A numerical procedure for the calibration of a turbocharged spark-ignition variable valve actuation engine at part load

Referring to spark-ignition engines, the downsizing, coupled to turbocharging and variable valve actuation systems are very common solutions to reduce the brake-specific fuel consumption at low-medium brake mean effective pressure. However, the adoption of such solutions increases the complexity of engine control and management because of the additional degrees of freedom, and hence results in a longer calibration time and higher experimental efforts. In this work, a twin-cylinder turbocharged variable valve actuation spark-ignition engine is numerically investigated by a one-dimensional model (GT-Power™). The considered engine is equipped with a fully flexible variable valve actuation system, realizing both a common full-lift strategy and a more advanced early intake valve closure strategy. Refined sub-models are used to describe turbulence and combustion processes. In the first stage, one-dimensional engine model is validated against the experimental data at full and part load. The validated model is then integrated in a multipurpose commercial optimizer (modeFRONTIER™) with the aim to identify the engine calibration that minimizes brake-specific fuel consumption at part load. In particular, the decision parameters of the optimization process are the early intake valve closure angle, the throttle valve opening, the turbocharger setting and the spark timing. Proper constraints are posed for intake pressure in order to limit the gas-dynamic noise radiated at the intake mouth. The adopted optimization approach shows the capability to reproduce with good accuracy the experimentally identified calibration. The latter corresponds to the numerically derived Pareto frontier in brake mean effective pressure–brake specific fuel consumption plane. The optimization also underlines the advantages of an engine calibration based on a combination of early intake valve closure strategy and intake throttling rather than a purely throttle-based calibration. The developed automatic procedure allows for a ‘virtual’ calibration of the considered engine on completely theoretical basis and proves to be very helpful in reducing the experimental costs and the engine time-to-market.

[1]  Shinichi Murata,et al.  Development of a New Multi-Mode Variable Valve Timing Engine , 1993 .

[2]  D. B. Rhodes,et al.  Laminar burning speed measurements of indolene-air-diluent mixtures at high pressures and temperatures , 1985 .

[3]  Michael Fischer,et al.  Efficient Layout and Calibration of Variable Valve Trains , 2001 .

[4]  Francesco Maiani,et al.  Multi-Objective Optimization of the Timing System on a Small 2-Wheeler Engine (SOHC): Methodology and Case Study , 2014 .

[5]  G. Fontana,et al.  Variable valve timing for fuel economy improvement in a small spark-ignition engine , 2009 .

[6]  Gianluca D'Errico,et al.  Multi-objective optimization of internal combustion engine by means of 1D fluid-dynamic models , 2011 .

[7]  Koichi Fukuo,et al.  Honda 3.0 Liter, New V6 Engine , 1997 .

[8]  Ahmed S. Ashour,et al.  Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) , 2008 .

[9]  Peter Heuser,et al.  Strategies to Improve SI-Engine Performance by Means of Variable Intake Lift, Timing and Duration , 1992 .

[10]  Rassem R. Henry,et al.  Control of Engine Load via Electromagnetic Valve Actuators , 1994 .

[11]  Enrico Rigoni,et al.  NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations , 2005, Practical Approaches to Multi-Objective Optimization.

[12]  James Tuttle,et al.  CONTROLLING ENGINE LOAD BY MEANS OF LATE INTAKE-VALVE CLOSING , 1980 .

[13]  Vincenzo De Bellisa,et al.  Hierarchical 1D/3D approach for the development of a turbulent combustion model applied to a VVA turbocharged engine. Part II: combustion model , 2014 .

[14]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[15]  D. A. Santavicca,et al.  The Fractal Nature of Premixed Turbulent Flames , 1990 .

[16]  F. Gouldin An application of fractals to modeling premixed turbulent flames , 1987 .

[17]  Atsushi Watanabe,et al.  A Newly Developed Intelligent Variable Valve Timing System - Continuously Controlled Cam Phasing as Applied to a New 3 Liter Inline 6 Engine , 1996 .

[18]  Yoshihiro Fujiyoshi,et al.  A Study of Vehicle Equipped with Non-Throttling S.I. Engine with Early Intake Valve Closing Mechanism , 1993 .

[19]  John B. Heywood,et al.  Flame photographs in a spark-ignition engine☆ , 1984 .

[20]  Keiichi Maekawa,et al.  Development of a Valve Timing Control System , 1989 .

[21]  N. Fraser,et al.  Challenges for Increased Efficiency through Gasoline Engine Downsizing , 2009 .

[22]  Michael Grohn,et al.  Variable Valve Timing in the new Mercedes-Benz Four-Valve Engines , 1989 .

[23]  Min Xu,et al.  Fuel economy optimization of an Atkinson cycle engine using genetic algorithm , 2013 .

[24]  The Fractal Concept of Turbulent Flames , 1990 .

[25]  Martin Wirth,et al.  Downsizing and Stratified Operation , 2007 .

[26]  Vincenzo De Bellis,et al.  Performance optimization of a spark-ignition turbocharged VVA engine under knock limited operation , 2016 .

[27]  Fabio Bozza,et al.  Development of a Phenomenological Turbulence Model through a Hierarchical 1D/3D Approach Applied to a VVA Turbocharged Engine , 2016 .