A Comparative Performance Analysis for loss Minimization of Induction Motor Drive Based on Soft Computing Techniques

摘要

This paper presents a comparative performance assessment for loss minimization of vector controlled induction motor (IM) drive based on three different efficient optimization algorithms, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Golden Search (GS). The present work deals with the recalculation of optimized flux component of current based on the mentioned techniques, for a better optimal efficiency operation of the IM drive. All the three algorithms based IM drive operation show improvement in efficiency by reduction in the core loss of the drive system. However, it is PSO based IM drive operation that has the advantages of fast response and high accuracy compared to other two schemes. The PSO based energy optimization scheme adaptively adjust the flux component of current to minimize the system loss Moreover, the three approaches have no effect on parameter variation and also need no additional hardware for hardware implementation. The simulation results for various speed patterns and operating conditions are presented here. Stability study of the whole drive system is also carried out utilizing the three optimizing schemes.