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An experimental analysis was executed on a NA (Natural Aspirated) 4-stroke gasoline engine to investigate the potential of exhaust waste energy recovery using power turbine technology for light duty application. Restrictions with decreasing diameter were mounted in the exhaust to simulate different vane positions of a VGT (Variable Geometry Turbine) and in-cylinder pressure measurements were performed to evaluate the effect of increased exhaust back pressure on intake- and exhaust pumping losses and on engine performance. Test points in the engine map were chosen on the basis of high residence time for the vehicle during the NEDC (New European Driving Cycle). The theoretically retrievable power was calculated in case a turbine is mounted instead of a restriction and the net balance was obtained between pumping power losses and recovered energy.

An acoustic one-dimensional compressor model has been developed. This model is based on compressor map information and it is able to predict how the pressure waves are transmitted and reflected by the compressor. This is later on necessary to predict radiated noise at the intake orifice. The fluid-dynamic behavior of the compressor has been reproduced by simplifying the real geometry in zero-dimensional and one-dimensional elements with acoustic purposes. These elements are responsible for attenuating or reflecting the pressure pulses generated by the engine. In order to compensate the effect of these elements in the mean flow variables, the model uses a corrected compressor map. Despite of the fact that the compressor model was developed originally as a part of the OpenWAM™ software, it can be exported to other commercial wave action models. An example is provided of exporting the described model to GT-Power™.

Analysis of pressure pulsations in ducts is an active research field within the automotive industry. The fluid dynamics and the wave transmission properties of internal combustion (IC) engine intake and exhaust systems contribute to the energy efficiency of the engines and are hence important for the final amount of CO₂ that is emitted from the vehicles. Sound waves, originating from the pressure pulses caused by the in- and outflow at the engine valves, are transmitted through the intake and exhaust system and are an important cause of noise pollution from road traffic at low speeds. Reliable prediction methods are of major importance to enable effective optimization of gas exchange systems. The use of nonlinear one-dimensional (1D) gas dynamics simulation software packages is widespread within the automotive industry. These time-domain codes are mainly used to predict engine performance parameters such as output torque and power but can also give estimates of radiated orifice noise.

A structured, semi-automatic method for reducing a high-fidelity engine model to a fast running one has been developed. The principle of this method rests on the fact that, under certain assumptions, the computationally expensive components of the simulation can be substituted with simpler ones. Thus, the computation speed increases substantially while the physical representation of the engine is retained to a large extent. The resulting model is not only suitable for fast running simulations, but also usable and updatable in later stages of the development process. The thrust of the method is that the calibration of the fast running components is achieved by use of automatically selected neural networks. Two illustrative examples demonstrate the methodology. The results show that the methodology achieves substantial increase in computation speed and satisfactory accuracy.