Otimização de TSF analíticas para SRMs via Algoritmo Enxame de Partículas e Plataforma HIL

Gustavo X. Prestes; Filipe P. Scalcon; Rodrigo P. Vieira

doi:10.20906/sbse.v2i1.3063

Gustavo X. Prestes PPGEE, Universidade de Santa Maria - RS
Filipe P. Scalcon McMaster Automotive Resource Center (MARC), McMaster University, Hamilton, ON L8P 0A6
Rodrigo P. Vieira PPGEE, Universidade de Santa Maria - RS

DOI: https://doi.org/10.20906/sbse.v2i1.3063

Keywords: Switched Reluctance Motor, Firing Angles, Torque Sharing Functions, Particle Swarm Optimization, Current Regulation

Abstract

This paper features a performance comparative study between analytical torque- sharing functions. The optimal conditions of Oon and Oov were obtained by particle swarm algorithm as method to drive optimization of three-phase switching reluctance motor. The aim is to assess the level of core losses and torque ripple in each TSF, as well as current controller performance in different speed conditions. In order to work out simulation process in less time, the non-linear model developed in Typhoon/Python environment was used to have real-time results.