Abstract:
A system according to the present disclosure includes a model predictive control (MPC) module and an actuator module. The MPC module generates a set of possible target values for an actuator of an engine and predicts an operating parameter for the set of possible target values. The predicted operating parameter includes an emission level and/or an operating parameter of an exhaust system. The MPC module determines a cost for the set of possible target values and selects the set of possible target values from multiple sets of possible target values based on the cost. The MPC module determines whether the predicted operating parameter for the selected set satisfies a constraint and sets target values to the possible target values of the selected set when the predicted operating parameter satisfies the constraint. The actuator module controls an actuator of an engine based on at least one of the target values.
Abstract:
A system is provided and includes a fuel module that, based on a crankshaft angle of an engine, generates a value indicative of an amount of fuel burned in a cylinder or a change in the amount of fuel burned. A heat release module, based on the value, determines an amount of heat released during a combustion event of the cylinder. A pressure module, based on the amount of heat released, estimates a pressure in the cylinder. A temperature module, based on the pressure, estimates a temperature in the cylinder. A concentration module, based on the pressure or the temperature, estimates nitrogen oxide concentration levels in the cylinder. An output module, based on the nitrogen oxide concentration levels, estimates an amount of nitrogen oxides. A control module, based on the amount of nitrogen oxides out of the cylinder, controls operation of the engine or an exhaust system.
Abstract:
A method of estimating soot loading in a diesel particulate filter (DPF) in a vehicle exhaust system includes determining engine operating conditions of an engine in exhaust flow communication with the diesel particulate filter, and monitoring a pressure differential of the exhaust flow across the diesel particulate filter. The method includes estimating soot loading in the diesel particulate filter according to a pressure-based model using the monitored pressure differential when the engine operating conditions are within a predetermined first set of engine operating conditions, and estimating soot loading in the diesel particulate filter according to an engine-out soot model and a DPF soot loading model when the engine operating conditions are within a predetermined second set of operating conditions. The method includes updating the engine-out soot model based in part on a difference in estimated soot loading between the pressure-based model and the DPF soot loading model.
Abstract:
A method of estimating soot loading in a diesel particulate filter (DPF) in a vehicle exhaust system includes estimating an engine-out soot rate using a first neural network that has a first set of vehicle operating conditions as inputs. The method further includes estimating DPF soot loading using a second neural network that has the estimated engine-out soot rate from the first neural network and a second set of vehicle operating conditions as inputs. Estimating the engine-out soot rate and estimating the DPF soot loading are performed by an electronic controller that executes the first and the second neural networks. The method also provides for training the first and second neural networks both offline (for initial settings of the neural networks in the vehicle), and online (when the vehicle is being used by a vehicle operator). An exhaust system has a controller that implements the method.
Abstract:
System and methods can identify a source of nitrogen oxide reduction inefficiency in an exhaust system including first and second selective catalytic reduction (SCR) catalysts connected in series along an exhaust line. The methods and systems can determine which of the first and second SCR catalysts is a source of nitrogen oxide reduction inefficiency based on the temperatures of the exhausts gases flowing through the first and second SCR catalysts.
Abstract:
A method for engine-out soot flow rate prediction of an exhaust gas treatment system is provided. A measured level of oxides of nitrogen in the exhaust gas treatment system is received. An engine fuel injection timing and air-fuel ratio of an engine producing the oxides of nitrogen are also received. An engine timing factor is determined based on the engine fuel injection timing. An engine air-fuel ratio factor is determined based on the engine air-fuel ratio. An engine-out soot flow rate prediction is generated based on the measured level of oxides of nitrogen, the engine timing factor, and the engine air-fuel ratio factor.
Abstract:
A method includes: (a) determining an engine speed of an internal combustion engine, wherein the internal combustion engine has an engine wall, and the engine wall has a wall temperature; (b) determining an engine load of the internal combustion engine; (c) determining a wall-reference temperature as a function of the engine load and the engine speed of the internal combustion engine; and (d) adjusting, using a cooling system, a volumetric flow rate of a coolant flowing through the internal combustion engine to maintain the wall temperature at the wall-reference temperature.
Abstract:
An automotive vehicle includes an internal combustion engine that combusts an air/fuel mixture thereby generating exhaust gas containing particulate matter, and an exhaust after-treatment component that collects the particulate matter. A regeneration system burns off the collected particulate matter thereby regenerating the exhaust after-treatment component. A controller obtains a model of the combustion that is based on a kinetic controlled combustion phase and a mixing controlled combustion phase, and determines a point on the model with respect to current engine conditions that indicates an amount of the particulate matter in the exhaust gas.
Abstract:
A method for controlling a selective catalytic reduction device in an exhaust aftertreatment system of a vehicle includes monitoring vehicle connectivity information, and controlling ammonia storage in the selective catalytic reduction device based on the monitored vehicle connectivity information. Vehicle connectivity information is used to predict vehicle operating conditions along an estimated path of vehicle travel. The predicted vehicle operating conditions are used to predict profiles for vehicle exhaust gas parameters. Predicted profiles for exhaust gas parameters are used in determining ammonia storage setpoints for the selective catalytic reduction device. The ammonia storage setpoints are use in regulating an amount of ammonia producing dosing agent injected into the exhaust aftertreatment system, thereby controlling ammonia storage in the selective catalytic reduction device.
Abstract:
A method of estimating a current soot output from an engine includes sensing a mass flow rate of a flow of exhaust gas from the engine, and defining a soot output base rate of the engine when the engine is operating at a reference state. A soot ratio for a current operating state of the engine is calculated. The mass flow rate, the soot output base rate, and the soot ratio are multiplied together to define an estimated value of the current soot output from the engine. The soot ratio is based on current engine operating parameters, including an air/fuel ratio of the engine, an exhaust gas recirculation ratio of the engine, a fuel injection pressure of the engine, and a fuel injection timing of the engine.