The complexity of modern engine control has increased rapidly. New software tools to support the difficult electronic control units application process are required to fulfill the limited emissions required by legislation. An in-car measurment with an online variation of the ECU maps during the driving cycles can support the application process. The paper describes the development of a digital measurement data processing system for in-car use. With the in-car data acquistion system implemented, it is possible to record data measured during arbitrary driving cycles. The acquired data are used to model the system behavior. In addition to static modelling, vehicle-specific parameters are considered by using system identification with dynamic neural networks. Consequently, the model for the nitrogen oxide emissions and the exhaust gas opacity can be used as a support tool in the application process and as a basis for an automated optimisation.


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    Title :

    In-car modelling of emissions with dynamic artificial neural networks


    Additional title:

    Emissionsmodellierung im Fahrzeug mit Hilfe künstlicher neuronaler Netze


    Contributors:


    Publication date :

    2001


    Size :

    7 Seiten, 12 Bilder, 8 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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