Uncertainty and Measurement Sensitivity of Turbocharger Compressor Gas Stands Honeywell Turbo Technologies

Format:

Conference/Event

Author/Creator:

Guillou, Guillou, author.

Conference Name:

SAE 2013 World Congress & Exhibition (2013-04-16 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2013

Summary:

Turbocharger performance is described in terms of compressor and turbine characteristics or operating maps. Reliable definition of the compressor map requires the accurate determination of the mass flow range, the boost pressure capability, and the efficiency of the compressor. Even though computational fluid dynamics provides significant information for the design of a given compressor, field testing is required to validate the actual compressor performance that will be delivered to the end-user. Hence, the precision and accuracy of the experimental facility are of vital importance, both regarding turbocharger development and customer needs.In this paper, uncertainty analysis is carried out to evaluate the propagation of measurement errors into the calculation of compressor performance characteristics. Uncertainty equations are derived from a simplified compressor data reduction code and applied to a typical set of experimental data. The uncertainty of an entire sample compressor map is computed to evaluate the repeatability of a given set of instrumentation. Sensitivity analysis is conducted to discuss the choice of instrumentation and identify the data acceptance limits and criteria. The issues in measuring a large flow range, the high sensitivity of compressor efficiency to temperature measurements, as well as the impact from correction factors, are highlighted. The overall study intends to describe the challenges of mapping and comparing compressor maps from different gas stand designs

Notes:

Vendor supplied data

Publisher Number:

2013-01-0925

Access Restriction:

Restricted for use by site license