Abstract
A comparison of four different control-oriented models has been carried out in this paper for the simulation of the main combustion metrics in diesel engines, i.e., combustion phasing, peak firing pressure, and brake mean effective pressure. The aim of the investigation has been to understand the potential of each approach in view of their implementation in the engine control unit (ECU) for onboard combustion control applications. The four developed control-oriented models, namely the baseline physics-based model, the artificial neural network (ANN) physics-based model, the semi-empirical model, and direct ANN model, have been assessed and compared under steady-state conditions and over the Worldwide Harmonized Heavy-duty Transient Cycle (WHTC) for a Euro VI FPT F1C 3.0 L diesel engine. Moreover, a new procedure has been introduced for the selection of the input parameters. The direct ANN model has shown the best accuracy in the estimation of the combustion metrics under both steady-state/transient operating conditions, since the root mean square errors are of the order of 0.25/1.1 deg, 0.85/9.6 bar, and 0.071/0.7 bar for combustion phasing, peak firing pressure, and brake mean effective pressure, respectively. Moreover, it requires the least computational time, that is, less than 50 μs when the model is run on a rapid prototyping device. Therefore, it can be considered the best candidate for model-based combustion control applications.
Highlights
Nowadays, emission and fuel consumption reductions are the two main challenges for internal combustion engines, and in particular for diesel technology [1,2,3]
The present study addresses this research need and compares the performance of four different modeling approaches for the prediction of the main combustion metrics which are generally considered for combustion control applications, i.e., crank angle at which 50% of fuel mass has burnt (MFB50), peak firing pressure (PFP) and brake mean effective pressure (BMEP):
On the basis of the results reported in this study, a model-based combustion controller will be developed in the near future, and will be tested on the engine through the ETAS ES910 rapid prototyping device
Summary
Emission and fuel consumption reductions are the two main challenges for internal combustion engines, and in particular for diesel technology [1,2,3]. Many techniques have been proposed to achieve this aim, such as variable geometry turbocharger (VGT), high-pressure common rail systems [4,5,6,7,8], exhaust gas recirculation (EGR) [9], innovative combustion concepts such as HCCI and PCCI [10], and innovative combustion controls [11,12,13,14] As far as these solutions are concerned, model-based combustion control is expected to make a significant contribution in the near future, thanks to the possibility of its integration with the emerging Vehicle-to-Everything (V2X) architectures. The model-based control technology will be boosted by the development of new sensors and by the increasing computational performance of the new multi-core processors that are available for mobility applications.
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