Online system identification with adaptive design of experiment is state of the art in static black box modelling in combustion engine calibration tasks. The online modelling is fast and leads to highly accurate results. Methodically, there is little room left for further optimization of the modelling process. The remaining bottleneck is the time consuming steady state measurement. In this contribution we present online black box modelling for dynamic models and model committees. The use of dynamic models helps to avoid the time consuming steady state measurement. This leads to time saving and/or more accurate models. The benefit of the proposed procedure for online modelling of dynamic models is also shown by comparing with steady state engine operating map documentation.     «

Online system identification with adaptive design of experiment is state of the art in static black box modelling in combustion engine calibration tasks. The online modelling is fast and leads to highly accurate results. Methodically, there is little room left for further optimization of the modelling process. The remaining bottleneck is the time consuming steady state measurement. In this contribution we present online black box modelling for dynamic models and model committees. The use of dyna...     »