@inproceedings{ed6d2c8453ee40b381d0af7ed6ae80f0,
title = "Asymptotically Stable Discrete-Time Observer for State-of-Charge Estimation",
abstract = "State-of-charge is an important variable in a battery management system. However, it cannot be measured directly from a battery. Instead, it is estimated from measurable variables like current and voltage. This paper addresses a discrete-time observer-based SOC estimation such that it has an asymptotic stability guarantee with some assumptions. The second-order equivalent circuit model and a piecewise linear approximation representing a relationship between the state-of-charge and the open circuit voltage are utilized. Simulations are conducted in Python to evaluate the designed observer. Some simulation scenarios also include the appearance of the model uncertainty, disturbance, and measurement noise. The estimated state-of-charge can track the real one for these situations, despite performance degradation.",
keywords = "Discrete-time, Lithium-ion, Lyapunov stability, Observer, State-of-Charge",
author = "Harry Septanto and Edi Kurniawan and Prakosa, \{Jalu Ahmad\} and Samsul Hafiz and \{Surya Atman\}, \{Made Widhi\} and Oetomo Sudjana",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation ; Conference date: 14-11-2023 Through 15-11-2023",
year = "2023",
doi = "10.1109/ICAMIMIA60881.2023.10427837",
language = "English",
series = "2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings",
publisher = "IEEE",
pages = "183--188",
booktitle = "2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings",
address = "United States",
}