Vincenzo Alfieri

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

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 1.6L 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

Feedback linearization control for the air & charging system in a diesel engine

The air and charge subsystem of a diesel engine is a quite complex system with strong couplings, actuator constraints, and fast dynamics. MIMO model based control strategies are essential to deal with such a process. Furthermore, the air-path process is highly nonlinear, based on thermodynamical phenomena. Therefore, classical linear MIMO approaches are difficult to be applied and require system linearization over equilibrium operating points. Conversely, feedback linearization control can be applied smoothly. In this paper, an air and charging model-based multivariable control approach is described, which has been developed for a single-stage turbocharged diesel architecture, enabling an improved trade-off of NOx and PM (particulate matter) emissions and better transient performances. The developed approach uses a nonlinear physics-based model of the air and charging system, and the control architecture is based on the feedback linearization technique that decouples interactions and compensates nonlinearities. The nonlinear control is then coupled with PI controllers in order to guarantee the transient performances and robustness. Test-bench results show the effectiveness of the proposed approach.