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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    Title :

    OBD of Diesel EGR Using Artificial Neural Networks


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE World Congress & Exhibition ; 2009



    Publication date :

    2009-04-20




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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