On Line Working Neural Estimator of SI Engines Operational Parameters University of Perugia

Format:

Conference/Event

Author/Creator:

Grimaldi, Carlo N., author.

Conference Name:

SAE 2000 World Congress (2000-03-06 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2000

Summary:

In this paper the evaluation of the suitability of the Artificial Neural Networks for setting up simulation modules for "analytical redundancy" was further carried out. The performance of the ANN modules was enhanced, by taking into account the engine dynamics for the simulation of fast engine transients and obtaining satisfactory results.Working toward actual on board application in Fault Diagnosis systems, some ANN modules were implemented in an on-line system which acquires signals from an engine mounted on a test bench and compares in real time the experimental values with the estimated ones. In this way, it was possible to perform long duration tests of ANN's behaviour, substantially confirming the results of the conventional off-line analysis

Notes:

Vendor supplied data

Publisher Number:

2000-01-1247

Access Restriction:

Restricted for use by site license