This contribution addresses the rotor design process of a Permanent Magnet-assisted Synchronous Reluctance Machine by adopting a multi-physics and multi-objective optimization algorithm. A Finite Element (FE) approach is employed to determine the electromagnetic and structural responses during the optimization. In particular, a detailed FE structural modeling is used, which often is based on simplifications and inaccuracies in the available literature. A genetic algorithm is adopted, with the objectives being the maximization of the mean torque, the minimization of the torque ripple and the minimization of the stress in the rotor. A parametric analysis of the geometric features precedes the optimization to establish the design variables which mostly affect the machine performance, and thus to reduce the computational cost of the optimization. The presented methodology consists of a useful tool for the final stages of the design process, and provides a rotor with a torque ripple reduced by 15.1% compared to an existing design used as a benchmark, while the mean torque and the maximum stress remain the same as the original configuration.

Multi-physics and multi-objective optimization of a permanent magnet-assisted synchronous reluctance machine for traction applications / Puglisi, Francesco; Barbieri, SAVERIO GIULIO; Mantovani, Sara; Devito, Giampaolo; Nuzzo, Stefano. - In: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS. PART C, JOURNAL OF MECHANICAL ENGINEERING SCIENCE. - ISSN 0954-4062. - (2024), pp. N/A-N/A. [10.1177/09544062241240888]

Multi-physics and multi-objective optimization of a permanent magnet-assisted synchronous reluctance machine for traction applications

Francesco Puglisi;Saverio Giulio Barbieri;Sara Mantovani
;
Giampaolo Devito;Stefano Nuzzo
2024

Abstract

This contribution addresses the rotor design process of a Permanent Magnet-assisted Synchronous Reluctance Machine by adopting a multi-physics and multi-objective optimization algorithm. A Finite Element (FE) approach is employed to determine the electromagnetic and structural responses during the optimization. In particular, a detailed FE structural modeling is used, which often is based on simplifications and inaccuracies in the available literature. A genetic algorithm is adopted, with the objectives being the maximization of the mean torque, the minimization of the torque ripple and the minimization of the stress in the rotor. A parametric analysis of the geometric features precedes the optimization to establish the design variables which mostly affect the machine performance, and thus to reduce the computational cost of the optimization. The presented methodology consists of a useful tool for the final stages of the design process, and provides a rotor with a torque ripple reduced by 15.1% compared to an existing design used as a benchmark, while the mean torque and the maximum stress remain the same as the original configuration.
2024
N/A
N/A
Multi-physics and multi-objective optimization of a permanent magnet-assisted synchronous reluctance machine for traction applications / Puglisi, Francesco; Barbieri, SAVERIO GIULIO; Mantovani, Sara; Devito, Giampaolo; Nuzzo, Stefano. - In: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS. PART C, JOURNAL OF MECHANICAL ENGINEERING SCIENCE. - ISSN 0954-4062. - (2024), pp. N/A-N/A. [10.1177/09544062241240888]
Puglisi, Francesco; Barbieri, SAVERIO GIULIO; Mantovani, Sara; Devito, Giampaolo; Nuzzo, Stefano
File in questo prodotto:
File Dimensione Formato  
__pub41_2024_FPuglisi_Multi-physics-and-multi-objective-optimization-of-a-permanent-magnet-assisted-synchronous-reluctance.pdf

Accesso riservato

Descrizione: Documento principale
Tipologia: Versione pubblicata dall'editore
Dimensione 4.26 MB
Formato Adobe PDF
4.26 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1335626
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact