Batarya Elektriksel Eşdeǧer Devre Modeli Parametrelerinin Elde Edilmesinde Kullanilan Eǧri Uydurma Yöntemlerinin Karşilaştirilmasi

Lithium-ion battery chemistry has become the preferred choice in modern electrical energy storage systems. While it offers many advantages, its reactive nature can lead to hazardous situations. To prevent this, parameters such as voltage, current, temperature, and state of charge (SOC) must be monitored. In order to carry out this monitoring process, the battery's behavior needs to be mathematically modeled. For this purpose, parameters were determined for equivalent circuit models of varying degrees using different curve-fitting methods. These parameters were derived from test data of A123 Systems' ANR26650M1-B and Samsung's INR 18650 20R battery types. Models created through different curve-fitting methods were then compared with the test data. As a result of this study, a curvefitting method was identified that provides a fast, easy, and highly consistent equivalent circuit model.