Improved Parametric Representation of IM from FEM for More Accurate Torque Predictions: Simulations and Experimental Validations
Journal article, 2024

In this work, an updated methodology to determine the parameters of three-phase induction machines (IMs) is developed and presented. The goal of this determination is to achieve a better model representation of induction machines for the usage of a circuit-based control system. First, the theory of the T-form model (TFM) and the inverse Γ-form model (IGFM) are reviewed. The former review becomes the foundation of the following interpretation of the developing methods for identifying the needed parameters. Next, a 2D electromagnetic finite element method (FEM) model of a 15kW IM is utilized to demonstrate the strength of the methodology on a real machine. Furthermore, a comparison of results using the conventional test and the newly proposed method is presented, demonstrating the strength of the proposed procedure with enhanced accuracy for the torque and slip prediction. Lastly, experimental results using a 15kW IM are utilized to demonstrate the usefulness of the proposed parameter determination procedure.

Finite Element Method (FEM)

Integrated circuit modeling

parameter determination

Stators

Stator windings

Couplings

Rotors

induction machine (IM)

Perfect field-oriented control (PFOC)

Torque

Finite element analysis

Equivalent circuits

Author

Meng-Ju Hsieh

Chalmers, Electrical Engineering, Electric Power Engineering

Emma Grunditz

Chalmers, Electrical Engineering, Electric Power Engineering

Torbjörn Thiringer

Chalmers, Electrical Engineering, Electric Power Engineering

2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2022

00939994 (ISSN) 19399367 (eISSN)

Vol. 60 5 6660-6671

Subject Categories

Applied Mechanics

Other Engineering and Technologies not elsewhere specified

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/TIA.2024.3403806

More information

Latest update

10/26/2024