion batteries based on regression techniques

Lithium-ion batteries present the energy source for many industrial applications such as telecommunication, robotic, informatics... Consequently, the monitoring of these assets is considered as primordial to minimize unexpected electricity outage and thereby to ensure the effective operation of the used machines. In this sense, this paper presents a comparison of various regression techniques for modeling batteries degradations. Indeed, a rich discussion is introduced to enhance the benefits of regression techniques and to highlight the challenges still untreated by the literature in this important area. This paper begins with a literature review with experimental and numerical applications of regression techniques and it ends by highlighting the new industrial challenges.