The current generation of vehicle models are increasingly being equipped with on-board diagnostic (OBD) systems aimed at assessing the 'state of health' of important anti-pollution subsystems and components. In order to promptly diagnose and fix quality and reliability problems that may potentially affect such complex diagnostic systems, even during advanced development prior to mass production, some vehicle prototypes undergo a testing phase under realistic conditions of use (a mileage accumulation campaign). The aim of this work is to set up a statistical tool for improving the reliability of the OBD system by monitoring its operation during the mileage accumulation campaign of a new vehicle model. A dedicated software program was developed by the authors to filter the large experimental database recorded during the mileage accumulation campaign and to extract the time series of the diagnostic indices to be analysed. A model-based monitoring approach, using continuous time autoregressive (CAR) modelsfor the time-series structure and traditional control chartsfor the estimated residuals, is adopted. A Kaiman recursion procedure for the estimation of the unknown CAR model parameters is described. An application of the proposed approach is presented for a diagnostic index related to the state ofhealth ofthe oxygen sensor.


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    Title :

    A statistical monitoring approach for automotive on-board diagnostic systems


    Additional title:

    Ein statistischer Ansatz zur Überwachung für On-Board-Diagnosesysteme von Fahrzeugen


    Contributors:


    Publication date :

    2007


    Size :

    11 Seiten, 6 Bilder, 24 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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