Growing Neural Gas-based Maximum Torque per Ampere (MTPA) Technique for SynRMs

Acetta, Angelo and Cirrincione, Maurizio and Di Piazza, Maria C. and La Tona, Giuseppe and Luna, Massimiliano and Pucci , Marcello (2020) Growing Neural Gas-based Maximum Torque per Ampere (MTPA) Technique for SynRMs. [Conference Proceedings]

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Abstract

This paper proposes a maximum torque per ampere (MTPA) technique specifically developed for Synchronous Reluctance Motors (SynRMs). The proposed MTPA is based on a self-organizing artificial neural network, called Growing Neural Gas (GNG). The GNG gas been trained in order to learn the real maximum torque per ampere points of the SynRM under test. The proposed MTPA has been tested experimentally on a suitably developed test set-up. The obtained experimental results clearly highlight a significant increase of maximum producible torque, with respect to the previously developed MTPA techniques.

Item Type:	Conference Proceedings
Additional Information:	DOI: 10.1109/ECCE44975.2020.9235713
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User:	Fulori Nainoca - Waqairagata
Date Deposited:	10 Dec 2020 04:48
Last Modified:	10 Dec 2020 04:48
URI:	https://repository.usp.ac.fj/id/eprint/12495

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