Novel methodology for the optimisation of turbocharger turbine design for improved engine performance

Abstract

Turbocharging has established itself as a key technology in the downsizing of internal combustions engines, with the aim of reducing fuel consumption and tailpipe emissions. For a turbocharger to be effective, both the compressor and the turbine need to be care- fully designed to match the engine’s requirements. This thesis presents a methodology for modelling the effect of turbine design on the engine performance, enabling an optimised match to be found. This ultimately leads to a turbine design which is tailored to the engine it is used for, as opposed to being selected from already available components. The process for selection of a turbocharger turbine has in recent years become en- hanced through the use of 1-D engine modelling, a method which uses the 1D Euler equations to predict the instantaneous gas exchange in the intake and exhaust systems of the engine. The turbocharger is modelled using maps of its performance parame- ters which are usually determined experimentally on a test bench. The methodology presented in this thesis replaces these maps with a meanline model which, using basic design parameters, solves the velocity triangles of the turbine for the mean flow path, and implements loss models to predict turbine performance. The meanline model developed for this work was validated against CFD results and test data, for turbine designs stemming from a parametric 3D turbine model. Three tur- bine design parameters were sampled and calculated by CFD, providing a dataset which enabled an assessment of the predictive capability of the meanline model. Subsequently, six turbine designs with variations of the same parameters were manufactured using rapid prototyping techniques, and tested on a cold testing facility. The results showed that the meanline model was able to predict efficiency and mass flow to within 3% across a range of designs and operating points, given data of a baseline design for calibration. The model was integrated into a 1-D model of a turbocharged gasoline engine and used to predict the impact of the meanline turbine design parameters on three aspects of engine performance: fuel consumption, low end torque and transient response. The insight given into the effect of each design parameter in the study allowed three optimised designs to be selected for the engine, representing three different trade-offs on performance, with fuel savings of up to 0.6%.