Development of virtual calibration methodologies for the torque estimation strategy for a high-performance turbocharged SI engine

Stringent vehicles emissions regulations are nowadays leading to an increasing complexity in automotive products, in order to comply to the new policies about pollutants and fuel economy while preserving performances and driving comfort. Vehicles hybridization is also taking hold as an effective way to reach these new standards. In this context, simulation-based virtual calibration processes play a key role in time and costs reduction, allowing faster calibration and validation with respect to traditional test bench activities, also resulting in shorter time-to-market. This work focuses on the virtual calibration of the Engine Management System (EMS) torque estimation algorithm for a twin-turbocharged McLaren Spark-Ignition (SI) engine. This algorithm is used by the EMS to evaluate the actual engine crankshaft torque and consequently control different powertrain actuators in order to match the torque demand coming from the driver. The calibration activity presented in this work bases on the use of a one-dimensional GT-SUITE engine model as a virtual test bench to populate several lookup tables upon which the torque estimation algorithm is built. After the description of the GT-SUITE simulation environment, the model simplification for computational time purposes and the model correlation with provided engine experimental data, the torque estimation algorithm is explained in detail and the calibration process is carried on. The work concludes with the validation of the EMS torque estimation algorithm and the analysis of results obtained with the virtual calibration activity.