Algorithms and architectures for self-calibration of engines

Engine Management Systems (EMS) is getting more complicated each year with new functions being introduced due to tighter emission regulations of both air quality and CO2. This directly a ects the calibration process of a powertrain because the number of vehicle parameters has increased about 10 times in the last 10 years. Self-calibrating feature such as proposed in this thesis has the potential to increase the e ciency of calibrating a complex EMS. The feature is intended to adapt itself to the engine behaviour and performance by continuously updating its calibration maps as the engine is being operated. This process will reduce the needs for new calibration data and additional ne-tuning when an EMS is being carried over to a di erent vehicle. The self-calibrating feature automatically adjusts the air path calibration maps of an engine. It adjusts the air path setpoint maps in real-time for steady state operating conditions. [Continues.]