Review of combustion indexes remote sensing applied to different combustion types 2019-01-1132
This paper summarizes the main studies carried out by the authors of this paper related to the development of combustion indexes remote sensing, applied to different combustion types, i.e. conventional gasoline and diesel combustions, diesel PCCI and dual fuel gasoline-diesel RCCI.
It is well-known that the continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at complying with upcoming increasingly stringent regulations throughout the world, both for criteria pollutants and CO2 emissions.
Performing an efficient combustion control is crucial for efficiency increase and pollutant emissions reduction. In the past years, the authors of this paper have developed several techniques in order to estimate the most important combustion indexes for combustion control, without using additional cylinder pressure sensors but only using the engine speed sensor always available on board and accelerometers usually available on board gasoline engines. In addition a cost effective sensor based on acoustic sensing can be integrated to support combustion indexes evaluation and other engine relevant information.
These aspects are even more crucial for innovative Low Temperature Combustions (such as diesel PCCI or dual fuel gasoline-diesel RCCI), mainly due to the high instability and the high sensitivity to slight variations of the injection parameters that characterize this kind of combustion. Therefore the authors of this paper have applied the developed techniques not only to conventional engines (gasoline and diesel combustion), but also to engines modified for Low Temperature Combustions, with promising results in term of validation and applicability for real-time combustion control.
The developed methodology has been tested with a large number of engine tests with rapid control prototyping and has been also optimized and efficiently implemented on board a current Engine Control Module (ECM) for further validation in the near future.
Matteo De Cesare, Vittorio Ravaglioli, Filippo Carra, Federico Stola
Magneti Marelli SpA – Driveline Division, University of Bologna