Model-Based Optimization of Combustion-Engine Control
Research output: Thesis › Doctoral Thesis (monograph)
Therefore, this thesis investigates closed-loop combustion control for reliable PPC operation. The feedback loop from pressure-sensor measurement to fuel-injection actuation is studied in particular. A common theme for the controllers presented is the use of models in the controller design. Either to evaluate controller performance in simulation, or to optimize engine performance online. The principle of model predictive control is used for its ability to incorporate modeled system behavior in the controller design, and to control multi-variable systems with input and output constraints.
The problem of tuning robust and noise insensitive combustion-timing controllers, and its dependence on fuel reactivity is studied in simulation. Simulation results reveal a nonlinear relation between start of injection and combustion timing that depends on both load and fuel reactivity. Optimization is used to find robust and noise-insensitive controller gains. Guidelines for combustion-timing controller tuning are also presented.
Low-order autoignition models are evaluated and compared for the purpose of model-based controller design. The comparison shows that a simple autoignition model is sufficient for control of the ignition delay when the cylinder-charge properties are varied. This model is then used by a model predictive controller to simultaneously control ignition delay and combustion timing in transient engine operation, using both gas-exchange and fuel-injection actuation.
The effects of pilot injection on the combustion processes are characterized experimentally. Experimental results show that a pilot injection can decrease the main-injection ignition delay and maintain the pressure-rise rate at an acceptable level. This is utilized by a presented fuel-injection controller that manages to control both combustion timing and pressure-rise rate.
Strategies for improving the low-load performance of PPC are studied experimentally, where results show that the selection of injection timings and the use of a pilot injection are important when maximizing the combustion efficiency. The suggested low-load controller demonstrated a 9 % efficiency increase during transient engine operation.
This thesis also investigates the design of a controller that utilizes the degrees of freedom enabled by multiple injections to efficiently fulfill constraints on cylinder pressure, NOx emissions and exhaust temperature. A simulation study shows a potential 2 - 4 % indicated efficiency increase when two injections are used instead of one. These findings motivated the design of a hybrid multiple-injection controller that changes the number of injections depending on operating conditions. The controller designed was capable of reproducing the found efficiency increase experimentally with respect to constraints on pressure and NOx emissions.
A model-predictive pressure controller is also introduced. The controller predicts how the cylinder pressure varies with fuel injection by taking advantage of the estimated heat-release rate and a cylinder-pressure model. This feature was used to adjust fuel-injection timings, durations, and number of injections, for efficient constraint fulfillment in transient engine operation. Experimental results demonstrate that the pressure controller can also be used for tracking of cycle-resolved in-cylinder pressure trajectories, as well as finding the most efficient combustion timing.
Heat-release analysis is an essential component in the pressure-sensor feedback loop. Methods for calibrating heat-release model parameters with the use of engine data, and methods for detecting combustion timings are therefore discussed in the thesis.
The experimental results presented were conducted on a heavy-duty Scania D13 engine with a modified gas-exchange system. The fuel used was a mixture (by volume) of 80 % gasoline and 20 % n-heptane, to elevate the fuel octane number and allow for longer ignition delays.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Award date||2018 Jun 1|
|Publication status||Published - 2018 Jun 1|
Anders Holmqvist, Niklas Andersson, Anton Cervin, Anders Mannesson, Ather Gattami, Andrey Ghulchak, Alessandro Vittorio Papadopoulos, Anders Rantzer, Anders Robertsson, Aivar Sootla, ALFRED THEORIN, Bo Bernhardsson, Björn Olofsson, Björn Wittenmark, Christian Grussler, Charlotta Johnsson, Daria Madjidian, Erik Johannesson, Fredrik Magnusson, Fredrik Ståhl, Giacomo Como, Georgios Chasparis, Gabriel Turesson, Isolde Dressler, Johan Åkesson, Jang Ho Cho, Karl-Erik Årzén, Karl Johan Åström, Kin Cheong Sou, Karl Mårtensson, Karl Berntorp, Kristian Soltesz, Laurent Lessard, Martin Hast, Meike Rönn, Martin Ansbjerg Kjær, Martina Maggio, Maxim Kristalny, Olof Garpinger, Pål Johan From, Per-Ola Larsson, Pontus Giselsson, Rolf Johansson, Tore Hägglund, Vladimeros Vladimerou, Vanessa Romero Segovia, Andreas Aurelius, Gustav Cedersjö, Kaan Bür, Manfred Dellkrantz, Manxing Du, Payam Amani, Robin Larsson, William Tärneberg, Zheng Li, Lianhao Yin, Fredrik Tufvesson, Stefan Höst, Bernt Nilsson, Stig Stenström, Jens A Andersson, Stefan Diehl, Jonas Dürango, Mahdi Ghazaei Ardakani, Per-Ola Forsberg, Fredrik Bengtsson, Henrik Jörntell, Carmen Arévalo, Claus Führer, Christian Andersson, Fatemeh Mohammadi, Per Ödling, Mikael Andersson, Maria Kihl & Per Tunestål
2008/07/01 → 2018/06/30