OBD of Diesel EGR Using Artificial Neural Networks

2009-01-1427

04/20/2009

Event
SAE World Congress & Exhibition
Authors Abstract
Content
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.
Meta TagsDetails
DOI
https://doi.org/10.4271/2009-01-1427
Pages
14
Citation
Fischer, M., Boettcher, J., Kirkham, C., and Georgi, R., "OBD of Diesel EGR Using Artificial Neural Networks," SAE Technical Paper 2009-01-1427, 2009, https://doi.org/10.4271/2009-01-1427.
Additional Details
Publisher
Published
Apr 20, 2009
Product Code
2009-01-1427
Content Type
Technical Paper
Language
English