Minimización del error en la estimación de parámetros eléctricos de motores de inducción trifásicos usando un algoritmo de distribución exponencial

Abstract

This work presents a detailed study on minimizing error in the estimation of electrical parameters of three-phase induction motors, based on the Exponential Distribution Optimization Algorithm (EDO), which is founded on the statistical properties of the exponential distribution, such as the lack of memory and its exploration and exploitation phases. The content covers the mathematical modeling of the motors equivalent circuit under a least-squares approach. The methodology was validated using test scenarios involving two motors, in which EDO demonstrated superior accuracy compared to traditional techniques such as genetic algorithms and particle swarm optimization. In conclusion, this work provides a robust and efficient solution for motor analysis and diagnosis, facilitating its application in predictive maintenance strategies and advanced control in industrial contexts.