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This paper presents a novel approach in real-time engine modeling. Unlike standard practices, which involve system level modeling, the presented methodology is a hybrid physical/system domain solution. Specifically, for each subsystem that the engine is divided into, a physical, map-based, or combination physical/map-based solution is chosen depending on the available computational power and the desired model detail. The resulting semi-physical engine models are suitable for real-time applications, such as Hardware-In-Loop (HiL) simulations, and, at the same time, re-usable to a large extent when model updates are required. In addition, since the proposed methodology allows for variable level of detail -from models as simple as pure map-based look-ups for torque, airflow, and exhaust temperature, all the way to models capable of predicting crank angle resolved cylinder pressure- it provides natural adjustability to the ongoing growth of computer power.

Engines and vehicle systems are becoming increasing complex partly due to the incorporation of emission abatement components as well as control strategies that are technologically evolving and innovative to keep up with emissions requirements. This makes the testing and verification with actual prototypes prohibitively expensive and time-consuming. Consequently, there is an increasing reliance on Software-In-the-Loop (SIL) and Hardware-In-the-Loop (HIL) simulations for design evaluation of system concepts. This paper introduces a methodology in which detailed chemical kinetic models of catalytic converters are transformed into fast running models for control design, calibration or real time ECU validation. The proposed methodology is based on the use of a hybrid, structured, semi-automatic scheme for reducing high-fidelity models into fast running models.