"Model Predictive Control of a Diesel Engine Airpath"
Model Predictive Control of a Diesel Engine Airpath
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This thesis addresses the model predictive control of a Diesel engine airpath and contributes a novel strategy to derive a sophisticated multi-objective control which is a basic tool for the control and finally the reduction of Diesel engine emissions.
Modern human society demands a still growing degree of mobility which is reflected in the strong increase of motorized transport. This increase of mobility, however, has a serious negative side-effect: It is well known that poor air quality can cause health problems, which is heavily affected by the large increase of vehicle traffic. To counteract this trend, regulating measures on emissions have been defined.
These regulating measures are typically met by emission aftertreatment, or by controlling the rawemissions of an engine. Such raw-emissions are typically influenced by the injection system and the airpath in Diesel engines. However, the control of an airpath is a very challenging task due to constraints, nonlinearities and uncertainties of the plant.
The aim of this thesis is to develop sophisticated control design, able to improve the performance of the airpath of a Diesel engine.
Every airpath control system of a Diesel engine tries to supply the combustion chamber with a mixture of fresh air-mass and recirculated exhaust gas adequate to the requested injection quantity such that emission is minimized and the torque is maximized. Starting from a discussion about the control objective of emissions, which demands modelling or sensing of emissions, this thesis follows the alternative of using intermediate variables, which can be the standard configuration using boost
pressure and fresh air-mass, or a new configuration of oxygen charge concentration and boost pressure measurement.
Then the plant is analyzed by physical assumptions, which are the basis for understanding and simulation experiments. To control the intermediate quantities, the nonlinear plant is linearly identified at selected operating points.