Parameter Estimation of Induction Motor with Bioinspired Algorithms

The identification of induction motor (IM) parameters is crucial for developing accurate models that simulate IM behavior under various conditions. This, in turn, facilitates the optimal design of control systems, early fault diagnosis, and predictive maintenance. Additionally, accurate parameter identification enables the implementation of energy efficiency strategies, reducing consumption and optimizing IM performance. This review article will analyze and elaborate on bioinspired optimization-based methods that have been widely employed in the parameter estimation of IMs.