I. Introduction
Over the last decades, Li-ion batteries have become a key energy storage technology in many fields, including e-mobility applications [1]. Lithium based batteries are characterized by a high investment cost in comparison to other energy storage technologies (e.g., lead acid or nickel metal hydride batteries), due to their high energy density and overall performances. However, their performance is highly influenced by current, temperature, Charge/discharge rate (C-rate), and State-of-Charge (SoC) [2]. Therefore, accurate and reliable models of these batteries are needed, not only in the design phase, but also in the real operating conditions. For instance, being able to accurately predict the behavior of the battery voltage versus SoC, C-rate and temperature can allow the implementation of efficient battery management systems.