State of Charge Estimation for a Lithium-Ion Battery Pack

Energy storage systems are becoming more and more widespread. The newest use case is in the power and energy sector, which is increasingly looking towards energy storage as a solution to speed up its shift to renewables while ensuring maximum supply at peak hours. The best-known example is the Tesla plant at Hornsdale, Australia, the largest battery storage system in the world currently. The boost in EV sales and its market share in developed nations demands effective, efficient, and safe battery management. One of the most important aspects of battery management is estimating the battery State of Charge (SOC). There are now a variety of ways for estimating the level of charge of a cell or a battery pack. Traditional approaches have been investigated, along with their shortcomings. Methods to counter sensor errors have been explored, the Kalman Filter, as well as the Extended Kalman Filter algorithm, have both been explored in detail particularly.