This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Neural Model for Real-Time Engine Volumetric Efficiency Estimation
Technical Paper
2013-24-0132
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Increasing the degrees of freedom in the air path has become a popular way to reduce the fuel consumption and pollutant emissions of modern combustion engines. That is why technical definitions will usually contain components such as multi or single-stage turbocharger, throttle, exhaust gas recirculation loops, wastegate, variable valve timing or phasing, etc. One of the biggest challenges is to precisely quantify the gas flows through the engine. They include fresh and burnt gases, with trapping and scavenging phenomena. An accurate prediction of these values leads to an efficient control of the engine air fuel ratio and torque. Fuel consumption and pollutant emissions are then minimized.
In this paper, we propose to use an artificial neural network- based model as a prediction tool for the engine volumetric efficiency. Results are presented for a downsized turbocharged spark-ignited engine, equipped with inlet and outlet variable valve timing. The calibration process that is used in this study only requires steady-state operating points. The validation stage was conducted on both steady-state and vehicle transients. Model prediction is in very good agreement with experimental results while keeping a very low calibration effort and matching embedded computational requirements. The conclusion stresses that thanks to their generic structure, neural models offer an interesting potential for generalization to even more complex technical definitions.
Recommended Content
Authors
Topic
Citation
El Hadef, J., Colin, G., Talon, V., and Chamaillard, Y., "Neural Model for Real-Time Engine Volumetric Efficiency Estimation," SAE Technical Paper 2013-24-0132, 2013, https://doi.org/10.4271/2013-24-0132.Also In
References
- Leroy , T. , Chauvin , J. , Le Solliec , G. , Corde , G. Air Path Estimation for a Turbocharged SI Engine with Variable Valve Timing American Control Conference, ACC'07 2007
- Malaczynski , G.W. , Mueller , M. , Pfeiffer , J. , Cabush , D. et al. Replacing Volumetric Efficiency Calibration Look-up Tables with Artificial Neural Network-based Algorithm for Variable Valve Actuation SAE Technical Paper 2010-01-0158 2010
- Malaczynski , G. , Mueller , M. , Pfeiffer , J. , Cabush , D. et al. Replacing Volumetric Efficiency Calibration Look-up Tables with Artificial Neural Network-based Algorithm for Variable Valve Actuation SAE Technical Paper 2010-01-0158 2010 10.4271/2010-01-0158
- El Hadef , J. , Colin , G. , Chamaillard , Y. , Talon , V. Turbocharged SI Engine Models for Control The 11th International Symposium on Advanced Vehicle Control - AVEC'12 Seoul, Korea 2012
- Eriksson , L. Modeling and Control of Turbocharged SI and DI Engines Oil & Gas Science and Technology - Rev. IFP Energies nouvelles 62 523 538 2007
- Henson , M.A. Nonlinear model predictive control: current status and future directions Computers & Chemical Engineering 23 187 202 1998 10.1016/S0098-1354(98)00260-9
- Stewart , G. , Borrelli , F. A model predictive control framework for industrial turbodiesel engine control 47th IEEE Conference on Decision and Control 2008
- Leroy , T. , Chauvin , J. , Petit , N. Motion Planning for Experimental Air Path Control of a Variable-Valve-Timing Spark Ignition Engine Control Engineering Practice 17 1432 1439 2009 10.1016/j.conengprac.2008.10.010
- Leroy , T. , Alix , G. , Chauvin , J. , Duparchy , A. et al. Modeling Fresh Air Charge and Residual Gas Fraction on a Dual Independent Variable Valve Timing SI Engine SAE Int. J. Engines 1 1 627 635 2009 10.4271/2008-01-0983
- Chauvin , J. , Grondin , O. , Moulin , P. Control Oriented Model of a Variable Geometry Turbocharger in an Engine with Two EGR loops Oil & Gas Science and Technology - Rev. IFP Energies nouvelles 66 563 571 2011
- De Nicolao , G. , Scattolini , R. , Siviero , C. Modeling the Volumetric Efficiency of IC Engines: Parametric, Non- Parametric and Neural Techniques Control Engineering Practise 4 1405 1415 1996
- Eriksson , L. , Nielsen , L. , Brugard , J. , Bergström , J. Modeling of a Turbocharged SI Engine Annual Reviews in Control 26 2002
- Hendricks , E. and Sorenson , S. Mean Value Modelling of Spark Ignition Engines SAE Technical Paper 900616 1990 10.4271/900616
- Heywood , J.B. Internal Combustion Engines Fundamentals M.-H. s. i. mechanical-engineering McGraw-Hill 1988
- El Hadef , J. , Colin , G. , Chamaillard , Y. , Olaru , S. et al. Explicit-Ready Nonlinear Model Predictive Control of the Air Path of a Turbocharged Spark-Ignited Engine 7th IFAC Symposium on Advances in Automotive Control Tokyo, Japan 2013
- Poggio , T. , Girosi , F. Networks for Approximation and Learning IEEE Proceedings 78 1481 1497 1990
- Lichtenthäler , D. , Ayeb , M. , Theuerkauf , H. , and Winsel , T. Improving Real-Time SI Engine Models by Integration of Neural Approximators SAE Technical Paper 1999-01-1164 1999 10.4271/1999-01-1164
- Ouenou Gamo , S. , Ouladsine , M. , and Rachid , A. Diesel Engine Exhaust Emissions Modelling Using Artificial Neural Networks SAE Technical Paper 1999-01-1163 1999 10.4271/1999-01-1163
- Colin , G. Control of Fast Nonlinear Systems : Application to a Turbocharged SI Engine with Variable Valve Timing PhD Thesis University of Orleans 2006
- Arsie , I. , Pianese , C. , Rizzo , G. Enhancement of Control Oriented Engine Models Using Neural Network 6th IEEE Mediterranean Conf. on Control Systems Alghero 1998
- Cybenko , G. Approximation by Superpositions of a Sigmoidal Function Mathematics of Control, Signals, and Systems 2 303 314 1989
- Jiang , S. , Nutter , D. , and Gullitti , A. Implementation of Model-Based Calibration for a Gasoline Engine SAE Technical Paper 2012-01-0722 2012 10.4271/2012- 01-0722
- Röpke , K. , von Essen , C. DoE in engine development Quality and Reliability Engineering International 24 2008 10.1002/qre.941
- Taylor , C.F. Internal-Combustion Engine in Theory and Practice, Volume 2 - Combustion, Fuels, Materials, Design 2nd MIT Press 1985 186 187