Abstract: A method of determining aging of a diesel oxidation catalyst (DOC) in an engine exhaust system includes receiving a first sensor signal from a first nitrogen oxides (NOx) sensor positioned in exhaust flow upstream of the DOC. The first sensor signal is indicative of an amount of NOx in the exhaust flow upstream of the DOC. The method further includes receiving a second sensor signal from a second NOx sensor positioned in the exhaust flow downstream of the DOC. The second sensor signal is indicative of an amount of NOx downstream of the DOC. A difference between the first sensor signal and the second sensor signal is calculated by a controller. A DOC aging level based on a predetermined correlation between the difference and DOC aging can then be determined by the controller if at least one predetermined operating condition is satisfied.

Abstract: A method of determining aging of a diesel oxidation catalyst (DOC) in an engine exhaust system includes receiving a first sensor signal from a first nitrogen oxides (NOx) sensor positioned in exhaust flow upstream of the DOC. The first sensor signal is indicative of an amount of NOx in the exhaust flow upstream of the DOC. The method further includes receiving a second sensor signal from a second NOx sensor positioned in exhaust flow downstream of the DOC. The second sensor signal is indicative of an amount of NOx downstream of the DOC. A difference between the first sensor signal and the second sensor signal is calculated via a controller. A DOC aging level based on a predetermined correlation between the difference and DOC aging is then determined by the controller.

Abstract: A vehicle includes an engine, an exhaust system, and a controller. The exhaust system includes a selective catalytic reduction (SCR) device, and a rear nitrogen oxide (NOx) sensor. The controller, which is in communication with the NOx sensor, includes a processor and tangible, non-transitory memory. A plurality of data maps and a plurality of binary maps are recorded in memory. Each data map is indexed by a different pair of exhaust system performance values. Each cell of each data map is populated by estimated downstream NOx levels. The binary maps are indexed by one of the pairs of exhaust system performance values. Each cell of each binary map is populated by a binary value, i.e., a 0 or 1. The controller uses the data maps and the binary maps to execute a control action with respect to the exhaust system, such as verifying plausibility of the rear NOx sensor.

Abstract: A particulate estimation system is configured for estimating a mass of particulate matter accumulated in a particulate filter of an exhaust system. The system includes a memory device, an interface, and a controller. The memory device stores a plurality of modules. Each of the plurality of modules is configured to uniquely estimate an amount of the particulate matter accumulated within the particulate filter over a period of time. The interface receives a plurality of input signals. The plurality of input signals correspond to a plurality of modules that are stored in the memory device. The controller derives a hybrid model based on the input signals. The hybrid model is configured to provide an output that is an estimation of the amount of particulate matter accumulated within the particulate filter over the period of time as a function of the plurality of input signals.

Abstract: An amount of particulate matter accumulated in a particulate filter of an exhaust system is estimated by preloading a memory location with a plurality of hybrid models. Each hybrid model estimates an amount of particulate matter accumulated in the particulate filter between a pair of operating points. An estimated amount of particulate matter accumulated in the particulate filter is stored in the memory location for each hybrid model. Each hybrid model is ranked based on estimation accuracy during operating conditions and the highest ranked hybrid model is selected. The estimated amount of particulate matter accumulated in the particulate filter corresponding to the highest ranked hybrid model is added to the soot estimation value stored in the memory location that corresponds to a ranked hybrid model to provide a soot estimation value of a cumulative estimated amount of particulate matter contained in the particulate filter for the ranked hybrid model.

Abstract: A method of monitoring soot mass in a particulate filter of an exhaust system includes determining a pressure differential across the filter, obtaining a first soot mass estimate by fitting the determined pressure differential to a first stored database of measured or modeled pressure differentials and corresponding measured soot masses taken during filter regeneration using a substantially similar filter previously loaded following a complete filter regeneration, and obtaining a second soot mass estimate by fitting the determined pressure differential to a second stored database of measured or modeled pressure differentials and corresponding measured soot masses taken during filter regeneration using a substantially similar filter loaded following an incomplete filter regeneration. Actual soot mass is estimated by calculating a weighted sum of the first and second soot mass estimates with weighting based on operating parameters indicative of regeneration efficiency.

Abstract: A method of controlling the regeneration of a particulate filter includes defining a regeneration trigger limit for at least one operating parameter of the vehicle, modifying the regeneration trigger limit based upon a sensed ambient operating condition and a sensed vehicle operating condition to define a modified regeneration trigger limit, and regenerating the particulate filter when the modified regeneration trigger limit for the operating parameter is reached.

Abstract: A method for controlling regeneration within an after-treatment component of a compression-ignition engine comprises calculating an initial estimate of accumulated particulate matter based on a pressure-based soot accumulation model and a pressure drop index indicative of a decrease in pressure across the component. An adjusted estimate of accumulated particulate matter in the component is calculated based on the initial estimate and a soot prediction error inherent in the soot model. The adjusted estimate is compared to a predetermined threshold associated with the after-treatment component, and a remedial action is initiated when the adjusted estimate of accumulated particulate matter in the after-treatment component exceeds the predetermined threshold. The pressure-based soot accumulation model may be configured to predict soot accumulation in the absence of passive regeneration, and an adjusted kinetic burn model may be used to estimate a quantity of soot disposed through passive regeneration.

Abstract: A method of monitoring soot mass in a particulate filter of an exhaust system includes predicting soot mass in the particulate filter based at least partially on a pressure differential between exhaust flowing into the filter and exhaust flowing out of the filter. The predicted soot mass is then revised based at least partially on measured operating parameters indicative of mass flow rate of nitrogen oxides in exhaust flow of the exhaust system and temperature of the particulate filter.

Abstract: An amount of particulate matter accumulated in a particulate filter of an exhaust system is estimated by preloading a memory location with a plurality of hybrid models. Each hybrid model estimates an amount of particulate matter accumulated in the particulate filter between a pair of operating points. An estimated amount of particulate matter accumulated in the particulate filter is stored in the memory location for each hybrid model. Each hybrid model is ranked based on estimation accuracy during operating conditions and the highest ranked hybrid model is selected. The estimated amount of particulate matter accumulated in the particulate filter corresponding to the highest ranked hybrid model is added to the soot estimation value stored in the memory location that corresponds to a ranked hybrid model to provide a soot estimation value of a cumulative estimated amount of particulate matter contained in the particulate filter for the ranked hybrid model.

Abstract: A particulate estimation system is configured for estimating a mass of particulate matter accumulated in a particulate filter of an exhaust system. The system includes a memory device, an interface, and a controller. The memory device stores a plurality of modules. Each of the plurality of modules is configured to uniquely estimate an amount of the particulate matter accumulated within the particulate filter over a period of time. The interface receives a plurality of input signals. The plurality of input signals correspond to a plurality of modules that are stored in the memory device. The controller derives a hybrid model based on the input signals. The hybrid model is configured to provide an output that is an estimation of the amount of particulate matter accumulated within the particulate filter over the period of time as a function of the plurality of input signals.

Abstract: A method of controlling the regeneration of a particulate filter includes defining a regeneration trigger limit for at least one operating parameter of the vehicle, modifying the regeneration trigger limit based upon a sensed ambient operating condition and a sensed vehicle operating condition to define a modified regeneration trigger limit, and regenerating the particulate filter when the modified regeneration trigger limit for the operating parameter is reached.

Abstract: A method of monitoring soot mass in a particulate filter of an exhaust system includes determining a pressure differential across the filter, obtaining a first soot mass estimate by fitting the determined pressure differential to a first stored database of measured or modeled pressure differentials and corresponding measured soot masses taken during filter regeneration using a substantially similar filter previously loaded following a complete filter regeneration, and obtaining a second soot mass estimate by fitting the determined pressure differential to a second stored database of measured or modeled pressure differentials and corresponding measured soot masses taken during filter regeneration using a substantially similar filter loaded following an incomplete filter regeneration. Actual soot mass is estimated by calculating a weighted sum of the first and second soot mass estimates with weighting based on operating parameters indicative of regeneration efficiency.

Abstract: A method of monitoring soot mass in a particulate filter of an exhaust system includes predicting soot mass in the particulate filter based at least partially on a pressure differential between exhaust flowing into the filter and exhaust flowing out of the filter. The predicted soot mass is then revised based at least partially on measured operating parameters indicative of mass flow rate of nitrogen oxides in exhaust flow of the exhaust system and temperature of the particulate filter.