Smart rule-based diesel engine control strategies by means of predictive driving information

Abstract

The increasing connectivity of future vehicles allows the prediction of the powertrain operational profiles. This technology will improve the transient control of the engine and its exhaust gas aftertreatment systems. This article describes the development of a rule-based algorithm for the air path control, which uses the knowledge of upcoming driving events to reduce especially [Formula: see text] and particulate (soot) emissions. In the first section of this article, the boosting and the lean [Formula: see text] trap systems of a diesel powertrain are investigated as relevant sub-systems for shorter prediction horizons, suitable for Car-to-X communication range. Reference control strategies, based on state-of-the-art engine control unit algorithms and suitable predictive control logics, are compared for the two sub-systems in a model in the loop simulation environment. The simulation driving cycles are based on Worldwide harmonized Light-duty Test Cycle and Real Driving Emissions regulations. Due to the shorter, and consequently more probable, prediction horizon and the demonstrated emission improvements, a dedicated rule-based algorithm for the air path control is developed and benchmarked in the Worldwide harmonized Light-duty Test Cycle as described in the second part of this article. Worldwide harmonized Light-duty Test Cycle test results show an improvement potential for engine-out soot and [Formula: see text] emissions of up to 5.2% and 1.2%, respectively, for the air path case and a reduction of the average fuel consumption in Real Driving Emissions of up to 1% for the lean NOx trap case. In addition, the developed rule-based algorithm allows the adjustment of the desired NOx–soot trade-off, while keeping the fuel consumption constant. The study concludes with brief recommendations for future research directions, as for example, the introduction of a prediction module for the estimation of the vehicle operational profile in the prediction horizon.

Effect of porous material as heat storage medium on fuel consumption in a turbocharged gasoline engine

“…To study the engine fuel economy, the worldwide harmonized light vehicles test cycle (WLTC) is an effective cycle test method compared to steady engine testing. 26–27 Simulation and experiment methods have been used to investigate the engine fuel consumption and emission by this transient cycle test. 28–30 Chiong 30 studied the effect of twin-scroll and single-scroll turbocharger on turbine performance and fuel consumption.…”

Special issue: Symposium for combustion control 2019

“…The joint activity with the International Journal of Engine Research started in 2016 and underlined the scientific quality and high technical relevance of the presented work. The two previous special issues illustrated the spectrum of the conference, which ranged from advanced control concepts 1–4 to application-oriented contributions with on-road vehicle validation, 5 detailed control of the combustion process on a laboratory scale 6–9 to combustion process simulation. 10…”

Symposium for combustion control 2017 and 2018 special issue

“…The paper selection covers the main topics of the SCC, from advanced control concepts 2-4 to application-oriented papers with on-road vehicle validation 5,6 or detailed engine process control. [7][8][9][10] Innovative sensor and actuator technologies do not only enable greater flexibility in process control but also lead to greater complexity in future drive trains.…”

“…The paper selection covers the main topics of the SCC, from advanced control concepts 2–4 to application-oriented papers with on-road vehicle validation 5,6 or detailed engine process control. 7–10…”

“…Finally, the potential of connectivity and the availability of look-ahead information were investigated by Vagnoni et al 6 An impressive improvement of the tradeoff between fuel efficiency and emissions was demonstrated by realistic driving profiles. This leads to the conclusion that connectivity and also autonomous driving give another degree of freedom to reduce emissions and to further improve the internal combustion engine.…”