Abstract

A high-fidelity two-axis model of an interior permanent-magnet synchronous machine (IPM) presents a convenient way for the characterization and validation of motor dynamic performance during the design stage. In order to consider a nonlinear IPM nature, the model is parameterized with a standard dataset calculated beforehand by finite-element analysis. From two possible model implementations, the current model (CM) seems to be preferable to the flux-linkage model (FLM). A particular reason for this state of affairs is the rather complex and time-demanding parameterization of FLM in comparison with CM. For this reason, a procedure for the fast and reliable parameterization of FLM is presented. The proposed procedure is significantly faster than comparable methods, hence providing considerable improvement in terms of computational time. Additionally, the execution time of FLM was demonstrated to be up to 20% shorter in comparison to CM. Therefore, the FLM should be used in computationally intensive simulation scenarios that have a significant number of iterations, or excessive real-time time span.

Highlights

  • Permanent-magnet synchronous machines excel in high torque density and high efficiency, so they have been widely investigated in recent years [1,2,3]

  • From the two permanent-magnet synchronous-machine topologies, i.e., surface permanent-magnet machines (SPM) and interior permanent-magnet machines (IPM), the latter are especially suitable for transport applications, where a wide speed range is a key requirement [4,5]

  • The specific feature that enables such an operation is their pronounced flux-weakening capability. This is an immediate consequence of IPM design, where the magnetic field due to the armature current is considerable with respect to the permanent magnet field [6]

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Summary

Introduction

Permanent-magnet synchronous machines excel in high torque density and high efficiency, so they have been widely investigated in recent years [1,2,3]. By taking into account the specific geometry and material, FEA produces an accurate magnetic-field model, which is an excellent foundation for the reliable prediction of machine operational characteristics In this way, the expensive and time-consuming prototype stage can be completely left out [10,11]. Rotor geometries, or any other variation of magnetic permeance along the air gap are a common sight in modern practices In this way, the effects of air-gap harmonics on voltages, currents, flux linkages, and torque can be properly described. The effects of air-gap harmonics on voltages, currents, flux linkages, and torque can be properly described This is essential for a user, if he intents to use the IPM model for, e.g., developing control (including sensorless and field-weakening operations) [22], analyzing torque ripple [31], and studying acoustic characteristics [19]

General Equations
Linear Model
Nonlinear Model
Simulation Form
Static FEA Batch Simulation
CM Parameterization orig
FLM Parameterization
Inversion via Minimization
Inversion via Intersections
Model Verification
Parameterization Time
Execution Time
Findings
Conclusions
Full Text
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