Development and Validation of Engine Calibration Using 1D Predictive Models 2019-01-1135

Stringent emission and GHG regulations drive Diesel engine manufactures to improve hardware and control strategies every model year, lead to increasing calibration development time and cost. Although physics based models has been used in industry for decades, due to accuracy deficiency and high computational time, the usage is still limited to initial design and research phase. In order to fully utilize physics based model’s potential in calibration development with minimal data, improved techniques been shown to overcome those limitations in this paper. Phenomenological combustion and emission models along with air path dynamics are developed in GT-Suite using steady state points over engine operation area. Models are validated using data with limited data corresponding to variation in actuators and Calibration parameters to understand any limitations of using models over wide range of variations. Accuracy targets for Engine performance and NO_x emissions are set based on references from technical publications, understanding of software capability and approach used, variation from different engines, environment conditions and test cells and so on. Design of experiments is carried out using validated model on Desktop for variation in calibration parameters, environment conditions based on Engine speed and Load. DOE data generated using 1D models was analyzed using AVL CAMEO and final calibration maps are generated. Developed Calibrations are validated in Engine Test cell under similar setup conditions of simulation. With the help of this activity, MBC/Desktop Calibration can be performed in virtual world over wide range of calibration inputs and used as good starting point for physical DOE, software development and so on. New Model Based Calibration Techniques aids in developing robust calibration optimizing physical testing and reduction in development cost and time.