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PROJECT TITLE :

Optimal-Behavior-Based Dynamic Calibration of the Automotive Diesel Engine

ABSTRACT:

This paper presents a completely unique automotive engine management system (EMS) calibration methodology for speedy dynamometer take a look at-bed information collection and mapping I.C. engine controllers with vital dynamic and transient performance necessities. This paper applies the methodology to an industrial cutting-edge WAVE-RT1 model of a 1.five L Turbo EU6.one Diesel engine acting as a virtual dynamometer based mostly engine. The approach directly yields a feedforward controller in a very nonlinear polynomial structure which will be either directly implemented within the EMS or converted into a dynamic or static lookup table format. The methodology is predicated on multistage black-box modeling and dynamic system optimization. The method can exploit the power of global constrained numerical optimization codes and use system identification techniques with dynamic design of experiments. The objective of the engine controller optimization is to improve the fuel economy whereas maintaining specified (legislated) limits on emissions and map smoothness for driveability. The key contribution is a novel approach to getting a feedforward dynamic calibration controller from the system identification of the computed optimal behavior. Model structure selection techniques are shown to be usefully used to further improve the accuracy of the system identification and thus enhance the management performance of the dynamic controllers. The results indicate that the dynamic calibration methodology results in a considerably reduced demand for testing time and an improvement of between one.nine% and a couple of.six% in fuel economy over additional urban driving cycle without violating the emission constraints compared with current steady-state model-based mostly calibration ways.1Ricardo PLC.


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