Multi-Disciplinary Multi-Point Optimization of a Turbocharger Compressor Wheel

Abstract

The paper describes the application of an optimization method to the redesign of a turbocharger compressor wheel. The starting design presents quite high performance. Previous attempts to improve this design have shown it difficult to increase aerodynamic performance without compromising mechanical stress levels. The optimization methodology relies on the combination of a genetic algorithm, a neural network, a database, and user generated objective functions. The originality of the paper is that the optimization is not only coupled to a CFD solver, but also to a CSM solver, so that mechanical stresses can be included in the optimization objectives. A parametric model of the solid sector of the blade, back plate and bore zone is built and included in the optimization. The challenging turbocharger test case has allowed gaining experience with design objectives of different nature. The results show that the optimization has been able to improve the aero performance, while also decreasing the peak mechanical stress levels significantly.