FPGA-based space vector PWM with Artificial Neural Networks

Author

Osorio, John ; Ponce, Pedro ; Molina, Arturo

Author_Institution

Res. Dept., Tecnol. de Monterrey-ITESM, Mexico City, Mexico

fYear

2012

fDate

26-28 Sept. 2012

Firstpage

1

Lastpage

6

Abstract

This article presents the improvement of a PWM technique, called Space Vector PWM (SVPWM), using an Artificial Neural Network (ANN) to minimize the mathematic complexity involved with the SVPWM. The latter is a pulse-width modulation technique that is wide implemented to control AC electric motors. The results obtained from this research work will be used for further implementation of artificial intelligence techniques to control electric vehicle powertrains. Matlab is implemented for the ANN design and Labview for the FPGA programming and implementation.

Keywords

AC motors; electric vehicles; field programmable gate arrays; machine control; neural nets; power transmission (mechanical); pulse width modulation; AC electric motor control; ANN design; FPGA programming; FPGA-based space vector PWM; Labview; Matlab; PWM technique; SVPWM; artificial intelligence techniques; artificial neural networks; electric vehicle powertrain control; mathematical complexity; pulse-width modulation technique; Artificial neural networks; Field programmable gate arrays; Induction motors; Space vector pulse width modulation; Vectors; AC Motors; ANN; Artificial Intelligence; FPGA; SVPWM;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering, Computing Science and Automatic Control (CCE), 2012 9th International Conference on

Conference_Location

Mexico City

Print_ISBN

978-1-4673-2170-9

Type

conf

DOI

10.1109/ICEEE.2012.6421215

Filename

6421215