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HRR and MFB50 Estimation in a Euro 6 Diesel Engine by Means of Control-Oriented Predictive Models

Journal Article
2015-01-0879
ISSN: 1946-3936, e-ISSN: 1946-3944
Published April 14, 2015 by SAE International in United States
HRR and MFB50 Estimation in a Euro 6 Diesel Engine by Means of Control-Oriented Predictive Models
Sector:
Citation: Finesso, R., Spessa, E., Yang, Y., Alfieri, V. et al., "HRR and MFB50 Estimation in a Euro 6 Diesel Engine by Means of Control-Oriented Predictive Models," SAE Int. J. Engines 8(3):1055-1068, 2015, https://doi.org/10.4271/2015-01-0879.
Language: English

Abstract:

The paper has the aim of assessing and applying control-oriented models capable of predicting HRR (Heat Release Rate) and MFB50 in DI diesel engines. To accomplish this, an existing combustion model, previously developed by the authors and based on the accumulated fuel mass approach, has been modified to enhance its physical background, and then calibrated and validated on a GM 1.6 L Euro 6 DI diesel engine.
It has been verified that the accumulated fuel mass approach is capable of accurately simulating medium-low load operating conditions characterized by a dominant premixed combustion phase, while it resulted to be less accurate at higher loads. In the latter case, the prediction of the heat release has been enhanced by including an additional term, proportional to the fuel injection rate, in the model.
The already existing and the enhanced combustion models have been calibrated on the basis of experimental tests carried out on a dynamic test bench at GMPT-E. A comparison has been made between the models, in terms of accuracy in the prediction of HRR and MFB50, as well as of the required computational time and calibration effort, at several steady-state operating conditions as well as over NEDC and WLTP cycles.
The values of MFB50 predicted by means of the two approaches, for the same steady-state tests and driving cycles, have been compared with those obtained from a low-throughput invertible MFB50 predictive model that has recently been developed by the authors, which is characterized by an extremely low computational time.