Dynamic to Static Model Comparison and Hybrid Metaheuristic Optimization in Induction Motor Parameter Estimation

• DOI: 10.3390/electronics14030524
• Publication Date: 2025-01-28T12:54:08Z
• Authors: Nelson H. B. Santana; Imene Yahyaoui; Flavio D. C. Oliv...; Arthur E. A. Amorim; Domingos S. L. Si...; Helder R. O. Rocha

This paper presents a comprehensive study of parameter estimation for three-phase induction motors (IMs) using hybrid optimization methods and comparative evaluation static dynamic modeling approaches. A metaheuristic combining the Sine Cosine Algorithm (SCA) Particle Swarm Optimization (PSO) is developed to identify optimal motor parameters efficiently. The approach utilizes model rapid estimation, with final values validated against ensure accuracy in operational predictions. Results confirm that provides robust estimates key performance metrics, including torque, power factor, current, aligning well experimental results from real-motor no-load tests. Parameters estimated by proposed method demonstrate high adherence real measurements. Comparisons also reveal limitations models scenarios requiring state-space accuracy, such as observer-based control applications. concludes recommending further exploration alternative structures algorithm estimation.