This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Model Based On Line Optimization For Modern Engine Management Systems
Annotation ability available
Sector:
Event:
SAE Brasil
Language:
English
Abstract
Due to the emission targets of the near future engines which are currently under development have to be equipped with high sophisticated electronic engine management systems (EMS). The calibration of an EMS needs more and more expensive development capacities because of the steadily increasing number of parameters which have to be adapted with respect to the individual engine behaviour.
Under that circumstances computer based systems for automatic parameter optimisation become most urgent. The special requirements to such a system are the following:
-
reduction of development time by using effective optimisation strategies
-
better test bench utilization
-
creating a reproducable optimised parameter set by application of exact mathematical algorithms
This paper describes a system for automatic parameter optimisation called VEGA, which was developed by Carl Schenck AG in close cooperation with FEV Motorentechnik. In addition to the system overview, results of an automatic optimisation of a heavy duty truck engine are presented.
Authors
Citation
Voigt, K., "Model Based On Line Optimization For Modern Engine Management Systems," SAE Technical Paper 931668, 1993, https://doi.org/10.4271/931668.Also In
References
- Cassidy J.F. A computerised on-line approach to calculating optimum engine calibrations SAE-Paper 77078
- Tennant J.A. Cohen A.I. Rao H.S. Powell J.D.
- Boning B
- De Salis, R. Automated Data Screening for Steady-State Engine Mapping SAE-paper 930394
- Ackerl K. Hochschwarzer H. Paulweber M. Kriegler W. Bloder L. Fully automatic parameter optimisation system Wiener Motorensymp 1992
- Fletcher, R. Practical methods of optimisation John Wiley & Sons 1987
- Bartz, R. Eifler G. Kemper H. Voigt, K.U. Parameter optimisation for electronic engine control systems paper No. 93ENO17