Transient Modeling of Induction Machine Using Artificial Neural Network Surrogate Models

A transient model of an induction machine (IM) is developed in this work using an artificial neural network (ANN) surrogate model. The model is suitable to be used for direct-on-line IMs. The finite-element (FE)-based model of IM is used to generate the training, validation, and testing datasets. Di...

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Bibliographic Details
Published in:IEEE transactions on magnetics 2022-09, Vol.58 (9), p.1-4
Main Authors: Tahkola, Mikko, Mukherjee, Victor, Keranen, Janne
Format: Article
Language:English
Subjects:
Artificial neural network (ANN)
Artificial neural networks
digital twin
Digital twins
Finite element method
induction machine (IM)
Induction motors
Magnetism
Optimization
Predictive models
real time
Shafts
surrogate modeling
Testing
Torque
Training
Transient analysis
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Summary:A transient model of an induction machine (IM) is developed in this work using an artificial neural network (ANN) surrogate model. The model is suitable to be used for direct-on-line IMs. The finite-element (FE)-based model of IM is used to generate the training, validation, and testing datasets. Different inputs and model configurations are investigated to find an optimal solution in developing the transient model. The proposed transient model is suitable to be used in digital twin services since it can estimate the current and torque accurately in real time based on only voltage and measured shaft speed.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2022.3180176