The article addresses the modeling of the Li-ion cell and the establishment of model parameters. We adopt a Thevenin model that includes terms describing the nonlinear battery system such as state of charge (SOC), open-circuit voltage V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ocv</inf> , R <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> , R <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> , and C <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> . Subsequently, appropriate battery discharge tests are conducted and processed to identify the model parameters. Initially, we began by establishing the relationship between open-circuit voltage (V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ocv</inf> ) and state of charge (SOC) and the relationship between R <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> and SOC using the least squares method. Once these relationships were determined, we applied the least squares method again to determine the value of the time constant τ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> to deduce R <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> and C <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> . Once the different parameters were identified, model verification was established through experimental tests. The obtained error indicates that the mean absolute error (MAE) for modeling is 0.0062 V, and the root mean square error (RMSE) is 0.0094 V. This modeling method demonstrates high precision.
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Lagraoui et al. (2024) studied this question.
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