Transient Modeling of Induction Machine Using Artificial Neural Network Surrogate Models
Mikko Tahkola, Victor Mukherjee, Janne Keränen
Abstract
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.
Topics & Concepts
Transient (computer programming)Artificial neural networkComputer scienceTorqueFinite element methodControl theory (sociology)VoltageArtificial intelligenceEngineeringPhysicsThermodynamicsControl (management)Structural engineeringElectrical engineeringOperating systemElectric Motor Design and AnalysisSensorless Control of Electric MotorsMagnetic Properties and Applications