This paper summarizes the main studies carried out by the authors for the development of indexes for remote combustion sensing applicable 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 pollutants and CO2 emissions.
Performing an efficient combustion control is crucial for efficiency increase and pollutant emissions reduction. Over the past years, the authors of this paper have developed several techniques 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 for gasoline engines). In addition, a low-cost sensor based on acoustic sensing can be integrated to support combustion indexes evaluation and other engine relevant information.
The real-time calculation of combustion indexes is 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 combustions. 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 terms of validation and applicability for real-time combustion control.
The developed methodologies have been tested and validated through a large amount of experimental tests. To run the estimation algorithms in real-time, they have been all implemented in a specifically designed rapid control prototyping system, the goal being to quantify the accuracy of the estimations and optimize the strategy implementations for the extensive use (in the near future) in modern Engine Control Modules (ECM).