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Lithium-Ion batteries modeling using NARX Nonlinear model
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DOI：10.1109/wits.2019.8723705.png)
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Abstract
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In this paper, we propose an effective technique for modeling of Lithium Ion (Li-Ion) batteries using Nonlinear Auto Regressive model with eXogenous input (NARX). The Artificial Neural Network (ANN) are trained employing the data collected from the battery testing process. The NARX network find the request battery model, where the input variables are the battery terminal voltage, SoC at the previous sample, and the current, temperature at the present sample. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in Matlab/Simulink show a good accuracy of proposed model.
Keywords:
Lithium-Ion
battery
modeling
SoC
ANN
NARX
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