scholarly journals Permanent Magnets Aging in Variable Flux Permanent Magnet Synchronous Machines

2018 ◽  
Author(s):  
Daniel Fernandez ◽  
Maria Martinez ◽  
David Reigosa ◽  
Juan Guerrero ◽  
Carlos Suarez ◽  
...  
Keyword(s):  
Permanent Magnet ◽  
Permanent Magnets ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machines ◽  
Variable Flux

scholarly journals Permanent Magnets Aging in Variable Flux Permanent Magnet Synchronous Machines

2020 ◽  
Vol 56 (3) ◽  
pp. 2462-2471
Author(s):  
Daniel Fernandez ◽  
Maria Martinez ◽  
David Reigosa ◽  
Juan M. Guerrero ◽  
Carlos Manuel Suarez Alvarez ◽  
...  
Keyword(s):  
Permanent Magnet ◽  
Permanent Magnets ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machines ◽  
Variable Flux

scholarly journals Effects of manufacturing tolerances of permanent magnets in fractional slot permanent magnet synchronous machines

2019 ◽  
Vol 2019 (17) ◽  
pp. 4060-4064
Author(s):  
Sergio Zarate ◽  
Gaizka Almandoz ◽  
Gaizka Ugalde ◽  
Javier Poza ◽  
Ana Julia Escalada
Keyword(s):  
Permanent Magnet ◽  
Permanent Magnets ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machines ◽  
Manufacturing Tolerances ◽  
Fractional Slot

scholarly journals Comparative Analysis of High Frequency Signal Injection Based Torque Estimation Methods for SPMSM, IPMSM and SynRM

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 592
Author(s):  
Maria Martinez ◽  
David Reigosa ◽  
Daniel Fernandez ◽  
Fernando Briz
Keyword(s):  
Permanent Magnet ◽  
High Frequency ◽  
Permanent Magnets ◽  
Estimation Methods ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machines ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Torque Estimation ◽  
Signal Injection

Torque estimation in permanent magnet synchronous machines and synchronous reluctance machines is required in many applications. Torque produced by a permanent magnet synchronous machine depends on the permanent magnets’ flux and d q -axes inductances, whereas torque in synchronous reluctance machines depends on the d q -axes inductances. Consequently, precise knowledge of these parameters is required for proper torque estimation. The use of high frequency signal both for permanent magnets’ flux and d q -axes inductances estimation has been recently shown to be a viable option. This paper reviews the physical principles, implementation and performance of high-frequency signal injection based torque estimation for permanent magnet synchronous machines and synchronous reluctance machines.

scholarly journals Development of Mathematical Models in Explicit Form for Design and Analysis of Axial Flux Permanent Magnet Synchronous Machines

2020 ◽  
Vol 10 (21) ◽  
pp. 7695
Author(s):  
Franjo Pranjić ◽  
Peter Virtič
Keyword(s):  
Magnetic Flux ◽  
Permanent Magnet ◽  
Input Data ◽  
Permanent Magnets ◽  
Synchronous Machines ◽  
Simplified Model ◽  
Magnetic Flux Density ◽  
Axial Component ◽  
Permanent Magnet Synchronous Machines ◽  
Axial Flux

This article proposes a methodology for the design of double-sided coreless axial flux permanent magnet synchronous machines, which is based on a developed model for calculating the axial component of the magnetic flux density in the middle of the distance between opposite permanent magnets, which also represents the middle of the stator. Values for different geometric parameters represent the input data for the mathematical model in explicit form. The input data are calculated by using a simplified finite element method (FEM), which means that calculations of simplified 3D models are performed. The simplified model consists of two rotor disks with surface-mounted permanent magnets and air between them, instead of stator windings. Such a simplification is possible due to similar values of permeability of the air and copper. For each simplified model of the machine the axial component of the magnetic flux density is analyzed along a line passing through the center of opposite permanent magnets and both rotor disks. Values at the middle of the distance between the opposite permanent magnets are the lowest and are therefore selected for the input data at different stator, rotor disks and permanent magnets (PM) thicknesses. Such input data enable the model to consider the nonlinearity of materials.

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