A method for monitoring crankcase pressure, in which a learning curve is calculated according to a target-actual deviation of the crankcase pressure, the target crankcase pressure is adjusted according to the learning curve, and a limit curve is calculated according to the target crankcase pressure. The actual crankcase pressure is monitored for exceedance of the limit curve. After an engine start, upon identification of a steady-state operation of the internal combustion engine, the actual crankcase pressure is compared with a limit value and, if the limit value is identified as being exceeded, the learning curve and, as a result, the limit curve are reset to their initial values.

A control device of an internal combustion engine includes a parameter acquisition unit that acquires a plurality of input parameters, a calculation unit that calculates at least one output parameter using a neural network model, and a controller that controls the internal combustion engine. The neural network model includes a plurality of neural network units and an output layer. Each of the neural network units includes one input layer and at least one intermediate layer. The neural network model inputs different combinations of input parameters selected from the input parameters to each of the input layers of the neural network units such that a total number of input parameters to be input to the neural network units is larger than the number of the input parameters.

A method for controlling an internal combustion engine with a crankshaft position sensor, intake air pressure sensor and fresh air intake throttle valve, includes: determining the engine's rotational speed based on the crankshaft position derivative relative to time; determining the intake air pressure for a first crankshaft position corresponding to 180° before top dead center; determining the intake air pressure for a second crankshaft position corresponding to 390° before top dead center; determining an atmospheric pressure learning pressure threshold based on the engine's rotational speed; determining whether the difference between the intake air pressures for the first and second crankshaft positions is below the atmospheric pressure learning pressure threshold; if so, commanding atmospheric pressure learning by applying a first-order filter to the intake air pressure for the second crankshaft position; and controlling the internal combustion engine as a function of the learned atmospheric pressure value.

A controller includes a memory device and an execution device, which executes an operation of an operated unit of an internal combustion engine. The execution device includes a first operation process that operates the operated unit by an operated amount, which is calculated on the basis of a state of a vehicle, using an adapted data set, a second operation process that operates the operated unit by an operated amount that is defined by a relationship defining data set and the state of the vehicle, and a switching process that switches the operation of the operated unit between an operation by the first operation process and an operation by the second operation process, depending on whether the vehicle is performing a manual acceleration travel or an automatic acceleration travel.

A control system includes a controller. The controller counts the number of driving times of a high pressure fuel pump, which is the number of reciprocating motions of a plunger based on a crank counter. The controller estimates a high pressure system fuel pressure based on the calculated number of driving times, a fuel temperature detected by a fuel temperature sensor, and a low pressure system fuel pressure detected by a low pressure system fuel pressure sensor when the high pressure system fuel pressure is not able to be acquired from a high pressure system fuel pressure sensor. The controller sets an opening period of an in-cylinder fuel injection valve based on the estimated high pressure system fuel pressure and to perform an engine start by an in-cylinder fuel injection when the high pressure system fuel pressure is not able to be acquired from the high pressure system fuel pressure sensor.

A CPU calculates probability models by inputting input variables to a neural network. Next, the CPU determines whether a maximum value among the calculated probability models is larger than an upper limit value of a permissible range. When the maximum value is larger than the upper limit value of the permissible range, the CPU calculates a difference between the maximum value and a first reference value within the permissible range, and subtracts the difference from all the probability models. Then, the CPU calculates a probability of misfire in each cylinder by inputting each of the calculated probability models to a softmax function of mapping.

Provided is a fuel injection control device that makes it possible to precisely estimate an amount of fuel remaining in an air intake passage at a start-up of an engine, and to precisely set an fuel injection amount during start-up operation. In the fuel injection control device of the present invention, in a process in which the engine is transferred from operation state to a stop state, engine stop information is acquired and stored in a nonvolatile memory, the engine stop information including, at least an information indicating whether the current engine stop is an intended stop accompanied by fuel cutting. During the start-up of the engine, judgement is made as to whether the last engine stop was the intended stop or not, based upon the engine stop information and a fuel injection amount during start-up operation is determined with reference to the result of the judgement.

A method and control device for automatically identifying knocking in an internal combustion engine, wherein, in a predefined measurement time frame, a signal of the knocking sensor is received and evaluated with respect to a criterion for detecting knocking. A basic threshold value predefined for the identification of knocking is modified by a predefined variable interference factor, which depends on a relative point in time at which an inlet valve of at least one of the cylinders closes in relation to a predefined reference point. A signal based on the sensor signal is only identified as knocking if it reaches at least the modified basic threshold value.

In the present invention, a clogging rate is calculated using a first flow rate function when the degree of clogging of the throttle valve is in the reference state and a second flow rate function estimated based on the intake air volume. For each predetermined period, sample points, which are combinations of the second flow rate function and throttle valve position, are obtained, and the learning points are calculated by averaging a plurality of sample points for each predetermined position range. Based on the plurality of learning points, coefficients a to c of the approximate function of the second flow rate function characteristic are calculated by the least-squares method, and the clogging rate is calculated based on the second flow rate function characteristic and the first flow rate function approximated by the approximate function using the coefficients a to c.

A system and method includes a driver component having a first sensor rigidly mounted therewith and configured to provide a first signal indicative of a rotation of the driver component, and a second sensor rigidly mounted relative to the driver component, a driven component, and a flexible coupler disposed between the driver component and the driven component; wherein the second sensor provides a second signal indicative of a rotation of the driven component, and a controller disposed to receive the first signal and the second signal. The controller is configured and operates to calculate a difference between the first signal and the second signal, and infer a torque variation between the driver component and the driven component based primarily on the difference between the first signal and the second signal.