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Variable Valve Actuation: Performance Evaluation and Optimization Tools
FISITA2010/F2010B050

Authors

I. Montalto* - Fiat Powertrain Technologies S.p.A.
A. Guzzo - Università della Calabria
A. Riegel - Fiat Powertrain Technologies S.p.A.
F. De Cristofaro - Fiat Powertrain Technologies S.p.A.
A. Casavola - Università degli Studi della Calabria
S.Bova - Università della Calabria

Abstract

The development of new engines and powertrains is shaped by the ever increasing requirements of the legislator as well as the customer. Compliance with current emission legislation, low fuel consumption and pleasant driving behaviour are prerequisites for a successful product. These demands are reflected by an increasing degree of freedom of the large number of control variables and, therefore, by an increasing number of parameters that need to be calibrated. This contradicts the demand for reducing time in the engine development process, even more in ‘’Base’’ calibrations, which are a major component in spark ignition and diesel engines. Furthermore, a relevant aspect, when dealing with modern internal combustion engine control systems, is the availability of new robust engine calibration methods and tools, which potentially allow a performance boost compared to the traditional calibration practice. In this paper a software tool development methodology is presented, which assists the off-line calibration of the base algorithms like charge and torque determination, injector model, spark advance calculation, exhaust temperature estimation for catalyst protection and so on. The use of optimization tools, to speed up the calibration and verification phases, has been proved effective and it is now a current industrial practice. This tool, conceived for the Engine Control Unit (ECU) of a gasoline engine equipped with the Variable Valve Actuation (VVA) technology and developed using MathWorks Matlab software, consists of 33 automatic calibration tools. The application of this approach, compared with the best competitors techniques, has reduced the experimental test bench effort, the calibration time and has improved the estimation precision up to 4 times.

Keywords: modeling, calibration, validation, VVA, optimization

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