This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Physical Modelling and Use of Modern System Identification for Real-Time Simulation of Spark Ignition Engines in all Phases of Engine Development
Technical Paper
2004-01-0421
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
The development of modern engine management systems makes ever-more stringent demands of the tools used. In future, the Hardware-in-the-Loop (HiL) simulation, used primarily for hardware and software tests to date, is also to be used for control function parameter adaptation tasks. This results in the need to provide highly precise, real-time-capable simulation models in all phases of the development process. This can be done by the use of modern methods for identification of non-linear, static and dynamic multi-variable systems, partly in conjunction with conventional physical model structures. In particular, artificial neural networks prove flexible in use in this case. This allows modelling dependent on the information available in the various phases of the engine development process. Thus, in the early phase, it is possible to develop engine models with computation results from complex engine simulation programs such as PROMO or GT Power. Methods of design of experiments (DOE) allow a high accuracy to be achieved with little modelling effort. Use of dynamic neural networks allows modelling for the non-stationary behaviour on the basis of measurements even where no confident statements are possible with complex simulation programs. This will be demonstrated by way of example of emissions.
This paper represents a supplement, comprising example applications of modern, non-linear identification methods, to a treatise [1] which was presented at the SAE World Congress and which predominantly deals with methods of real-
time modelling in early development phases.
Recommended Content
Authors
Topic
Citation
Krug, C., Liebl, J., Munk, F., Kämmer, A. et al., "Physical Modelling and Use of Modern System Identification for Real-Time Simulation of Spark Ignition Engines in all Phases of Engine Development," SAE Technical Paper 2004-01-0421, 2004, https://doi.org/10.4271/2004-01-0421.Also In
References
- Kämmer, A. et. al. Real-Time Engine Models Detroit SAE 2003-01-1050 SP 1749 Society of Automotive Engineers 2003
- Konrad, H. Krämer, G. Die Entwicklung der Steuerfunktionen für die BMW VALVETRONIC-Motoren (Development of BMW VALVETRONIC SI engines control functions) Mannheim Tagung Steuerung und Regelung von Fahrzeugen und Motoren, VDI-Gesellschaft Meß- und Automatisierungstechnik 2002
- Ayeb, M. Lichtenthäler, D. et. al. SI Engine Modeling Using Neural Networks Detroit SAE 980790 Society of Automotive Engineers 1998
- Schantl, R. Echtzeitsimulation der Verbrennungskraftmaschine für die Motorsteuergeräteentwicklung (Realtime simulation of SI engines for development of engine control units) Graz Diplomarbeit FH Joanneum 2002
- Schultz, J. Identifikation dynamischer Systeme mit künstlichen Neuronalen Netzen (Identification of dynamical systems with artificial neural networks) Karlsruhe Dissertation Technische Universität 1998
- Haykin, S. Neural Networks: a comprehensive foundation New York Macmillan 2 1999