Uncertainties in power computations in a turbocharger test bench

Abstract

A specific study of the uncertainties of turbine power output measured in turbocharger test benches is presented using the law of uncertainty propagation and the influence of the different terms that contribute to it is shown. Then, non-linear mixed integer mathematical programming algorithms used with the turbine power uncertainty expression become an essential tool to overcome the problem of selection new sensors to improve an existing test rig or to contribute to a new one. A method of optimisation is presented for two different scenarios: first, where the maximum cost is a constraint; second where the maximum uncertainty is a constraint and the total cost is minimised. When using a large transducers database, computational efforts may be reduced by solving the relaxed non-integer problem by means of sequential quadratic programming and then probing the ceilings and floors of the parameters to get an optimum approximation with low costs. A comparison between the linear uncertainty propagation model and Monte Carlo simulations is also presented, only showing benefits of the later method when computing high order statistical moments of the turbine power output probability distribution.

Experimental Investigation of an Inverted Brayton Cycle for Exhaust Gas Energy Recovery

“…Since many readings have been taken at each operating point, the standard deviation of the mean is small and type A related uncertainty due to uncertainty in the mean can be ignored. This leaves only type B uncertainty, which is consistent with the approach taken in other uncertainty analyses of turbocharger test results such as Olmeda et al [35], Guillou [36] and Mohtar et al [37].…”

Turbocharger heat transfer and mechanical losses influence in predicting engines performance by using one-dimensional simulation codes

“…In Table 1 the uncertainty of the sensors is shown. The un-95 certainty due to the inaccuracy of each sensor is computed assuming uniform rectangular distribution of probability [16]. Equation 1 is used in this case.…”

Experimental approach for the characterization and performance analysis of twin entry radial-inflow turbines in a gas stand and with different flow admission conditions

“…as it is dependent on the ratio of isentropic enthalpy difference to the measured enthalpy difference between the inlet and outlet stations of the turbine and compressor. The uncertainty of the performance parameters was computed using the standard procedure described in [28] and applied in [29]. The mean and maximum values are presented in Table 3.…”