Meanline Modeling of Asymmetrical Twin-Scroll Turbine: Loss Coefficient Transferability Between Turbines of Different Sizes

Abstract The meanline modeling of asymmetrical twin-scroll turbocharger turbine performance has been in continuous development since its first introduction in 2008 by Daimler AG. Asymmetric turbine features scrolls of different sizes to enable high-pressure exhaust gas recirculation (EGR), which has been proven to be effective. However, the asymmetric feature of the scrolls has been identified as the major difficulty in the meanline modeling. This is particularly true at unequal-admission operating conditions, where the two volute scrolls are subjected to different magnitude of pressure and mass flow rate. Tuning a mean-line model for one particular turbine unit is usually possible, depending on the amount of flexibility in its loss sub-models. However the transferability of loss coefficients for the use of different turbine sizes has not been studied in the case of asymmetrical twin-scroll turbine. The feasibility in doing so, and the consequences, difficulties and outcomes, will be presented in this paper. The modeling work in this study will be carried out using commercial meanline tool — RITAL™ from Concepts NREC. The loss model is first tuned for the largest asymmetrical twin-scroll turbine in Daimler AG’s product line, at different admission conditions. After the model prediction has been validated with coldflow experimental data, the same loss coefficient settings are then used for performance prediction of a smaller asymmetrical twin-scroll turbine. The finding of this paper suggests that the fraction of the volute flow exit area varies with turbine admission state. The variation trend exhibits a unique function of the turbine geometry, and found to be consistent across the turbine sizes. On the other hand, the rotor loss coefficient may remain constant regardless of the turbine operation. The goal of this study is to establish the confidence level for blind performance prediction in the future.