Improving Fuel Consumption Prediction for Marine Diesel Engines Using Hierarchical Neural Networks and Pulsating Exhaust Models

Improving Fuel Consumption Prediction for Marine Diesel Engines Using Hierarchical Neural Networks and Pulsating Exhaust Models

Predicting end-of-process variables in internal combustion engines, such as brake-specific fuel consumption or pollutant emissions, is crucial for engine design decisions. However, errors in common multi-layer-perceptron-based artificial neural network models often match the magnitude of the expecte...

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Bibliographic Details
Main Authors: Anibal Aguillon Salazar, Georges Salameh, Pascal Chesse, Nicolas Bulot, Yoann Thevenoux
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Energies
Subjects:
diesel engines
neural networks
fuel consumption
metamodel
mean-value engine model
pulse unsteadiness
Online Access:https://www.mdpi.com/1996-1073/18/1/17
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