Document Type : Research article
Authors
1 Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran
2 Nuclear Fuel Cycle Research School, Nuclear Science and Technology Research Institute (NSTRI), Tehran, Iran
Abstract
This paper explores the impact of two types of experiments, known as "long pulse" and "short pulse," experiments, on identifying models for Lithium-ion batteries. The focus is on improving the estimation of the state of charge (SoC) using an extended Kalman filter. The results consistently demonstrate that applying the extended Kalman filter to models identified through long pulse experiments outperforms those identified through short pulse experiments in estimating battery SoC and terminal voltage. The article delves into the reasons for this improvement from both circuit and electrochemical perspectives, providing insights into the obtained results. Thus, the study advocates for the preference of long pulse strategies to enhance the performance of Lithium-ion batteries, offering insights that contribute to the development of innovative and sustainable energy storage solutions.
Highlights
- Long- and short-pulse effects on lithium-ion battery models are analyzed.
- It is proved that long-pulse models enhance SoC and voltage accuracy using EKF.
- Dual-cell model is used and computational efficiency and accuracy are optimized for real-time battery management.
- Circuit and electrochemical factors enhancing long pulse models' SoC estimation performance are analyzed.
- Further research on optimizing battery models with advanced techniques for diverse conditions is suggested.
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