Dead-times and switch voltage drops represent the most important sources of distortion of the (average) output voltage in PWM inverters. Their effect is a function of the parameters of the drive system and of the operating conditions, and is often intolerable in many drives applications, thus requiring a proper compensation strategy. Many techniques are implemented in industrial drives and reported in literature, even very recently. Differently from standard approaches the proposed methodology is based on a detailed physical model of the power converter (including output capacitance), described by a small set of parameters. A novel self-commissioning identification procedure is proposed, adopting Multiple Linear Regression. The technique is tested on a commercial drive in comparison to state-of-the-art techniques. Also back-EMF estimation improvements in a PMSM sensorless drive system are shown to provide additional validation of the method.

Self-commissioning of inverter dead-time compensation by multiple linear regression based on a physical model

Calligaro, S.;PETRELLA, Roberto
2014-01-01

Abstract

Dead-times and switch voltage drops represent the most important sources of distortion of the (average) output voltage in PWM inverters. Their effect is a function of the parameters of the drive system and of the operating conditions, and is often intolerable in many drives applications, thus requiring a proper compensation strategy. Many techniques are implemented in industrial drives and reported in literature, even very recently. Differently from standard approaches the proposed methodology is based on a detailed physical model of the power converter (including output capacitance), described by a small set of parameters. A novel self-commissioning identification procedure is proposed, adopting Multiple Linear Regression. The technique is tested on a commercial drive in comparison to state-of-the-art techniques. Also back-EMF estimation improvements in a PMSM sensorless drive system are shown to provide additional validation of the method.
2014
978-147995698-2
File in questo prodotto:
File Dimensione Formato  
06953400IEEExplore.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: Versione Editoriale (PDF)
Licenza: Non pubblico
Dimensione 1.26 MB
Formato Adobe PDF
1.26 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1064186
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 3
social impact