Genetic Algorithm and Taguchi Method: An Approach for Better Li-Ion Cell Model Parameter Identification

Abstract

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.