A method for generating data for an internal combustion engine control unit includes receiving at least one constraint by a simulated internal combustion engine, receiving a first value of an air condition by the simulated internal combustion engine, and determining at least one simulated engine parameter associated with a maximum expected output of the simulated internal combustion engine, wherein the maximum expected output is determined based on the first value and the at least one constraint. The method also includes supplementing existing engine information by storing the at least one simulated engine parameter in a memory associated with the internal combustion engine control unit together with the existing engine information.

The disclosure relates to a method for determining a parameter characterizing the anti-knock property of a fuel using a test engine having at least one cylinder, wherein the fuel undergoes combustion inside the cylinder during the course of the method and the cylinder pressure generated by the combustion is detected using a pressure sensor. The pressure sensor has a linear pressure output signal curve. A parameter characterizing the anti-knock property of the fuel is calculated based on the output signal of the pressure sensor. The calculation is done using a mathematical model that considers the deviation of the pressure output signal curve of the pressure sensor being used from the pressure output signal curve of a pick-up sensor prescribed in the ASTM D2699 standard. Moreover, a test system to determine the anti-knock property of a fuel is disclosed.

A system for estimating engine performance is configured to receive, via a cylinder combustion model, a cylinder pressure of a cylinder associated with operation of an internal combustion engine. The system estimates a liner bending moment based at least in part on the cylinder pressure, generates a piston side load associated with the cylinder based at least in part on the liner bending moment, and estimates a piston friction value for a piston associated with the cylinder. The piston friction value may be based at least in part on the cylinder pressure and an engine speed of the internal combustion engine. The system receives, via a convective heat transfer model, an exhaust heat transfer value indicative of a cumulative heat transfer from an exhaust manifold, and estimates an engine torque value based at least in part on the exhaust heat transfer value.

The invention relates to a motor controller for an internal combustion engine of a vehicle, comprising a control unit for setting one or more control variables on the basis of one or more measured variables according to a stored control scheme; wherein the control unit is designed to modify the stored control scheme when the control unit is used as intended with the operational internal combustion engine, which is being controlled by the motor controller, according to a specified learning algorithm, namely using at least one feedback parameter which is associated with an optimization criterion and is provided to the control unit, in order to provide an improved control of the internal combustion engine.

A system for use in a simulation is disclosed. The system may comprise a receiver to receive states of the simulation. A memory may store sets of hyperparameters for a neural network encoder. The memory may also store A-matrices. The neural network encoder, implemented using a processor, may use hyperparameters to implement an encoding function. The hyperparameters and an A-matrix may be selected from the memory responsive to the states of the simulation. The A-matrix may be used to determine a next predicted state for the simulation.

An engine virtual test environment system may include at least one memory and at least one processor configured to perform a virtual engine test and generate a virtual engine to which a physics-based model and a data-driven model are applied to replace an engine. The at least one memory may be configured to store a physics-based model representing the actual structure of an engine by any one of simulation, phenomenological relationship expression, physical characteristic change of constituent elements, a combust model, an ECU model, and an engine model, and a data-driven model representing the actual operation of the engine by any one of a test model, a mathematical model, modeling, engine DoE techniques, mathematical and statistical techniques, a driving range.

An engine simulation system and method for replacing an original engine in an existing system of a piece of equipment, including an engine controller from the original engine, a new engine having an engine controller, and a simulator module connected between the engine controller of the new engine and the engine controller of the original engine. The simulator module is configured to simulate that the original engine is still in the existing system.

The invention relates to an engine control unit for an internal combustion engine of a vehicle, with a control unit which is designed to set one or more operating parameters of the internal combustion engine based on a predefined multidimensional operating parameter map which is stored in the control unit and specifies respective operating parameter values for various operating states of the internal combustion engine, wherein the control unit is designed to transmit an operating parameter history, which comprises operating parameter values set for the internal combustion engine in its operating history, to a learning unit, and to receive operating parameter map update data from the learning unit and to update the stored operating parameter map by means of the operating parameter map update data in order to provide improved control for the internal combustion engine.

A control device of an internal combustion engine using a neural network, wherein an output value obtained by experiments is made training data for a value of an operating parameter of the engine in a presumed usable range, while an output value obtained by prediction without relying on experiments is made training data for a value of the operating parameter of the engine outside of the presumed usable range. The training data obtained by experiments and the training data obtained by prediction are used to learn the weights and the biases of the neural network so that an output value which changes in accordance with a value of an operating parameter of the engine matches the training data, and thereby even outside of the presumed usable range of the operating parameter, the output value can be suitably estimated.

A system for estimating engine performance is configured to receive, via a cylinder combustion model, a cylinder pressure of a cylinder associated with operation of an internal combustion engine. The system estimates a liner bending moment based at least in part on the cylinder pressure, generates a piston side load associated with the cylinder based at least in part on the liner bending moment, and estimates a piston friction value for a piston associated with the cylinder. The piston friction value may be based at least in part on the cylinder pressure and an engine speed of the internal combustion engine. The system receives, via a convective heat transfer model, an exhaust heat transfer value indicative of a cumulative heat transfer from an exhaust manifold, and estimates an engine torque value based at least in part on the exhaust heat transfer value.