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Technical Paper

Modeling Waves in ICE Ducts: Comparison of 1D and Low Order Models

Abstract The paper presents a comparative study of various models used to estimate gas dynamics in internal combustion engine (ICE) ducts. 1D models provide a sufficient accuracy, but they are still not implementable on current ECUs. On the other hand, low order models can be real-time but their lack of accuracy and high calibration cost are still a challenging problem. This work aims at presenting a comparison of currently used gas dynamics models to predict transient phenomena in engine ducts. It emphasizes on 1D and low order models. To test under engine-like conditions, the intake path of a virtual engine implemented in GT-Power and a production two cylinder engine are used. Results show a contrast in the performance of the different models, which gives the possibility to evaluate the various approaches. Based on this assessment and depending on the application in hand, the models can be chosen properly to estimate the gas dynamics in internal combustion engine ducts.
Technical Paper

Incorporating Thermo- and Aerodynamic Losses into Compressor Models for Real-Time Applications

Abstract Compressor models play a major role as they define the boost pressure in the intake manifold. These models have to be suitable for real-time applications such as control and diagnosis and for that, they need to be both accurate and computationally inexpensive. However, the models available in the literature usually fulfill only one of these two competing requirements. On the one hand, physics-based models are often too complex to be evaluated on line. On the other hand, data-based models generally suffer insufficient extrapolation features. To combine the merits of these two types of models, this work presents an extended approach to compressor modeling with respect to thermo- and aerodynamic losses. In particular, the model developed by Martin et al. [1] is augmented to explicitly incorporate friction, incidence and heat transfer losses. The resulting model surpasses the extrapolation properties of data-based models and facilitates the generation of extended lookup tables.