With the advent of the fourth (4th) industrial revolution, energy needs are increasing. For this revolution which is expected to improve the quality of human lives to succeed – energy that is reliable, affordable and sustainable is a sine qua non. At the heart of energy storage are electrochemical devices of which batteries are key. However, batteries require monitoring in order to accurately estimate the states of charge (SOC) and health (SOH).

To effectively monitor SOC and SOH – there is a need to develop smart models which can accurately track and capture battery dynamic and static characteristics.

Two main classes of models are used in battery modeling are electrochemical and electrical models (equivalent circuit models, ECMs). The electrochemical models tend to be accurate but computationally expensive. They have also been reported as impractical for online usage. The reverse happens with ECMs but they are much less accurate.

This paper reviews models reported in previous works for Lithium-ion battery SOC & SOH estimation in battery management systems (BMS). Comparison is made of ELECTROCHEMICAL models as well as ECMs on the Lithium-ion batteries. This gives a working overview of how practical smart-battery models can be developed. This is in order to track accurately parameters such as film resistance and diffusion coefficients etc which are beneficial for accurate SOC and SOH estimation.