Incorporating a Deep Neural Network into Moving Horizon Estimation for Embedded Thermal Torque Derating of an Electric Machine

Incorporating a Deep Neural Network into Moving Horizon Estimation for Embedded Thermal Torque Derating of an Electric Machine

This study presents a novel state estimation approach integrating Deep Neural Networks (DNNs) into Moving Horizon Estimation (MHE). This is a shift from using traditional physics-based models within MHE towards data-driven techniques. Specifically, a Long Short-Term Memory (LSTM)-based DNN is traine...

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Bibliographic Details
Main Authors: Alexander Winkler, Pranav Shah, Katrin Baumgärtner, Vasu Sharma, David Gordon, Jakob Andert
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
state estimation
deep learning
moving horizon estimation
nonlinear and optimal automotive control
neural networks
temperature control
Online Access:https://www.mdpi.com/1996-1073/18/14/3813
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