A Combined Physical / Neural Approach for Real-Time Models of Losses in Combustion Engines

Christian Wilhelm; Thomas Winsel; Mohamed Ayeb; Heinz J. Theuerkauf; Sven Brandt; Elmar Busche; Claudio Longo; Gunter D. Knoll

doi:10.4271/2007-01-1345

2007-04-16

A Combined Physical / Neural Approach for Real-Time Models of Losses in Combustion Engines 2007-01-1345

Reliable estimation of pumping and friction losses in modern combustion engines allows better control strategies aiming at optimal fuel consumption and emissions. Sophisticated simulation tools enable detailed simulation of losses based as well on physical and thermodynamic laws as well as on design data. Models embedded in these tools however are not real-time capable and cannot be implemented into the programs of the electronic control units (ECU's).

In this paper an approach is presented that estimates the pumping and friction losses of a combustion engine with variable valve train (VVT). Particularly the pumping losses strongly depend on the control of variable valve train by ECU.

The model is based on a combination of a globally physical structure embedding data driven sub models based on test bed measurements. Losses are separated concerning different component groups (bearings, pistons, etc.). Modularity of the model allows a simple parameterization for different engines of the same family. Additionally design data, available from the development process, are included to reduce measuring and to enhance the scalability of the model.

These models are real-time capable and can be integrated as well in HiL test systems as in ECU's to optimize fuel injection and VVT control strategies.

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A Combined Physical / Neural Approach for Real-Time Models of Losses in Combustion Engines 2007-01-1345

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