Paper Contents
Abstract
State of Charge (SoC) prediction for lithium-ion batteries indicates the amount of electrical energy available for usage by the drivers of the electric vehicle (EV). Understanding and accurately measuring SoC levels allows effective battery management. Charging infrastructure operates at its optimal point with known battery SoC levels, therefore increasing the optimal performance in various applications such as electric vehicles. A model was developed using simple battery equivalent circuits for prediction of the SoC using data analysis predictive tools. The limitations on SoC prediction using this methodology using the ratio of the remaining capacity of the battery after use to its rated nominal capacity was revised to reflect the actual SoC remaining based on aging factors. Advantages in accurate SoC estimation were drawn from its help in managing the device usage plans, enabling battery management systems for optimal usage, contributing to the overall health of the battery, and improving the safety of users. Past literature recorded many factors (temperature, current load, age, and self-discharge), but limited information is available on improved life from varying battery chemistry.
Copyright
Copyright © 2025 Vineet Kumar. This is an open access article distributed under the Creative Commons Attribution License.
