Switched Reluctance Motor (SRM), built using revolutionary concept, has highly nonlinear flux-linkage characteristics depending heavily on phase current and rotor position. A good mathematical model for these characteristics would help to understand the workings of the motor; thus providing path for better control algorithms and motor designs. It is very much proven by many researchers in this area, that a straightforward simple mathematical model has never satisfied the complete overall characteristics. Moreover, there is no distinct guideline about what sort of mathematical model would be suitable. To overcome this problem, a self-organizing polynomial neural network is proposed in this paper. In this scheme, without any prior knowledge of the mathematical model, the model is evolved iteratively and progressively. The simulation test results verify the effectiveness of this approach.
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).
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