Efficient figureconverter fed PMBLDC motor using artificial neural network

1Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

In this paper, a new design of Bridgeless SEPIC (Single Ended Primary Inductance converter) with Artificial neural network (ANN) fed PMBLDC Motor drive is proposed to improve Power Factor. The proposed converter has single switching device of MOSFET, so the switching losses is reduced.ANN is used to achieve the higher power factor and fixed dc link voltage. Also the ANN methodology the time taken for computation is less since there is no mathematical model. The output voltage depends on the switching frequency of the MOSFET. The BLSEPIC act as a buck operation in continuous conduction mode. Detailed converter analysis, equivalent circuit and closed-loop analysis are presented for 36V, 120W, 1500rpm BLDC Motor drive. This proposed converter produces low conduction loss, low total harmonic reduction, low settling time and high power factor reaching near-unity. All the simulation work is verified with MATLAB – Simulink.

Cite

CITATION STYLE

APA

Meena Devi, R., & Premalatha, L. (2019). Efficient figureconverter fed PMBLDC motor using artificial neural network. International Journal of Electrical and Computer Engineering, 9(4), 3025–3031. https://doi.org/10.11591/ijece.v9i4.pp3025-3031

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free