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@PHDTHESIS{Vagnoni:816862,
author = {Vagnoni, Giovanni},
othercontributors = {Pischinger, Stefan and Abel, Dirk},
title = {{E}mission control concepts for connected {D}iesel
powertrains},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
reportid = {RWTH-2021-03499},
pages = {xviii, 114 Seiten : Illustrationen, Diagramme},
year = {2021},
note = {Dissertation, Rheinisch-Westfälische Technische Hochschule
Aachen, 2021},
abstract = {The increasing connectivity of future vehicles allows the
prediction of the powertrain operational profiles. This
technology can potentially improve the control of the engine
and its exhaust gas aftertreatment systems. The study
describes the development of rule- and optimization-based
algorithms, which use the a-priori knowledge of upcoming
driving events to reduce especially nitrogen oxides (NOx)
and particulate (soot) emissions. In the first part of the
work, the boosting, the Lean NOx Trap (LNT) and the Diesel
Particulate Filter (DPF) systems of a diesel powertrain are
investigated as relevant subsystems for a typical passenger
car application. Reference control strategies, based on
state-of-the-art Engine Control Unit (ECU) algorithms and
suitable predictive control logics, are compared for the
three subsystems in a Model in the Loop (MiL) simulation
environment. The simulation driving cycles are based on
Worldwide harmonized Light duty Test Cycle (WLTC) and Real
Driving Emissions (RDE) profiles. WLTC simulation results
show an improvement potential for engine-out soot and NOx
emissions of up to 5.5 $\%$ and 4.9 $\%$ respectively for
the air path case. Additionally, the developed rule-based
algorithm allows the adjustment of the NOx-soot trade-off,
while keeping the fuel consumption constant. A reduction of
the average fuel consumption in RDE of up to 1 $\%$ for the
LNT case is achieved, thanks to the avoidance of aborted
regeneration events. Similarly, also the DPF regeneration
process is improved, sparing up to 5.5 $\%$ fuel in a
representative real driving mission. In the second part of
the work, a concept for an Integrated Engine and Exhaust
Aftertreatment System Supervisory Controller is proposed for
a conventional long-haul truck. It relies on a Nonlinear
Model Predictive Control (NMPC), whose simplified Optimal
Control Problem (OCP) formulation allows its real-time
application and reduces its calibration effort. The concept
is benchmarked in the simulation environment against Dynamic
Programming (DP) techniques and finally validated at the
engine test-bench. Measurement results show the
effectiveness of the developed controller in minimizing the
powertrain operational costs, while complying with the
emission constraints at the tailpipe. The work concludes
with brief recommendations for future research directions
such as the introduction of a prediction module for the
estimation of the vehicle operational profile in the
prediction horizon and the extension of the developed
algorithms to electrified diesel powertrains.},
cin = {412310},
ddc = {620},
cid = {$I:(DE-82)412310_20140620$},
typ = {PUB:(DE-HGF)11},
url = {https://publications.rwth-aachen.de/record/816862},
}
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