Assessment of turbocharger turbine unsteady flow modelling methodology on engine performance

• Main Authors: Mustafa, Ammar, Martines-Botas, Ricardo, Pesiridis, Apostolos, Chiong, Meng Soon, Rajoo, Srithar
• Format: Article
• Published: Web Portal ASME (American Society of Mechanical Engineers) 2014
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/51953/; http://dx.doi.org/10.1115/ESDA2014-20392

Although it is well known that the flow entering a turbine of a turbocharger engine is highly unsteady, engine manufacturers prefer to use turbine performance predictions that are based on steady-state performance maps, which inherently lead to inaccuracies in the turbine's behavior and mismatches between turbocharger turbines and engines. The reason for this preference is due to the turbocharger turbine design software that are generally available to engine manufacturers being based on and compatible with steady-state performance maps and this fact led researchers to investigate how the inaccuracies of this steady-state treatment of the turbine can be alleviated. To this effect, this paper investigates how modelling techniques on Ricardo Wave, a 1D gas dynamics engine simulation software, gives rise to more accurate turbine swallowing curve predictions using steady-state maps. In particular, the turbine being investigated is that of Szymko [1], which is a twin nozzleless mixed-flow turbine that is being powered by a 10 litre, 6 cylinder 4 stroke diesel engine with an operating range from 800-2000 RPM for which 800, 1200 and 1600 engine RPM relate to 40, 60 and 80Hz exhaust gas pulse frequencies at the turbine. The main investigation in this paper is to demonstrate the capability of the engine simulation software to deal with unsteady flows and specifically to show the significant effect of accounting for the volute design in the single turbine wheel entry model. The data obtained in this investigation were compared with those of Szymko [1], which offered a validated set of data to compare against.