A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …

Legislations for greenhouse gas and pollutant emissions from light-duty vehicles are
pushing the spark ignition engine to be cleaner and more efficient. As one of the promising …

Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …

In response to the stringent emission regulations, artificial neural network (ANN) coupled
with genetic algorithm (GA) is employed to optimize a novel internal combustion engine …

Abstract Machine learning (ML) models can accelerate the development of efficient internal
combustion engines. This study assessed the feasibility of data-driven methods toward …

Abstract Machine learning method provides a promising way to predict the transient
emission characteristic of diesel engine due to its many advantages such as short …

This review targets various scenarios where CFD could be used and the logical parts
needed for exemplary computations. The machine learning aspect with algorithms that have …

In the present study, a new combination of different available engine sensors along with an
exhaust gas temperature sensor is used as the input of an artificial neural network to …

The use of computational models for internal combustion engine development is ubiquitous.
Numerical simulations using simpler to complex physical models can predict engine's …

An optimized active pre-chamber geometry was obtained by combining computational fluid
dynamics (CFD) and machine learning (ML). A heavy-duty engine operating with methane …