Modeling of Exhaust Gas Temperature at the Turbine Outlet Using Neural Networks and a Physical Expansion Model

Modeling of Exhaust Gas Temperature at the Turbine Outlet Using Neural Networks and a Physical Expansion Model

The accurate estimation of exhaust gas temperature across the turbine is always more important for the optimization of engine performance, ensuring durability of the turbine impeller and catalyst, and reducing and calculating emissions concentration. Traditional physical modeling approaches, based o...

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Bibliographic Details
Main Authors: Alessandro Brusa, Alice Grossi, Mirco Lenzi, Fenil Panalal Shethia, Nicolò Cavina, Ioannis Kitsopanidis
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Energies
Subjects:
neural networks
engine modeling
exhaust gas temperature
turbine
physical approach
simulation
Online Access:https://www.mdpi.com/1996-1073/18/7/1721
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