Effective Battery Management System considering Intelligent SoC estimation for Li-ion battery

This paper provides a sophisticated Battery Management system (BMS) framework that involves smart State of Charge (SoC) estimation for Li-ion batteries only using simulation studies. Its practical application is particularly noted to be in dynamic environments like electric vehicles and underwater systems. The research discussed explores different modeling approaches. In this case, two kinds of models have been addressed: electrochemical models and equivalent circuit models (1RC and 2RC). While the former has high fidelity, computational intensity restricts its applicability for real-time applications. On the contrary, the 2RC equivalent circuit model balances computational efficiency with accuracy and captures dynamic responses such as polarization effects. MATLAB simulations validate the models under varying temperature and pressure conditions. The results highlight the 2RC model as the optimal choice for real-time battery monitoring. Future work will focus on enhancing thermal modeling and integrating advanced thermal management systems to improve battery performance in practical scenarios.