OBD of Diesel EGR Using Artificial Neural Networks Honda R&D Europe (Deutschland) GmbH

Format:

Book

Conference/Event

Author/Creator:

Fischer, Michael, author.

Conference Name:

SAE World Congress & Exhibition (2009-04-20 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2009

Summary:

To detect malfunctions of the EGR system of a passenger car diesel engine, a neural network approach was selected using Self Organizing Maps (SOM). Self Organizing Maps are self-learning technologies that can be used to retrieve typical data patterns in large data sets. This technology is very efficient for identifying if patterns from a new, modified or changed system are similar to already existing patterns. The SOM outputs a measure of similarity to typical system behavior patterns'. As an OBD function, this value is a measure for system anomaly detection.Performing dynamic tests using standard driving cycles, not only was the occurrence of a malfunction within the EGR system detected by the neural network, the cause of the malfunction could also be identified

Notes:

Vendor supplied data

Publisher Number:

2009-01-1427

Access Restriction:

Restricted for use by site license