Keywords:
Automotive
Internal Combustion Engines
Artificial Intelligence
Machine Learning
Combustion Models
Data-driven models
Exhaust emission modeling
In my PhD program, I focus on studying and applying artificial intelligence algorithms and methodologies to analyze data collected from experimental activities on vehicles and internal combustion engines. One of the main goals is to model complex physical phenomena, such as the formation of pollutant emissions and the combustion process, using both traditional and innovative fuels.
My activities include conducting practical tests in engine test benches and emission laboratories with vehicle roller benches, analyzing the collected data (where I use AI methods and tools), developing data-driven models, and integrating them into advanced simulation tools. All of this is aimed at applying these solutions in real industrial contexts.
