Multidisciplinary Multipoint Optimization of a Transonic Turbocharger Compressor

Abstract

A transonic centrifugal compressor for turbocharger applications has been redesigned by means of a multidisciplinary multipoint optimization system composed of: a 3D Navier-Stokes solver, a Finite Element stress Analyzer, a Genetic Algorithm and an Artificial Neural Network. The latter makes use of a database, containing the geometry and corresponding performance of previously analyzed impellers and allows a considerable reduction in computational effort. The performance of every new geometry is verified by a 3D Navier-Stokes solver. A Finite Element Analysis verifies the mechanical integrity of the impeller. The geometrical description of the impeller has been extended to better adapt the inducer part of the impeller to transonic flows. The splitters are no longer copies of the full blades but specially designed for minimum losses and equal mass flow on both sides. The blade thickness and number of blades are unchanged because defined by robustness and inertia considerations. The operating range is guaranteed by a two-step optimization procedure. The first one provides information allowing a modification of the inlet section to guarantee the required choking mass flow and a more accurate prediction of the boundary conditions for the Navier-Stokes analysis of the modified impeller. The second one predicts the performance curve of the new geometry for which the choking mass flow is known. It is shown how these extensions of the optimization method have led to a considerable improvement of the efficiency and corresponding pressure ratio, while respecting the surge and choking limits without increase of the stress level.

Aerodynamic Design Optimization of a Micro Radial Compressor of a Turbocharger

“…The Mach number distributions on the blade surface and passage could aid in understanding how the efficiency of the compressor increased owing to optimization of the beta distribution. The lower suction side Mach number distribution at the shroud leads to a reduction in shock losses, and shock boundary layer interaction losses in the blade passage therefore improved efficiency, as expected [16]. In this study, remarkable changes were observed in the shroud rather than in the hub.…”

“…In the standard geometry definition of the radial impeller, the parameterized hub and shroud curves coupled with beta distribution, which is the angle between the meridional plane (m) and blade camber line (s) (Figure 1), are generally considered [16]. In this study, in particular, the beta distribution itself on the main blade is parameterized and investigated with additional parameters of the splitter leading edge to optimize the compressor aerodynamically.…”

“…Therefore, selecting the most influential design parameters could lead to better optimization performance [16]. In the conventional design optimization process of the impeller, the hub and shroud profiles of the main blade, which are defined by the Bezier curve method [17], are commonly examined, and splitter blades are considered as short versions of the main blade to provide equal flow passage in the impeller.…”

“…In addition, another limitation is considered for the lean angle (rake angle) during the designing of the compressor (Figure 3). The maximum lean angle is set as 45° [16] from axial owing to a manufacturing issue. To calculate the lean angle, first, the blade camber line circumferential angle θ needs to be obtained by Equation (3).…”

An Integrated Design and Optimization Approach for Radial Inflow Turbines—Part II: Multidisciplinary Optimization Design

“…The differential evolution algorithm and the artificial neural network (ANN) were used to improve the efficiency and reduce the impeller inertia while limiting the stress to an allowable level at reasonable computational cost. Van den Braembussche et al [11] conducted a multidisciplinary multipoint optimization for a transonic turbocharge compressor. The operating range is guaranteed by a two-step optimization procedure.…”