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Faults in the intake and exhaust path of turbocharged common-rail Diesel engines can lead to an increase of emissions and performance losses. Standard fault detection strategies based on plausibility checks and trend checking of sensor data are not able to detect and isolate all faults appearing in the intake and exhaust path without employing additional sensors. By applying model based methods a limited sensor configuration can be used for fault detection. Therefore a model based fault diagnosis concept with parity equations is considered, [1]. In this contribution the fault diagnosis system, which comprises semi-physical thermodynamic turbocharger model, models of gas pressure in the intake and exhaust manifold, residual generation, residual to symptom transformation and fault diagnosis is presented.

The complexity of the air path of modern common rail diesel engines is rapidly increasing and simultaneously, the demand on air and turbocharger control performances is becoming more challenging. To meet the upcoming emission regulations, the usage of a low pressure exhaust gas recirculation (EGR) circuit in addition to the standard high pressure EGR circuit is often considered. This kind of architecture usually requires a more sophisticated air control system in which a precise control of the EGR flow delivered by the two recirculation branches is required. Moreover, as an alternative or in addition to the low pressure EGR, the implementation of a NOx reduction system e.g. a NOx trap is possible. To proper maintain the correct efficiency of this kind of after-treatment system, special regeneration strategies are adopted where a rich combustion is used instead of the standard Diesel lean mode.

Faults in the intake and exhaust path of turbocharged common-rail diesel engines lead to an increase of emissions and to performance losses. Fault detection strategies based on plausibility checks, threshold based trend or limit checking of sensor data are not able to detect and isolate all faults appearing in the intake and exhaust path without increasing of the number of sensors. The need to minimize mass and reduce cost, including the number of sensors, while maintaining robust performance leads to higher application of models for intake and exhaust path components. Therefore a concept of model based fault detection with parity equations is considered. It contains the following parts: modeling, residual generation with parity equations using parallel nonlinear models, fault to symptom transformation with masking of residuals dependent on the operating point and limit violation checking of the residuals.