A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers

Marcello Canova; Massimo Naddeo; Yuxing Liu; Junqiang Zhou; Yue-Yun Wang

doi:10.4271/2015-01-1288

Engine downsizing and super/turbocharging is currently the most followed trend in order to reduce CO₂ emissions and increase the powertrain efficiency. A key challenge for achieving the desired fuel economy benefits lies in optimizing the design and control of the engine boosting system, which requires the ability to rapidly sort different design options and technologies in simulation, evaluating their impact on engine performance and fuel consumption.

This paper presents a scalable modeling approach for the characterization of flow and efficiency maps for automotive turbochargers. Starting from the dimensional analysis theory for turbomachinery and a set of well-known control-oriented models for turbocharged engines simulation, a novel scalable model is proposed to predict the flow and efficiency maps of centrifugal compressors and radial inflow turbines as function of their key design parameters. The proposed approach is validated on a database of compressors and turbines for automotive boosting applications. Examples are given to illustrate how the characteristic curves can be scaled with key design parameters.

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A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers 2015-01-1288

SAE MOBILUS