Aplicación del algoritmo de optimización por senos y cosenos al problema de estimación paramétrica en motores de inducción trifásicos

Abstract

The steady-state analysis of electrical machines requires a detailed characterization of the equivalente electrical circuit, which adequately represents the interaction and transformation between electrical energy and mechanical energy within them. This research aims to characterize the equivalent circuit of triphasic induction motors by minimizing the mean square error between the measured and calculated toque variables. These torques are obtained from data provided by the manufacturer, including starting, peak, and full-load torques. A metaheuristic optimization technique is applied to solve the resulting nonlinear programming model based on the interactions between the sine and cosine functions. The numerical results obtained with this algorithm demonstrate its efficiency in terms of response quality, reaching objective functions with values less than 1 × 10−8 regarding the measured and calculated variables. The simulación results in two test systems allow us to conclude that the parametric estimation problem in three-phase induction motors is part of the multimodal optimization problems. This implies a potentially infinite set of solutions that minimize the root mean square error and adequately represent the behavior of the motores output torque under various probable operating conditions.