A Review of Applications of Machine Learning for Emissions Estimation in Diesel Engines

Abstract

There has been an increasing demand to reduce the emissions of diesel engines, especially in maritime applications. Moreover, emission regulations are becoming stricter every year. This has led to an urge for more complex engine control systems with more accurate emissions estimators included. Machine learning methods have been long adopted to create models with high complexity to estimate the engine’s emissions and to rely less on conventional physical measurement devices. This paper presents a brief review of the development of engine emissions estimation using machine learning methods over the last 20 years. The review will however mainly focus on emissions prediction from engine in-cylinder pressure and engine functional vibration signal.