A method of calculating a nitrogen oxide (NOx) mass reduced from a lean NOx trap (LNT) during regeneration includes calculating a C3H6 mass flow used to reduce the NOx among a C3H6 mass flow flowing into the LNT of an exhaust purification device, calculating a NH3 mass flow used to reduce the NOx among a NH3 mass flow generated in the LNT, calculating a reduced NOx mass flow based on the C3H6 mass flow used to reduce the NOx and the NH3 mass flow used to reduce the NOx, and calculating the reduced NOx mass by integrating the reduced NOx mass flow over a regeneration period.

The purpose of the present invention is to prevent disturbance in the behavior of a power plant at the time of switching a controller in a vehicle power plant whose operation is controlled by manipulation of a plurality of actuators by the controller. In order to achieve the purpose, a vehicle power plant control apparatus provided by the present invention is configured as a target value tracking controller in which at least one controller calculates the amount of manipulation of the actuators according to an equation including an integrator for integrating a deviation between a state quantity and a target value thereof such that each of a plurality of state quantities of the power plant can track the corresponding target value. When the controller used for manipulating the actuators is switched from another controller to the target value tracking controller, the initial value of the integrator is inversely calculated such that, in a state equation of a plant model for the power plant with the state quantity as a state vector and the amount of manipulation as an input vector, a differential immediately before the switching of the state vector agrees with a differential immediately after the switching.

A method for ascertaining a variable characterizing a flow rate of a fuel injector during an operation of an internal combustion engine, to which the fuel injector is assigned. At least two input values for a data-based model are ascertained, and at least one output value is determined with the aid of the data-based model, on the basis of which a value for the variable characterizing the flow rate of the fuel injector is ascertained. The data-based model combines at least two methods differing from one another for ascertaining a variable characterizing a flow rate of a fuel injector.

The present invention provides a method for analyzing and optimizing the injection of fluid into an internal combustion engine via a common rail system. Once various injection parameters are determined for a given injection system, these data may be used to model the effect of sequential injection events for the system. A processer can then be used to run the model and to adjust sequential fuel injection events to optimize engine performance and fuel usage.

Methods and systems for optimizing fuel economy and maintaining particulate emissions below a threshold of an engine system in a vehicle. An engine system has port fuel injection, direct injection, variable compression ratio, and independent compression/expansion. A processor predicts settings for the four systems that optimize for a fuel economy that is maximized. A particulate rate of the engine system is computed based on the settings. A determination is made of whether the particulate rate is below a threshold. When the particulate rate is below the threshold, command signals are delivered to actuators of the systems to move to the settings. When the threshold is exceeded, the settings are revised to maintain the particulate below the threshold while optimizing for fuel economy.

The disclosure describes a system that includes a closed-loop reference module, an adaptation module, and a control module. The closed-loop reference module is configured to execute a reference model that represents operation of an engine and determine a reference control signal and a reference state trajectory signal. The adaptation module is configured to determine an adaptation signal based on a difference between the reference state trajectory signal and an engine state trajectory signal representative of actual operation of the engine. The control module is configured to receive the reference control signal from the closed-loop reference module, the adaptation signal from the adaptation module, and the engine state trajectory signal. The control module is further configured to determine a demand signal based on the engine state trajectory signal, the adaptation signal, and the reference control signal, and output the demand signal to control operation of at least one engine component.

An auxiliary-machine control device equipped with: a command-value acquisition unit for acquiring an operation command value for a device to be controlled and an allowable range for the operation amount of control means for controlling the operating state of the device to be controlled; an operation-amount calculation unit for calculating the operation amount for the control means on the basis of the acquired operation command value; and an operation-amount determination unit for outputting the calculated operation-amount signal to the device to be controlled if the operation amount calculated by the operation-amount calculation unit falls within the allowable range, and outputting an upper-limit value or a lower-limit value for the operation-amount allowable range if the calculated operation amount falls outside of the allowable range.

A heating system includes at least one electric heater disposed within the fluid flow system. A control device includes a microprocessor and is configured to determine a temperature of the at least one electric heater based on a model and at least one input from the fluid flow system. The control device is configured to provide power to the at least one electric heater based on the temperature of the at least one electric heater.

A method for identifying a set of interpolation point data points from training data for a sparse Gaussian process model, encompassing the following tasks: successively selecting training data points from the set of training data for acceptance into or exclusion from a set of interpolation point data points in accordance with a selection criterion; and terminating selection when a termination criterion exists; the selection criterion depending on a divergence between a target value of the selected training data point and a function value, at the selected training data point, of the Gaussian process model based on the respectively current set of interpolation point data points.

A system and approach for development of setpoints for a controller of a powertrain system. The controller may be parameterized as a function of setpoints to provide performance variables that are considered acceptable by a user or operator for current operating conditions of the engine or powertrain. The controller may determine set point trajectories in real time during operation of the powertrain system and determine positions of manipulated variables do drive controlled variables to associated and determined set point trajectories. The present system and approach may determine set point trajectories for powertrain conditions on-line and in real time, whereas set point trajectories have previously been determined off-line for powertrain control.