Data maps are easy to put in place and require very low calculation time. As a consequence they are often valued over fully physic-based models. This is particularly true when it is question of turbochargers. However, even if these maps are directly provided by the manufacturer, they usually do not cover the entire engine operating range and are poorly discretized. That's why before implementing them into any model they need to be interpolated and extrapolated.This paper introduces a new interpolation/extrapolation method based on the idea of integrating more physics into the widespread Jensen and Kristensen's method [6]. It essentially relies on the turbo machinery equation analysis performed by Martin during his PhD thesis [9, 10, 11] and the interpolation and extrapolation strategies that he proposed. In most cases the new strategies presented in this paper rely on improvements of the models he proposed. However the major issue here is to associate to each model a robust algorithm to obtain the fully extrapolated data maps from the raw manufacturer's data.The major outcomes of the study are: - new models for compression ratio and turbine flow rate extrapolations and - robust and easy to implement algorithms for interpolation and extrapolation to low rotational speeds. These address single stage turbocharging configurations with fixed geometry turbines (in the case of variable geometry turbines, taking each position as a different fixed geometry turbine allow to use the same algorithms).
Physical-Based Algorithms for Interpolation and Extrapolation of Turbocharger Data Maps
Sae Int. J. Engines
SAE 2012 World Congress & Exhibition ; 2012
Sae International Journal of Engines ; 5 , 2 ; 363-378
2012-04-16
16 pages
Conference paper
English
Physical-Based Algorithms for Interpolation and Extrapolation of Turbocharger Data Maps
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