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A Combined Model and Data-Driven Approach for the Determination of Rotor Temperature in an Induction Machine.

Razvan Mocanu1, Alexandru Onea1, Constantin Catalin Dosoftei1

  • 1Department of Automatic Control and Applied Informatics, Gheorghe Asachi Technical University of Iasi, Bulevardul Profesor Dimitrie Mangeron 67, 700050 Iași, Romania.

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Summary

This study presents a hybrid method using a NARX network and particle filter to estimate Induction Machine rotor temperature. This approach enhances electric powertrain reliability and safety in automotive applications.

Keywords:
AC machinesfault diagnosisneural network applicationsrecursive estimation

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Area of Science:

  • Electrical Engineering
  • Machine Learning
  • Automotive Engineering

Background:

  • Automotive industry safety regulations necessitate robust electrical machine protection.
  • Reliable electric powertrains are crucial for modern vehicles.
  • Accurate rotor temperature estimation is key for Induction Machine (IM) performance and longevity.

Purpose of the Study:

  • To introduce a hybrid method for estimating the rotor temperature of an Induction Machine (IM).
  • To enhance the reliability and safety of electric powertrains through accurate thermal management.
  • To develop a method that accounts for model uncertainties for improved estimation.

Main Methods:

  • A hybrid approach combining a Nonlinear Autoregressive Network with Exogenous inputs (NARX) and a particle filter.
  • Utilizing measured stator case temperature as input for the NARX network and a thermal process observation function.
  • Incorporating uncertainties from both the NARX and thermal models to refine the posterior estimate.

Main Results:

  • The proposed hybrid method demonstrated good performance in estimating IM rotor temperature.
  • Experimental validation using a real IM test-bench confirmed the method's applicability.
  • The approach effectively managed uncertainties in the prediction and observation models.

Conclusions:

  • The developed hybrid method is effective for real-time rotor temperature estimation in Induction Machines.
  • This technique contributes to improved safety and reliability of automotive electric powertrains.
  • The integration of NARX networks within particle filters offers a promising direction for advanced machine thermal monitoring.