The gas exchange processes of engines are becoming increasingly complex since modern engines leverage technologies including variable valve actuation, turbochargers, and exhaust gas recirculation. Control of these many devices and the underlying gas flows is essential for high efficiency engine concepts. If these processes are to be controlled and estimated using model-based techniques, accurate models are required. This work explores a model framework that leverages a data-driven model of the turbocharger along with submodels of the intercooler, intake and exhaust manifolds and engine processes to provide cylinder-specific predictions of the pressure and temperatures of the gases across the system. This model is developed and validated using data from a 2.0 liter VW turbocharged, direct-injection diesel engine and shown to provide accurate prediction of critical gas properties.

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