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Batteries have been widely used for energy storage in various fields. Renewable energy systems, such as solar cells and wind turbines, produce energy depending on the weather. Because of that, batteries are needed in these fields to ensure energy availability. Electric vehicles also rely on batteries for energy storages. Therefore, the failure of battery management can result in large losses in various aspects. To prevent this, a number of studies on State of Health (SoH) of battery have been carried out. Prediction and estimation of SoH have been carried out using several methods such as SVM, deep learning, random forest and others. In many cases, these methods are applied by assuming that the change in SoH is a linear or non-linear phenomenon. However, in this paper, it is found that SoH exhibits chaotic behavior. Several well known methods to illustrate the Mackey-Glass Equation method and Lyapunov Exponent are considered to identify the chaotic nature of SoH. The obtained results can provide a new understanding of SoH behaviors on batteries, especially for the development of battery management system, control and safety system.