This is the second part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the off-line identification of its parameters. The first part has treated the theoretical framework of the model. This second part is devoted to the description of an identification technique which has been suitably developed for the estimation of the parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses, described in the first part of the paper. Such an identification technique is strictly related to the state formulation of the proposed model and exploits Genetic Algorithms (GA) for minimizing a suitable cost function. The proposed dynamic model and its related parameters estimation technique have been validated comparing its results with those obtainable experimentally on a suitably developed test set-up as well as with those obtainable by a Finite Element Analysis (FEA) model of the LIM.

State Space-Vector Model of Linear Induction Motors Including Iron Losses: Part II: Model Identification and Results

Accetta;Angelo;Marcello;
2018

Abstract

This is the second part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the off-line identification of its parameters. The first part has treated the theoretical framework of the model. This second part is devoted to the description of an identification technique which has been suitably developed for the estimation of the parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses, described in the first part of the paper. Such an identification technique is strictly related to the state formulation of the proposed model and exploits Genetic Algorithms (GA) for minimizing a suitable cost function. The proposed dynamic model and its related parameters estimation technique have been validated comparing its results with those obtainable experimentally on a suitably developed test set-up as well as with those obtainable by a Finite Element Analysis (FEA) model of the LIM.
2018
Istituto di iNgegneria del Mare - INM (ex INSEAN)
Inglese
IEEE Energy Conversion Congress and Expo 2018 (ECCE 18), 23-27 September 2018, Portland, USA
2018
3190
3197
8
978-1-4799-7312-5
IEEE
New York
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
23-27 September 2018
Portland, USA
Linear Induction Motor (LIM)
End-effects
Space-vector
State Model
vedi anche ID 411246
2
none
Accetta; Angelo; Cirrincione; Maurizio Pucci; Marcello ; Sferlazza Antonino
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/394149
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