An exhaust gas system for a motor vehicle includes an exhaust gas burner and a pressure sensor for sensing flame formation in the exhaust gas burner.

Methods and systems are provided for monitoring a change in exhaust particulate filter (PF) soot load during an engine non-combusting condition. In one example, a method may include, responsive to a higher than threshold PF temperature immediately prior to an engine shutdown, estimating a rate of soot burn when the engine is no longer combusting, and estimating a soot load on the PF during and at an onset of immediately subsequent engine start based in part on the rate of soot burn.

A device for diagnosing a particulate filter suitable for: determining a measured pressure time profile, and a theoretical pressure time profile upstream of the filter, implementing, on each profile: low-pass filtering to obtain a first filtered time profile, second low-pass filtering of the first filtered time profile to obtain a second filtered time profile, calculating a difference between the second filtered time profile and the first filtered time profile, obtaining an absolute value of the calculated difference, and calculating an integral of the absolute value, and, from a comparison between the two integrals, a diagnosis of the particulate filter.

The invention relates to a method for controlling the pressure of the exhaust gas of a machine, in particular an internal combustion engine. The exhaust gas is discharged from the machine via an exhaust gas line, and the exhaust gas line has a regulating device, preferably comprising a throttle valve or a throttle flap, said regulating device delimiting a pressure-regulated section of the exhaust gas line. Gas, preferably air, which is regulated into the pressure-regulated section via a compressed gas line is supplied such that the pressure in the pressure-regulated section is substantially kept at a constant value. The invention additionally relates to a corresponding device.

A method for controlling an exhaust after-treatment system based on NO.sub.2 medium adjustment includes the following steps: creating a diesel oxidation catalyst (DOC) reaction map, a diesel particulate filter (DPF) reaction map, and a selective catalytic reduction (SCR) reaction map; obtaining an SCR reaction temperature, desired SCR reaction efficiency, and obtaining NO.sub.2 demand according to the SCR reaction map; obtaining a DPF reaction temperature and differential pressure, and obtaining NO.sub.2 consumption from the DPF reaction map; obtaining NO.sub.2 production, and calculating NO.sub.2 input for SCR; if the NO.sub.2 input is not equal to the NO.sub.2 demand, calculating target NO.sub.2 production, obtaining a target DOC reaction temperature corresponding to the target NO.sub.2 production from the DOC reaction map, and adjusting a fuel injection rate so that the DOC reaction temperature is equal to the target DOC reaction temperature.

A control system for an engine including a turbocharger disposed downstream of a plurality of cylinders. The control system includes an engine sensor configured to generate a signal indicative of an operational characteristic of the engine. The control system includes a first valve configured to control exhaust flow through a first set of cylinders from the plurality of cylinders. The control system includes a second valve configured to control exhaust flow through a second set of cylinders from the plurality of cylinders. The control system includes a controller communicably coupled to the engine sensor, the first valve, and the second valve. The controller is configured to receive the signal generated by the engine sensor. The controller is configured to actuate the first valve and the second valve based on the received signal. The first valve and the second valve are actuated to adjust exhaust flow received by the turbocharger.

Using machine learning for cylinder misfire detection in a dynamic firing level modulation controlled internal combustion engine is described. In a classification embodiment, cylinder misfires are differentiated from intentional skips based on a measured exhaust manifold pressure. In a regressive model embodiment, the measured exhaust manifold pressure is compared to a predicted exhaust manifold pressure generated by neural network in response to one or more inputs indicative of the operation of the vehicle. Based on the comparison, a prediction is made if a misfire has occurred or not. In yet other alternative embodiment, angular crank acceleration is used as well for misfire detection.

An improved method for performing a conditioning process for a particulate filter, preferably adapted for an aftertreatment system arranged downstream of an internal combustion engine. The proposed method provides for conditioning of a filter under controlled conditions such that the filter may reach a desired operation state in a more efficient and faster manner. Further, the proposed method also advantageously provides for maintaining the desired operation state, in which the filtration capacity may be at a usable level.

The disclosure relates to a DPF regeneration trigger control method and terminal device, and a storage medium. The method includes: setting an active trigger differential pressure and an initial trigger differential pressure; and controlling, according to a relationship between a differential pressure of the DPF collected in real time during a vehicle travelling process and and the active trigger differential pressure and a relationship between the differential pressure of the DPF and the initial trigger differential pressure, the vehicle to actively start DPF regeneration, to trigger passive DPF regeneration, or not to start DPF regeneration; otherwise, controlling the vehicle to actively start DPF regeneration. According to the disclosure, by setting a flexible trigger interval, there is a tolerance interval of differential pressure, so that fuel consumption of the diesel engine can be reduced, and the economy is improved.

An exhaust purification system of an internal combustion engine comprises a filter trapping particulate matter in exhaust gas, a differential pressure sensor detecting a differential pressure before and after the filter or a differential pressure between a pressure in the exhaust passage and an atmospheric pressure, a temperature sensor detecting a temperature of exhaust gas, and a deposition calculating part configured to calculate an amount of particulate matter deposited at the filter. The deposition calculating part is configured to calculate a first estimated value of an amount of the particulate matter based on the differential pressure, calculate a second estimated value of an amount of the particulate matter based on an amount of increase of temperature of the exhaust gas, and calculate an amount of the particulate matter based on the first estimated value and the second estimated value.