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Research Papers: Gas Turbines: Combustion, Fuels, and Emissions

Estimation Methodology for Automotive Turbochargers Speed Fluctuations Due to Pulsating Flows

[+] Author and Article Information
Fabrizio Ponti

Department of Industrial Engineering,
University of Bologna,
Via Fontanelle 40,
Forlì 47121, Italy
e-mail: fabrizio.ponti@unibo.it

Vittorio Ravaglioli

Department of Industrial Engineering,
University of Bologna,
Via Fontanelle 40,
Forlì 47121, Italy
e-mail: vittorio.ravaglioli2@unibo.it

Matteo De Cesare

Magneti Marelli Powertrain S.p.A.,
via del Timavo 33,
Bologna 40131, Italy
e-mail: matteo.decesare@magnetimarelli.com

1Corresponding author.

Contributed by the Combustion and Fuels Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received May 4, 2015; final manuscript received May 19, 2015; published online July 7, 2015. Editor: David Wisler.

J. Eng. Gas Turbines Power 137(12), 121507 (Jul 07, 2015) (7 pages) Paper No: GTP-15-1155; doi: 10.1115/1.4030839 History: Received May 04, 2015

Turbocharging technique, together with engine downsizing, will play a fundamental role in the near future as a way to reach the required maximum performance while reducing engine displacement and, consequently, CO2 emissions. However, performing an optimal control of the turbocharging system is very difficult, especially for small engines fitted with a low number of cylinders. This is mainly due to the high turbocharger operating range and to the fact that the flow through compressor and turbine is highly unsteady, while only steady-flow maps are usually provided by the manufacturer. In addition, in passenger cars applications, it is usually difficult to optimize turbocharger operating conditions because of the lack of information about pressure/temperature in turbine upstream/downstream circuits and turbocharger rotational speed. This work presents a methodology suitable for instantaneous turbocharger rotational speed determination through a proper processing of the signal coming from an accelerometer mounted on the compressor diffuser or a microphone faced to the compressor. The presented approach can be used to evaluate turbocharger speed mean value and turbocharger speed fluctuation (due to unsteady flow in turbine upstream and downstream circuits), which can be correlated to the power delivered by the turbine. The whole estimation algorithm has been developed and validated for a light-duty turbocharged common-rail diesel engine mounted in a test cell. Nevertheless, the developed methodology is general and can be applied to different turbochargers, both for spark ignited and diesel applications.

Copyright © 2015 by ASME
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References

Figures

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Fig. 1

Location of the installed sensors

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Fig. 2

Turbocharger instantaneous speed measured using the eddy-current sensor during a test run at 2000 rpm and bmep = 20 bar

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Fig. 3

Amplitude of turbocharger speed fluctuation for tests run at 2000 rpm and different loads (evaluated using the eddy-current speed sensor)

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Fig. 6

Comparison between accelerometer (top plot) and acoustic emission (bottom plot) frequency spectra

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Fig. 4

Correlations between turbine power and turbocharger rotational speed

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Fig. 9

Filtered accelerometer spectra for acceleration (top plot) and audio signal (bottom plot)

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Fig. 10

Comparison between measured turbocharger speed (using the eddy-current sensor, blue line) and turbo speed estimated via accelerometer (black line) and audio signal (red dashed line) processing

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Fig. 15

Scheme of the complete instantaneous turbo speed estimation methodology

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Fig. 7

Compressor characteristic map

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Fig. 5

Correlation between normalized turbine power and the product between the amplitude of turbocharger speed fluctuation and turbo speed mean value

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Fig. 8

Inverted compressor map for rough turbo speed estimation

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Fig. 11

Detailed view of the comparison between measured turbocharger speed (using the eddy-current sensor) and turbo speed estimated via accelerometer (black line) and audio signal (red dashed line) processing

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Fig. 12

Comparison between acquired and filtered accelerometer signal (the selective filter based on fB estimation via spectral analysis has been applied)

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Fig. 13

Falling zero-crossing positions detected (circles) for the filtered accelerometer signal

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Fig. 14

Comparison between measured and estimated instantaneous turbo speed

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