Dieter Seebach

Aspects of gasoline controlled auto ignition — development of a controller concept

A promising approach to decrease emissions and fuel consumption at the same time for gasoline engines is the controlled auto ignition. The complex process is analysed and modelled within the “Collaborate Research Centre 686 — model based control of the homogenized low temperature combustion” by the Institute for Combustion Engines and the Institute of Automatic Control at RWTH Aachen University to design a future controller concept.

Control of future low Temperature Combustion Technologies with nonlinear Model based Predictive Control based on Neural Networks

Abstract The combustion in future engines will work with a very high amount of recirculated exhaust gas in part load conditions to enable a low peak combustion temperature. This combustion suffers from instabilities of the process and a highly nonlinear behaviour. The paper presents the use of neural nets for observing the engine. A nonlinear model without feedback of measurements is linearised online and combined with an extended Kalman filter. This observer is compared to a neural net with observer structure by application to two different valve timing strategies. The more promising observer is combined with a model based predictive controller with a quadratic cost function. Its analytic solution is compared with quadratic programming for respecting constraints in the prediction for improving the control error.

NEURAL NETWORKS FOR MODELLING AND CONTROLLING FUTURE LOW TEMPERATURE COMBUSTION TECHNOLOGIES

Abstract Modern internal combustion engines with a low peak combustion temperature suffer from instabilities of the process and a highly nonlinear behaviour. These make a closed loop control a necessity. In order to build and tune a controller a model is needed, which has to be able to reproduce the nonlinear behaviour. The paper presents the application of offline trained NNSSIF nets, a neural networks architecture with state space attributes. These are combined with an extended Kalman filter and a nonlinear model-based predictive controller to a research internal combustion engine.

Modeling and Simulation of Gasoline Auto Ignition Engines

Abstract Both the customer demand for increasing mobility and the emission legislation lead to a challenge for engine researchers and developers in order to reduce emissions and fuel consumption. One approach that is presently under extensive investigation is to implement auto-ignition combustion in gasoline engines. This combustion mode offers the possibility to reduce emissions and fuel consumption during part load operation. Furthermore it offers the advantage that it does not need an expensive exhaust gas after treatment due to nearly zero NOx-emissions in contrast to stratified direct injection operation. The auto-ignition depends strongly on stratification of air, residual gas and fuel. Furthermore, the thermodynamic state of the charge is of major importance to control the combustion process. Detailed knowledge of ignition and its dependency on operating conditions is necessary to develop efficient control strategies. This paper gives a summary on modeling strategies for gasoline auto-ignition developed within the collaborative research centre “SFB 686 – Modellbasierte Regelung der homogenisierten Niedertemperatur-Verbrennung” [1]. The auto-ignition process is simulated with two different approaches. 3D CFD calculation of flow, injection and mixture formation, which is bi-directional coupled to a multi-zone reaction kinetics solver. This 3D approach enables to analyze the thermodynamic conditions in the combustion chamber that lead to the auto-ignition. Thus, the temporal and spatial occurrence of exothermic reactions and their influence on the engine process are specified in detail. To reduce the computational costs and enable multi-cycle calculations, a second simulation approach was developed to analyze the process under steady state and transient operating conditions. The approach uses 1D gas exchange calculation with embedded burn function calculations based on reaction kinetics. The simulation shows good correlation to the test bench results, but requires a computational time of approximately 5 min per cycle. The calculation time can be further reduced with an approach based on a polynomial combustion model. Multi-cycle calculations are performed and compared to test bench results. Due to the small computational effort, this approach offers the possibility of a coupling to a controller design environment for synchronous simulation and control.

Aspekte der ottomotorischen Selbstzündung

Ein viel versprechender Ansatz, sowohl Schadstoffausstos als auch Kraftstoffverbrauch bei Ottomotoren zu senken, stellt der Einsatz der kontrollierten Selbstzundung dar. Der komplexe Prozess wird im Rahmen des „Sonderforschungsbereichs 686 — Modellbasierte Regelung der homogenisierten Niedertemperatur-Verbrennung“ vom Lehrstuhl fur Verbrennungskraftmaschinen und dem Institut fur Regelungstechnik der RWTH Aachen University analysiert und modelliert, um ein kunftiges Regelkonzept zu entwerfen.Ein viel versprechender Ansatz, sowohl Schadstoffausstos als auch Kraftstoffverbrauch bei Ottomotoren zu senken, stellt der Einsatz der kontrollierten Selbstzundung dar. Der komplexe Prozess wird im Rahmen des „Sonderforschungsbereichs 686 — Modellbasierte Regelung der homogenisierten Niedertemperatur-Verbrennung“ vom Lehrstuhl fur Verbrennungskraftmaschinen und dem Institut fur Regelungstechnik der RWTH Aachen University analysiert und modelliert, um ein kunftiges Regelkonzept zu entwerfen.