According to the invention, a diagnostic system is provided for diagnosing a misfire condition is provided of individual engine cylinders in a turbocharged diesel engine having at least a first and a second cylinder associated with a common exhaust path. The system comprises a pressure sensor in an exhaust path, for measuring a pressure value; a crankshaft position sensor, for detecting a rotational crankshaft position; and a processor unit for reading the pressure sensor and the crankshaft position sensor. The processor unit is arranged for performing acts of: sampling pressure values of the pressure sensor in the common exhaust path as a function of crankshaft angle position; attributing for each cylinder fired in succession at least two sampling values (P.sub.α, P.sub.β) for at least two successive crankshaft angle positions of a pressure pulse during a cylinder firing operation; determining a boundary for a coordinate (P.sub.α, P.sub.β) formed by a tuple of sampling values (P.sub.α, P.sub.β); diagnosing a misfire condition if the coordinate formed by said tuple of sampling values is outside the boundary.

A method for ascertaining emissions of a motor vehicle driven with the aid of an internal combustion engine in a practical driving operation. A machine learning system is trained to generate time curves of the operating variables with the aid of measured time curves of operating variables of the motor vehicle and/or of the internal combustion engine, and to then ascertain the emissions as a function of these generated time curves.

A method for operating a nitrogen oxide sensor comprising: sensing a first measurement signal of the nitrogen oxide sensor, the first measurement signal representing a detected voltage between a reference electrode and an external electrode; sensing a second measurement signal representing a measured gas content in a measuring chamber of the nitrogen oxide sensor; comparing the first measurement signal with a predefined first threshold value; and if the first threshold value is exceeded, assigning the second measurement signal to an emission of NH3.

Detecting manipulation of an SCR catalytic converter system of a motor vehicle. A control command (61) for the SCR catalytic converter system, transmitted from a control unit outside the motor vehicle, is received by the motor vehicle. Manipulation is detected (57) if a response (55) of the SCR catalytic converter system to the execution (54) of the control command (61) does not correspond to expectation. Embodiments also relate to monitoring manipulation of the SCR catalytic converter system. Here, a control command (61) for the SCR catalytic converter system is transmitted (41) to the motor vehicle (10) from a control unit (20) outside the motor vehicle.

Methods and systems are provided for diagnosing an active exhaust valve in an exhaust system based on thermal data. In one example, a method may include indicating degradation of a first active exhaust valve positioned in a first exhaust pipe of a first engine bank based on a difference between a first temperature of exhaust downstream of the first active exhaust valve and a second temperature of exhaust downstream of a second active exhaust valve positioned in a second exhaust pipe of a second engine bank. Degradation of the valve may be confirmed based on thermal image data acquired at outlets of the first and second exhaust pipes.

An exhaust intrusion mitigation system for a vehicle includes one or more processors and a memory communicably coupled to the one or more processors. The memory stores an enclosure detection module which determines if a vehicle is parked within an enclosure with the engine running. An exhaust module determines a point in time at which one or more vehicle vents should be closed if the vehicle remains in the enclosure and the engine remains on. A mitigation module controls operation of the vehicle to close the one or more vents at the point in time when the vent(s) should be closed.

A machine learning device of an amount of unburned fuel using a neural network in which the correlation functions showing correlations between parameters and an amount of unburned fuel are found for parameters relating to operation of an internal combustion engine, and the parameters with strong degrees of correlation with the amount of unburned fuel exhausted from the engine are selected from among the parameters based on the correlation functions. The amount of unburned fuel is learned by using the neural network from the selected parameters and amount of unburned fuel.

An exhaust pipe is fixed to an internal combustion engine. A proximal end of a sensor guide is fixed to the exhaust pipe. A lead extends from an exhaust gas temperature sensor through the inside of the sensor guide to the outside of the sensor guide. The lead is fixed to a body of a vehicle outside the sensor guide. A distal end of the sensor guide is located forward of the proximal end.

An internal combustion engine condition determination apparatus includes a storage device; and an execution device. The storage device stores mapping data that defines a mapping. The execution device is configured to execute an acquisition process of acquiring an internal combustion engine state variable every time a crankshaft of an internal combustion engine rotates by a predetermined angle, and a determination process of determining a condition of the internal combustion engine based on an output obtained through the mapping using the internal combustion engine state variable as an input. The mapping data is trained by machine learning. The execution device is configured to prohibit the determination process when a rotation speed of the crankshaft is equal to or higher than a predetermined threshold.

Methods and systems are provided for diagnosing an active exhaust valve in an exhaust system based on thermal data. In one example, a method may include indicating degradation of a first active exhaust valve positioned in a first exhaust pipe of a first engine bank based on a difference between a first temperature of exhaust downstream of the first active exhaust valve and a second temperature of exhaust downstream of a second active exhaust valve positioned in a second exhaust pipe of a second engine bank. Degradation of the valve may be confirmed based on thermal image data acquired at outlets of the first and second exhaust pipes.