Major
Computer Engineering
Anticipated Graduation Year
2023
Access Type
Open Access
Abstract
In this paper, we investigate the state of charge (SoC) estimation of Lithium-Ion batteries using an extended Kalman filter, and an unscented Kalman filter. The results show that both perform well with battery management systems in power grids, with the unscented Kalman filter providing a more accurate estimation of the SoC.
Faculty Mentors & Instructors
Brook Abegaz, Assisstant Professor, Computer Engineering
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
Design of a State-Predictive and Robust Control of Energy Storage Units for Smart Power Grids
In this paper, we investigate the state of charge (SoC) estimation of Lithium-Ion batteries using an extended Kalman filter, and an unscented Kalman filter. The results show that both perform well with battery management systems in power grids, with the unscented Kalman filter providing a more accurate estimation of the SoC.