Novella, Ricardo (Universitat Politecnica de Valencia), Pla, Benjamín (Universitat Politecnica de Valencia), Bares, Pau (Universitat Politecnica de Valencia), Aramburu, Alexandra (Universitat Politecnica de Valencia)

Identification of Adequate Combustion in Turbulent Jet Ignition Engines Using Machine Learning Algorithms

Scheduled for presentation during the Regular session "Engine control system" (MoBT1), Monday, August 23, 2021, 17:30−17:50, Room T1

6th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, August 23-25, 2021, Tokyo, Japan

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

Turbulent jet ignition (TJI) engines might substantially improve the efficiency of spark ignition (SI) engines by locating the spark in a pre-chamber. Concretely, the passive pre-chamber concept could be directly applied in commercial SI engines with minor modifications. The pre-chamber burns a small quantity of fuel providing the rest of the chamber with sufficient energy for a fast and efficient combustion, however, the combustion suffers from controllability and the phenomena involved are difficult to predict. The present paper aims to develop a suitable algorithm for combustion prediction in TJI engines by exploring machine learning techniques to identify the more appropriate operating conditions. The algorithm differentiates between stable and unstable combustion using online data to keep updated in case of a non-expected bias. Experimental data from a research TJI engine demonstrate the capacity of the algorithm proposed.