An intelligent electronic device (IED) may monitor wet stack residue buildup of a diesel engine. Once the wet stack residue accumulates to a certain amount, the IED may perform a mitigation procedure. Additionally, tracking wet stack residue buildup may allow an IED to attempt to prevent or reduce accumulation of the wet stack residue. The IED may track an operating power level of the diesel engine to estimate the rate of residue buildup.

A method and system are provided for assessing engine faults. The method includes measuring actual diesel particulate filter (DPF) soot loading, determining expected DPF soot loading, aid determining that a possible engin component fault is an actual engine component fault by determining that measured actual DPF soot loading exceeds the expected DPF soot loading.

Methods and systems are provided for using an engine laser ignition system to take images, in real-time, of a cylinder during combustion and estimate cylinder soot generation. If excess soot generation is determined, cylinder fueling is adjusted by varying an injection pressure, amount, and ratio. An air-fuel ratio of the cylinder is also adjusted in view of exhaust temperature constraints to reduce soot generation.

The present invention refers to a method for determining an amount of a substance in exhaust gas of an internal combustion engine, the method comprises the steps of: determining, for an effective condition of the engine, at least one operating parameter; determining, for a reference condition of the engine, a reference amount of the substance present in exhaust gas of the engine in the reference condition when being operated based on the determined operating parameter; determining an intake manifold temperature difference between the effective condition and the reference condition of the engine; and determining an effective amount of the substance in the exhaust gas of the engine in the effective condition in dependence on the determined reference amount of the substance and the determined intake manifold temperature difference.

An intelligent electronic device (IED) may monitor wet stack residue buildup of a diesel engine. Once the wet stack residue accumulates to a certain amount, the IED may perform a mitigation procedure. Additionally, tracking wet stack residue buildup may allow an IED to attempt to prevent or reduce accumulation of the wet stack residue. The IED may track an operating power level of the diesel engine to estimate the rate of residue buildup.

A system for particulate filter regeneration includes a pre-converter universal heated exhaust gas oxygen (UHEGO) sensor disposed upstream from a three-way catalytic (TWC) converter and a particulate filter (PF), and a post-converter UHEGO sensor disposed downstream from the TWC converter and upstream from the PF. An engine controller for an internal combustion engine (ICE) and in communication with the pre-converter UHEGO sensor and the post-converter UHEGO sensor is included. The engine controller is configured to determine an amount of particulate mass accumulated in the PF during operation of the ICE and deactivate at least one of a plurality of cylinders of the ICE such that a deactivated cylinder intake air (DCIA) pass-through volume flows through the at least one deactivated cylinder and into the TWC converter and the PF. The DCIA pass-through volume is a function of the determined amount of particulate mass accumulated in the PF.

A method and system are provided for assessing engine faults. The method includes measuring actual diesel particulate filter (DPF) soot loading, determining expected DPF soot loading, aid determining that a possible engin component fault is an actual engine component fault by determining that measured actual DPF soot loading exceeds the expected DPF soot loading.

A control device 60 of a vehicle drive device comprises a processing part 81 configured to use a trained model using a neural network to calculate at least one output parameter of a vehicle, and a control part 82 configured to control the vehicle drive device. The neural network includes a first input layer to which at least one first input parameter of the vehicle at a first point of time is input, a second input layer to which at least one second input parameter of the vehicle at a second point of time is input, a first hidden layer to which outputs of the first input layer are input, a second hidden layer to which at least one value correlated with the outputs of the first hidden layer, and outputs of the second input layer are input, and an output layer outputting at least one output parameter.

A fuel content detection system is disclosed. The fuel content detection system may include an engine control module (ECM) to receive a measurement of a parameter. The parameter may correlate with an amount of a substance in a fuel that is being consumed in an engine. The ECM may determine an estimation of the parameter based on a model. The model may use a predetermined value associated with the amount of the substance, and the engine may be configured to consume a designated type of fuel that includes an amount of the substance that corresponds to the predetermined value. The ECM may determine, based on the estimation and the measurement not being within a threshold range, that the fuel is not the designated type of fuel and perform an action associated with the engine.

An active purge system may include: a canister to collect therein an evaporation gas evaporated from a fuel tank; a purge line to connect the canister to an intake pipe; a purge pump to pressurize the evaporation gas to allow the evaporation gas to move from the canister to the intake pipe; a purge valve installed on the purge line to be located between the purge pump and the intake pipe; and an engine connected to the intake pipe. In particular, the engine includes an injector installed on a cylinder head, an intake valve, and an exhaust valve.