Improving Real-Time SI Engine Models by Integration of Neural Approximators

Paper #:
  • 1999-01-1164

Published:
  • 1999-03-01
Citation:
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, https://doi.org/10.4271/1999-01-1164.
Pages:
14
Abstract:
Real-time models, which reflect dynamic behavior of the SI engine, are needed for building up ECU testing devices like HIL simulators. In this paper the thermodynamic processes are reduced to some basic assumptions and combined with neural approximators of testbench data. So the parameters of the approximators can be easily adapted to similar new engines, while the principle structure describing interaction of the time- and angle-based processes remains unchanged. The model has been implemented and tested in a HIL-simulator. The performance of the proposed modeling strategy could be proved by comparing measurement data from a test bench to real-time simulation results.
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