This article focuses on the magnetic field analysis of cryogenic permanent magnet synchronous motor (CPMSM). It develops a rhombic magnetic permeability-based equivalent magnetic network (EMN) model. This model is used to calculate the magnetic field in the air-gap region. Considering the variation of motor electromagnetic parameters at low temperatures, a grid-boundary magnetic permeability parameter reconstruction method is proposed. This method redistributes magnetic permeability parameters to improve their accuracy and, combined with the magnetic network, establishes the permeance reconstruction magnetic network (PRMN) model. Additionally, a modular assignment method is introduced in the rotor grid region for dynamic solution calculation. This method eliminates the need for remodeling at different time instances, reducing time costs and enhancing modeling efficiency. Compared with the EMN model and the finite element analysis (FEA), the proposed PRMN model combines the advantages of fast calculation speed of EMN model and the high accuracy close to FEA. Finally, experiments verify that the calculated results from the PRMN model show good agreement with experimental measurements.

A Magnetic Network Parameter Reconstruction and Modular Assignment Approach for Cryogenic PMSM

Bianchi, Nicola;
2026

Abstract

This article focuses on the magnetic field analysis of cryogenic permanent magnet synchronous motor (CPMSM). It develops a rhombic magnetic permeability-based equivalent magnetic network (EMN) model. This model is used to calculate the magnetic field in the air-gap region. Considering the variation of motor electromagnetic parameters at low temperatures, a grid-boundary magnetic permeability parameter reconstruction method is proposed. This method redistributes magnetic permeability parameters to improve their accuracy and, combined with the magnetic network, establishes the permeance reconstruction magnetic network (PRMN) model. Additionally, a modular assignment method is introduced in the rotor grid region for dynamic solution calculation. This method eliminates the need for remodeling at different time instances, reducing time costs and enhancing modeling efficiency. Compared with the EMN model and the finite element analysis (FEA), the proposed PRMN model combines the advantages of fast calculation speed of EMN model and the high accuracy close to FEA. Finally, experiments verify that the calculated results from the PRMN model show good agreement with experimental measurements.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3600941
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