Abstract: Computational models and calculations relating to trapped and scavenged air per cylinder (APC) improve scavenging and non-scavenging operational modes of internal combustion engines as well as the transition there-between. Data from sensors which include engine speed, manifold air pressure, barometric pressure, crankshaft position, and valve state are provided to a pair of artificial neural networks. A first neural network utilizes this data to calculate the nominal volume of gas, i.e., air trapped in the cylinder. A second neural network utilizes this data to calculate the trapping ratio. The output of the first network is utilized with the ideal gas law to calculate the actual mass of trapped APC. The actual mass of trapped APC is also divided by the trapping ratio calculated by the second network to determine the total APC and is further utilized to calculate the scavenged APC by subtracting the trapped APC from the total APC.

Abstract: Computational models and calculations relating to trapped and scavenged air per cylinder (APC) improve scavenging and non-scavenging operational modes of internal combustion engines as well as the transition there-between. Data from sensors which include engine speed, manifold air pressure, barometric pressure, crankshaft position, and valve state are provided to a pair of artificial neural networks. A first neural network utilizes this data to calculate the nominal volume of gas, i.e., air trapped in the cylinder. A second neural network utilizes this data to calculate the trapping ratio. The output of the first network is utilized with the ideal gas law to calculate the actual mass of trapped APC. The actual mass of trapped APC is also divided by the trapping ratio calculated by the second network to determine the total APC and is further utilized to calculate the scavenged APC by subtracting the trapped APC from the total APC.

Abstract: A method for determining if a selective catalytic reduction (SCR) device that is dosed with a reductant is being mis-dosed by considering an expected exhaust gas output state from the SCR device and measured exhaust gas output state, a NOx sensor sensitivity figure that is an indication of how sensitive the measured exhaust gas output state is to dosing errors and performing cross-correlation operations.