Quantification and Sensitivity Analysis of Uncertainties in Turbocharger Compressor Gas Stand Measurements Using Monte Carlo Simulation 2014-01-1651
Turbocharger hot gas stand testing is routinely carried out in the industry both to provide an experimental assessment of different designs, and to confirm to automotive OEM customers that the product meets the afore-promised levels of performance and durability. The resulting characteristics, or maps, have a hugely significant role in the correct matching of turbocharger options for engine applications. However, since these are generated from experimentally-determined values of pressure, temperature and mass flow, with each sensed variable having an inherent finite error, the uncertainty in these measured components is variously propagated through to the flow and efficiency characteristics - and the significance of this is not well recognized.
This paper addresses this concern by classifying uncertainties according to ISO standards and propagating these through to the standard compressor performance parameters using Monte Carlo simulations, in order to quantify the overall uncertainty present in a turbocharger compressor hot gas test bench. This is followed by a global sensitivity analysis to establish which parameters contribute the highest levels of uncertainty to, for instance, the compressor efficiency characteristic, thereby providing a sensitivity ranking of the most influential measurands. Finally, the analyses are combined to explain the trend in the degree of uncertainty of performance characteristics in different regions of compressor operation. The data presented herein serves as a useful point of reference such that recommendations to improve turbocharger test facilities, either in terms of measurement methods or data acquisition and sensor hardware, can be focused on the most effective areas.
Citation: Shiva Kumar, S., van Leeuwen, B., and Costall, A., "Quantification and Sensitivity Analysis of Uncertainties in Turbocharger Compressor Gas Stand Measurements Using Monte Carlo Simulation," SAE Technical Paper 2014-01-1651, 2014, https://doi.org/10.4271/2014-01-1651. Download Citation
Sathvick Shiva Kumar, Bert van Leeuwen, Aaron Costall
HAN University of Applied Sciences, Mitsubishi Turbocharger & Engine Europe, Imperial College London