Fast Neural Networks for Diesel Engine Control Design

摘要

Advanced engine control systems require accurate process models. This paper presents neural net models for combustion engines. After briefly introducing a special local linear RBF network (LOLIMOT) two applications are described. Different methods for developing exhaust gas models are compared and a dynamic model for the charging pressure dynamics of a turbocharger is presented. Finally, an exhaust vs. consumption optimization is presented for optimizing the injection angle dependent on givenweighting factors for specific emissions, the fuel consumtion and the current driving situation.