Detection of Engine Misfire Events using an Artificial Neural Network AXEON Limited

Format:

Conference/Event

Author/Creator:

Nareid, Helge, author.

Conference Name:

SAE 2004 World Congress & Exhibition (2004-03-08 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2004

Summary:

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

Notes:

Vendor supplied data

Publisher Number:

2004-01-1363

Access Restriction:

Restricted for use by site license