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PhD Thesis

Physical Modeling and Control of Low Temperature Combustion in Engines

Anders Widd

Abstract

The topic of this thesis is model-based control of two combustion engine concepts, Homogeneous Charge Compression Ignition (HCCI) and Partially Premixed Combustion (PPC), using physics-based models. The studied combustion concepts hold promise of reducing the emission levels and fuel consumption of internal combustion engines.

A cycle-to-cycle model of HCCI, including heat losses to the cylinder wall, was derived. The continuous heat transfer between the cylinder wall and the gas in the cylinder was approximated by three heat transfer events during each cycle. This allowed the model to capture the main dynamics of the cylinder wall temperature while keeping the complexity of the resulting model at a tractable level.

The model was used to derive model predictive controllers for the combustion phasing using the inlet air temperature and inlet valve closing timing as control signals. The resulting controllers were evaluated experimentally and achieved promising results in terms of set-point tracking and disturbance rejection.

Additionally, the differences in performance between using a switched state feedback controller and a hybrid model predictive controller for controlling exhaust recompression HCCI were investigated. The dynamics of exhaust recompression HCCI vary significantly between certain operating points, and the model predictive controller produced smoother transients in both simulations and experiments.

A continuous-time model of PPC was derived and implemented in the Modelica language. The model structure, a single-zone model, and implementation platform, JModelica.org, were chosen in order to allow for numerical optimization based on the model equations. The resulting framework allowed the calibration of the model parameters to be formulated as an optimization problem penalizing deviations between a measured pressure trace and that of the model. The calibrated model predicted the effects of variations in the injection timing with satisfactory accuracy.


PhD Thesis ISRN LUTFD2/TFRT--1090--SE, Department of Automatic Control, Lund University, Sweden, April 2012.

 
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