Taha AL RAFEI

Mr. Taha AL RAFEI


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 January 2023 in Batteries
Verified
Journal Article
Open access
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TRTaha AL RAFEI
Taha AL RAFEI
NSNadia Yousfi Steiner
Nadia Yousfi Steiner
DCDaniela Chrenko
Daniela Chrenko
The genetic algorithm (GA) is one of the most used methods to identify the parameters of Li-ion battery models. However, the parametrization of the GA method is not straightforward and can lead to poor accuracy and/or long calculation times. The Taguchi design method provides an approach to optimize GA parameters, achieving a good balance between accuracy and calculation time. The Taguchi design method is thus used to define the most adapted GA parameters to identify the parameters of model of Li-ion batteries for household applications based on static and dynamic tests in the time domain. The results show a good compromise between calculation time and accuracy (RMSE less than 0.6). This promising approach could be applied to other Li-ion battery applications, resulting from measurements in the frequency domain or different kinds of energy storage.