Improvements in Off Design Aeroengine Performance Prediction Using Analytic Compressor Map Interpolation

Misté, Gianluigi Alberto; Benini, Ernesto

doi:10.1515/tjj-2012-0012

Cited by 8 publications

(9 citation statements)

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“…One common way of treating compressor maps is to introduce beta-lines [9,[12][13][14], which span the map, roughly parallel to the surge line on one side and the choke line on the other. An important drawback is that data will either need to be truncated from some speed lines, or extrapolated in others, although some works have improved the implementation of beta-lines, e.g., [13]. This study focuses on the consequences for interpolation of different map formats, so extrapolation was excluded.…”

Section: Mapping Algorithmmentioning

confidence: 99%

A Flow and Loading Coefficient-Based Compressor Map Interpolation Technique for Improved Accuracy of Turbocharged Engine Simulations

Gharaibeh

Costall

2017

SAE Technical Paper Series

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Internal combustion engines are routinely developed using 1D engine simulation tools. A well-known limitation is the accuracy of the turbocharger compressor and turbine sub-models, which rely on hot gas bench-measured maps to characterize performance. Such discrete map data is inherently too sparse to be used directly in simulation, and so a preprocessing algorithm interpolates and extrapolates the data to generate a wider, more densely populated map. Methods used for compressor map interpolation vary. They may be mathematical or physical in nature, but there is no unified approach, except that they typically operate on input map data in SAE format. For decades it has been common practice for turbocharger suppliers to share performance data with engine OEMs in this form. This paper describes a compressor map interpolation technique based on the nondimensional compressor flow and loading coefficients, instead of SAE-format data. It compares the difference in compressor operating point prediction accuracy when using this method against the standard approach employing dimensional parameters. This is done by removing a speed line from a dataset, interpolating for the removed speed using the two methods, and comparing their accuracy to the original data. Three maps corresponding to compressor diameters of 54, 88, and 108 mm were evaluated. In some cases, the residual sum of squares between the interpolated and original data demonstrated an order of magnitude improvement when using the nondimensional coefficients. When evaluated in a simple engine model, this manifests as a slight shift in interpolated turbocharger speed, resulting in a difference in predicted compressor efficiency of up to 0.89 percentage points. This paper shows how the use of truly nondimensional interpolation techniques can improve the accuracy of processed turbocharger compressor maps, and consequently the value of 1D engine simulations as a reliable performance development tool, at virtually no additional effort or cost.

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Section: Mapping Algorithmmentioning

confidence: 99%

A Flow and Loading Coefficient-Based Compressor Map Interpolation Technique for Improved Accuracy of Turbocharged Engine Simulations

Gharaibeh

Costall

2017

SAE Technical Paper Series

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“…Hence, in this paper, the ANN predicts values of t s from which t is computed using the inverse of equation (10). Table 1 summarizes t min and t max .…”

Section: Neural Network Trainingmentioning

confidence: 99%

Application of integrated fuzzy logic and neural networks to the performance prediction of axial compressors

Gholamrezaei

Ghorbanian

2015

Proceedings of the Institution of Mechanical Engineers, Part A:

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An integrated fuzzy logic-neural network methodology is presented as a mean to improve the reconstruction of the performance map of axial compressors and fans. The learning capability of artificial neural network technique is integrated to the knowledge aspect of fuzzy inference system to offer enhanced prediction capabilities compared to using a single methodology independently. The proposed technique incorporates information of experimental data on surge, operating, and choke lines at any arbitrary but fixed rotational speed. A comparison of the predicted results with experimental data reveals a very good agreement. The proposed technique has the capability to model the nonlinear surge line as well as the kink in the performance map. Application of the method for compressor map generation showed that the proposed technique is robust and capable of enhancing any performance simulation tool used for the dynamic simulation and condition monitoring.

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“…Once tabulated, these values are the data source used to draw compressor map plots. To trace the ß lines different mathematical functions can be employed (e.g., equispaced parabolas [12], bivariate linear or more complex functions [13], etc. When choosing the two variables to define the operating point, it is necessary that they are not collinear and are able to produce a unique operating point.…”

Section: Gas Turbine Off Design Performancementioning

confidence: 99%

“…[13]. Some information related to the compressor map characteristics is derived from the results' output by an engine deck.…”

Section: Setting the Initial Turbojet Enginementioning

confidence: 99%

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Turbojet Engine Performance Tuning With a New Map Adaptation Concept

Misté

Benini

2014

Journal of Engineering for Gas Turbines and Power

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Gas turbine off design performance prediction is strictly dependent on the accuracy of compressor and turbine map characteristics. Experimental data regarding component maps are very difficult to find in literature, since it is undisclosed proprietary information of the engine manufacturers. To overcome this limitation, gas turbine engineers use available generic component maps and modify them to reach the maximum adherence with the experimental measures. Different scaling and adaptation techniques have been employed to this aim; these methodologies are usually based upon analytic regression models which minimize the deviation from experimental data. However, since these models are built mainly for a specific compressor or turbine map, their generalization is quite difficult: in fact, regression is highly shape-dependent and, therefore, requires a different model for each different specific component. This paper proposes a solution to the problem stated above: a new method for map adaptation is investigated to improve steady-state off design prediction accuracy of a generic gas turbine component. The methodology does not employ analytical regression models; its main principle relies in performing map modifications in an appropriate neighborhood of the multiple experimental points used for the adaptation. When using gas turbine simulation codes, component maps are usually stored in a data matrix and are ordered in a format suitable for 2D interpolation. A perturbation of the values contained in the matrix results in component map morphing. An optimization algorithm varies the perturbation intensity vector in order to minimize the deviation between experimental and predicted points. The adaptation method is integrated inside TSHAFT, the gas turbine prediction code developed at the University of Padova. The assessment of this methodology will be exposed by illustrating a case study carried out upon a turbojet engine

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Improvements in Off Design Aeroengine Performance Prediction Using Analytic Compressor Map Interpolation

Cited by 8 publications

References 0 publications

A Flow and Loading Coefficient-Based Compressor Map Interpolation Technique for Improved Accuracy of Turbocharged Engine Simulations

A Flow and Loading Coefficient-Based Compressor Map Interpolation Technique for Improved Accuracy of Turbocharged Engine Simulations

Application of integrated fuzzy logic and neural networks to the performance prediction of axial compressors

Turbojet Engine Performance Tuning With a New Map Adaptation Concept

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