Hybridization and Splitting of a Crank Angle Resolved Internal Combustion Engine Model Using a Mean Value Intake for Real-time Performance

This document explores the development of a real-time capable crank-angle resolved internal combustion engine simulation framework using Dymola and Modelica by combining detailed combustion models with a calibrated mean value intake model.

The research focuses on overcoming the computational challenges associated with splitting highly coupled air path and combustion models across multiple processor cores for Hardware-in-the-Loop (HiL) applications. By replacing complex fluid-based intake models with dynamically calibrated mean value models and automated lookup table generation techniques, the study demonstrates how accurate intake manifold pressure, airflow, AFR dynamics, and cylinder pressure behaviour can be reproduced while significantly improving simulation speed and real-time performance. The work also introduces control-based automated calibration methods that reduce calibration effort, improve robustness during transient operating conditions, and enable efficient deployment of high-fidelity engine models on real-time Concurrent simulation hardware.