This paper describes a new approach towards a model-based optimization of internal combustion engine control maps. The goals of the optimization are - at the same time - minimum fuel consumption, low emissions and a good driveability. First the structure of a torque-oriented engine management system based on control maps is described. Then, an optimization environment is developed, which calculates the basic control maps for the engine settings based on the modelled emission behaviour of the engine. The underlying nonlinear models are realized by fast neural networks. Results in both simulation and measurements prove the quality of the proposed methodology.
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