Nowadays, the switched reluctance machine (SRM) is being given considerable attention from researchers due to the increasing demand for cost effective electrical machines in various sectors, especially renewable energy and electric mobility. Comparing to other electrical machines SRM exhibits various advantages in terms of cost and fault tolerance. Yet, the nonlinear behavior of SRM makes its modeling and identification an extremely challenging topic. Therefore, this study proposes a robust method for SRM modeling and parameters identification based on Hammerstein approach and frequency response analysis. Furthermore, to validate the identification results, a comparative analysis is performed against established techniques such as Finite Element Analysis (FEA) and the Recursive Least Squares (RLS). The results demonstrate that the proposed technique offers higher accuracy, computational efficiency, and practical applicability.