| Issue |
E3S Web Conf.
Volume 601, 2025
The 3rd International Conference on Energy and Green Computing (ICEGC’2024)
|
|
|---|---|---|
| Article Number | 00091 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202560100091 | |
| Published online | 16 January 2025 | |
A Comparative Study on State of Charge Estimation using EKF and IEKF
Laboratory Energy and Electrical Systems, National Higher School of Electricity and Mechanics, Hassan II University, Casablanca, Morocco
* Corresponding author: yassine.derouech.doc20@ensem.ac.ma
The nature of the “Portable Intelligent Micro Device for Hemodialysis” system requires a mobile electrical energy source capable of providing the essential power for efficient system operation. A battery with a management system can ensure this operation, the first target is to model the battery with a simple model capable of combining the various internal and external parameters that can affect battery behavior, then we develop the equations required to compose the two filters “Extended Kalman Filter” and “Invariant Extended Kalman Filter” in order to guarantee the estimation of the state of charge, which is a key element for the desired operation, and finally a MATLAB/Simulink simulation to compare the two filters, which reveals the IEKF filter’s performance in terms of stability and precision.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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