Product development using virtual technology is getting more important in automotive industry. In engine development, virtual methodologies are widely used in emission field such as RDE. However the application for engine calibration supported by virt...
Product development using virtual technology is getting more important in automotive industry. In engine development, virtual methodologies are widely used in emission field such as RDE. However the application for engine calibration supported by virtual model is not commonly used so far despite of its great potential. In this study, engine calibration combining experimental dataset and virtual models were investigated to find out the potential of calibration efficiency and robustness. Two cases calibration against extreme environmental conditions such as very low temperature and high altitude were investigated to apply to mass production projects. One was turbocharger boost control open-loop calibration and the other was ignition correction calibration according to coolant and intake air temperature. In both applications, the dataset from virtual models are successfully linked to existing calibrations methodology. Promising calibration DCM could be achieved in each application. It can be shown from this study that engine calibration by virtual engine at certain surrounding condition is sufficiently beneficial in terms of time and cost. After a number of validation experiences, it can be expected that some calibration can be eventually replaced by virtual methodology and its coverage will grow gradually