Flux Linkage Model Optimization using Binary Coded Genetic Algorithm for Switched Reluctance Motor

Abstract

As of late, many researchers have shown a tremendous structure. Harmonics of these normal forces will resonate the surge of interest in the field of switched reluctance motor. A natural frequency resonant modes of the stator structure, precise model of switched reluctance motor will even boost the producing excessive amount of acoustic [1]. The mechanical work time of this research progression as well as attract more design can be optimize to avoid significant resonance at researchers into this area. The phases of switched reluctance common operating points over the speed range of the motor. motor are approximately identical to each other with appropriate Supplementary, the phase energizing can be modified to reduce shift between them; hence most modeling will only concentrate the frequency components of the normal forces. on one selected phase of the drive. The flux linkage-current relationship is very much represented by function of rotor The performance and efficiency of the motor drive is position with taking account of the magnetic characteristic; this reduced, as it needs a rotor-positioning sensor to control the makes the modeling to be a more challenging task In this paper SRM other than an electronic power converter for maneuver we compare two existing models of flux linkage current purpose. This will introduce additional cost to the motor but at derivationthe optimization of measured flux using measured overall the cost of SRM motor will still be lower compared to values and the estimation of flux via the Binary Coded Genetic induction and dc motors. Algorithm (BCGA).