Multipoint Optimisation of Radial Compressor Using Computational Fluid Dynamics and Genetic Algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Radial compressors applied in automotive turbochargers require high efficiency and pressure ratio over a wide operating range. However, due to the large number of design parameters, iterative design techniques and manual tweaking easily become arduous and unfeasible In order to account for the performance requirements and achieve the desired aerodynamic capabilities, automatic optimisation techniques have found wide application.
This paper introduces a strategy for a three-dimensional, multipoint aerodynamic shape optimisation and seeks to optimise an automotive radial compressor. In detail, the method couples the computational fluid dynamics (CFD) solver of ANSYS CFX with a genetic algorithm in MATLAB to maximise isentropic efficiency at a target operating point near surge, while ensuring no significant reduction in performance is incurred near the choke margin.
A CFD model data including inlet pipe, single flow passage, diffuser as well as volute was validated using experimental data and used for optimisation considering 13 geometrical parameters. The numerical results indicated an efficiency improvement of around 1.9 percentage points in the target optimisation region with negligible decrease in performance near the choke line. Experimental testing of the optimised compressor confirm an increase in efficiency of around 1-2 percentage points with respect to the baseline model, while peak efficiency is increased by 3.0 percentage points with the choke line remaining virtually unchanged.
Original languageEnglish
Title of host publicationGPPS-2018
Publication statusPublished - May 2018

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Compressors
Computational fluid dynamics
Genetic algorithms
Electric inductors
Aerodynamics
Shape optimization
MATLAB
Dynamic models
Pipe
Testing

Cite this

Multipoint Optimisation of Radial Compressor Using Computational Fluid Dynamics and Genetic Algorithm. / Tuechler, Stefan; Chen, Zhihang; Copeland, Colin.

GPPS-2018. 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Radial compressors applied in automotive turbochargers require high efficiency and pressure ratio over a wide operating range. However, due to the large number of design parameters, iterative design techniques and manual tweaking easily become arduous and unfeasible In order to account for the performance requirements and achieve the desired aerodynamic capabilities, automatic optimisation techniques have found wide application. This paper introduces a strategy for a three-dimensional, multipoint aerodynamic shape optimisation and seeks to optimise an automotive radial compressor. In detail, the method couples the computational fluid dynamics (CFD) solver of ANSYS CFX with a genetic algorithm in MATLAB to maximise isentropic efficiency at a target operating point near surge, while ensuring no significant reduction in performance is incurred near the choke margin.A CFD model data including inlet pipe, single flow passage, diffuser as well as volute was validated using experimental data and used for optimisation considering 13 geometrical parameters. The numerical results indicated an efficiency improvement of around 1.9 percentage points in the target optimisation region with negligible decrease in performance near the choke line. Experimental testing of the optimised compressor confirm an increase in efficiency of around 1-2 percentage points with respect to the baseline model, while peak efficiency is increased by 3.0 percentage points with the choke line remaining virtually unchanged.

AB - Radial compressors applied in automotive turbochargers require high efficiency and pressure ratio over a wide operating range. However, due to the large number of design parameters, iterative design techniques and manual tweaking easily become arduous and unfeasible In order to account for the performance requirements and achieve the desired aerodynamic capabilities, automatic optimisation techniques have found wide application. This paper introduces a strategy for a three-dimensional, multipoint aerodynamic shape optimisation and seeks to optimise an automotive radial compressor. In detail, the method couples the computational fluid dynamics (CFD) solver of ANSYS CFX with a genetic algorithm in MATLAB to maximise isentropic efficiency at a target operating point near surge, while ensuring no significant reduction in performance is incurred near the choke margin.A CFD model data including inlet pipe, single flow passage, diffuser as well as volute was validated using experimental data and used for optimisation considering 13 geometrical parameters. The numerical results indicated an efficiency improvement of around 1.9 percentage points in the target optimisation region with negligible decrease in performance near the choke line. Experimental testing of the optimised compressor confirm an increase in efficiency of around 1-2 percentage points with respect to the baseline model, while peak efficiency is increased by 3.0 percentage points with the choke line remaining virtually unchanged.

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