Browse Publications Technical Papers 2004-01-1363
2004-03-08

Detection of Engine Misfire Events using an Artificial Neural Network 2004-01-1363

New environmental legislation places increasing demands on automobile emission controls, requiring new approaches to engine management and diagnostics systems. This paper demonstrates the use of an Artificial Neural Network (ANN) solution for misfire detection in spark ignition engines. The solution is based on a truly parallel hardware implementation of an ANN. The network is developed by a data-driven training process, using data with known incidences of misfires. No analytical or algorithmic methods need to be developed in order to train or use the ANN for misfire detection. There is minimal processing overhead on the main processor of the engine management unit, freeing resources for alternative engine management tasks or enabling the use of less costly processor solutions.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Members save up to 18% off list price.
Login to see discount.
Special Offer: Download multiple Technical Papers each year? TechSelect is a cost-effective subscription option to select and download 12-100 full-text Technical Papers per year. Find more information here.
We also recommend:
TECHNICAL PAPER

Advance Data Analytics Methodologies to Solve Diesel Engine Exhaust Aftertreatment System Challenges

2019-01-5035

View Details

TECHNICAL PAPER

A Neural Network for Fault Recognition

930861

View Details

TECHNICAL PAPER

SI Engine Emissions Model Based on Dynamic Neural Networks and D-Optimality

2005-01-0019

View Details

X