The objective of the present invention is to provide an exhaust purification system that is capable of purifying exhaust gas during both lean and stoichiometric driving. The exhaust purification system is equipped with: a feedback-use identifier, which identifies parameter values such that the error between the output value from a LAF sensor and the estimated value for the LAF sensor output as obtained from a model equation is minimized; and a stoichiometric driving mode controller. The controller performs feedback control and thereby determines the fuel injection amount such that in the stoichiometric driving mode the equivalence ratio value as calculated from the parameters reaches a target value which is set such that a three-way purification reaction occurs in an under-engine catalyst. The identifier identifies the model parameters before feedback control is initiated by the controller.

A method and apparatus is disclosed to control the operation of an air charging system of an internal combustion engine. A plurality of output parameters of the air charging system are monitored. An error is calculated between the monitored output parameters and a target value thereof. The calculated errors are applied to a linear controller that yields a virtual input used to calculate a plurality of input parameters for the air charging system. The input parameters is used to determine the position of a corresponding actuator of the air charging system for operating the actuators according to the determined position thereof. The inputs parameters are calculated with a non-linear mathematical model of the air charging system configured such that the virtual inputs are in a linear relation with only one of the output parameters and vice versa.

A rate based model predictive controller and method for air path control for a diesel engine regulates intake manifold pressure (MAP) and EGR valve flow rate to specified set points by coordinated control of a variable geometry turbine (VGT) and EGR valve position. A decay and a flexible Lyapunov function is enforced on the rate based model predictive controller for a single step prediction and control arisen.

A system and method are provided for monitoring a pressure of fuel supplied to the fuel injector, and providing a control input voltage to the piezostack in response to the pressure to cause the injector to provide a fuel injection having a desired shape. In the system and method, providing a control input voltage includes applying a model-based algorithm to the pressure to determine the control input voltage.

Disclosed herein are devices, systems, and methods relating to balancing engine performance and engine emissions of an engine in a vehicle in real time. In an example, a method can include sensing operation data indicative of an engine response during a current engine operation. The current ending operation can include a supervisory control of engine emissions. The method can include evaluating a response model to determine engine performance deviation data corresponding to an expected baseline engine performance and an expected current engine performance at the current engine operation. This evaluation can be performed via controller. This evaluation can be based on the operation data. The method can include generating and setting a performance constraint in response to evaluating the response model. The performance constraint can be set such that the engine performance deviation data is maintained at a controls objective that inhibits deterioration of the engine performance over time.

A method for controlling an engine of a vehicle by a controller includes determining whether a running time of the engine exceeds a reference driving time, based on the running time being less than or equal to the reference driving time, determining a first CO2 emission amount corresponding to the driving time by utilizing an MAF sensor, determining a model CO2 amount based on a first regression model that has correlation data between a combusted fuel amount and a CO2 emission amount of the engine, comparing the first CO2 emission amount with the model CO2 amount, determining a correction factor to adjust the first regression model based on comparing the first CO2 emission amount with the model CO2 amount, determining a second CO2 emission amount through a second regression model generated by applying the correction factor, and controlling the engine based on the second CO2 emission amount.