TY - JOUR
AU - Filipi, Z
AB - Non-linearity of the engine system creates a challenge in building a reliable control-oriented model (COM). The main source of non-linearity is the complex nature of the combustion process. Modern engine system configurations are increasingly complex and predicting their transient response poses additional difficulty. In the present paper, a COM is developed to address the challenges and capture the behaviour of a high-degree-of-freedom engine system. Engine combustion models are created by utilizing the high-fidelity engine cycle simulation to characterize the effects of main parameters, such as turbulence, air—fuel ratio, and residual fraction, and subsequently capturing the interrelationships with artificial neural networks. Then, system dynamics are accounted for by adding manifold and actuator dynamics models. The capabilities of the proposed COM are demonstrated using a spark-ignition engine with a dual-independent cam phasing as a test case. The results indicate the model's ability to accurately predict engine responses to an arbitrary schedule of engine control inputs over the feasible operating range.
TI - High-Degree-of-Freedom Engine Modelling for Control Design Using a Crank-Angle-Resolved Flame Propagation Simulation and Artificial Neural Network Surrogate Models
JF - Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
DO - 10.1243/09596518JSCE908
DA - 2010-09-01
UR - https://www.deepdyve.com/lp/sage/high-degree-of-freedom-engine-modelling-for-control-design-using-a-5v0MCyk6Bc
SP - 747
EP - 761
VL - 224
IS - 6
DP - DeepDyve
ER -