Lithium-ion batteries modeling and state of charge estimation using artificial neural network
| Main Authors: | Younes Boujoudar, Hassan Elmoussaoui, Tijani Lamhamdi |
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| Format: | Article Journal |
| Terbitan: |
, 2019
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4061062 |
Daftar Isi:
- In this paper, we propose an effective and online technique for modeling of Li-ion battery and estimation of State of Charge (SoC). Based on Feed Forward Neural Networks (FFNN) and Nonlinear Auto Regressive model with eXogenous input (NARX). The both Artificial Neural Network (ANN) are trained offline using the data collected from the experimental data. The NARX network finds the require battery votage in the FFNN network to estimate SoC. The proposed method is implemented on a Li-Ion battery cell and the results of simulation show a good accuracy and fast convergence of the proposed method.