A Reduced Complexity Model for the Compressor Power of an Automotive Turbocharger

Author:

Zeng Tao1,Upadhyay Devesh2,Zhu Guoming3

Affiliation:

1. Department of Mechanical Engineering, Michigan State University, East Lansing, MI 48824 e-mail:

2. Ford Motor Company, Dearborn, MI 48124 e-mail:

3. Fellow ASME Department of Mechanical Engineering, Michigan State University, East Lansing, MI 48824 e-mail:

Abstract

Control-oriented models for automotive turbocharger (TC) compressors typically describe the compressor power assuming an isentropic thermodynamic process with fixed isentropic and mechanical efficiencies for power transmission between the turbine and the compressor. Although these simplifications make the control-oriented model tractable, they also introduce additional errors due to unmodeled dynamics. This is especially true for map-based approaches since the manufacture-provided maps tend to be sparse and often incomplete at the operational boundaries, especially at operational conditions with low mass flow rate and low speed. Extrapolation scheme is often used when the compressor is operated outside the mapped regions, which introduces additional errors. Furthermore, the manufacture-provided compressor maps, based on steady-flow bench tests, could be quite different from those under pulsating engine flow. In this paper, a physics-based model of compressor power is developed using Euler equations for turbomachinery, where the mass flow rate and the compressor rotational speed are used as model inputs. Two new coefficients, speed and power coefficients, are defined. As a result, this makes it possible to directly estimate the compressor power over the entire compressor operational range based on a single analytic relationship. The proposed modeling approach is validated against test data from standard TC flow bench tests, standard supercharger tests, steady-state, and certain transient engine dynamometer tests. Model validation results show that the proposed model has acceptable accuracy for model-based control design and also reduces the dimension of the parameter space typically needed to model compressor dynamics.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

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