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.


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    Titel :

    OBD of Diesel EGR Using Artificial Neural Networks


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Kirkham, Chris (Autor:in) / Boettcher, Joerg (Autor:in) / Fischer, Michael (Autor:in) / Georgi, Richard (Autor:in)

    Kongress:

    SAE World Congress & Exhibition ; 2009



    Erscheinungsdatum :

    20.04.2009




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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