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The optimization of turbocharging systems for automotive applications has become crucial in order to increase engine performance and meet the requirements for pollutant emissions and fuel consumption reduction. Unfortunately, performing an optimal turbocharging system control is very difficult, mainly due to the fact that the flow through compressor and turbine is highly unsteady, while only steady flow maps are usually provided by the manufacturer. For these reasons, one of the most important quantities to be used onboard for optimal turbocharger system control is the rotational speed fluctuation, since it provides information both on turbocharger operating point and on the energy of the unsteady flow in the intake and exhaust circuits. This work presents a methodology that allows determining the instantaneous turbocharger rotational speed through a proper frequency processing of the signal coming from one accelerometer mounted on the turbocharger compressor.

The paper presents a non-intrusive, indirect and low-cost methodology for a real time on-board measurement of an automotive turbocharger rotational speed. In the first part of the paper the feasibility to gather information on the turbocharger speed trend is demonstrated by comparing the time-frequency analysis of the acoustic signal with the direct measurement obtained by an optical sensor facing the compressor blades, mounted in the compressor housing of a spark ignited turbocharged engine. In the second part of the paper, a real time algorithm, to be implemented in the engine control unit, is proposed. The algorithm is able to tune on the turbocharger revolution frequency and to follow it in order to extract the desired speed information. The frequency range containing the turbocharger acoustic frequency can be set utilizing a raw estimation of the compressor speed, derived by its characteristic map.

The present paper is about the rotational speed measurement of an automotive turbocharger, obtained starting from the analysis of acoustic emission produced by an engine, which have been acquired by a microphone placed under the vehicle hood. In the first part of the paper several upgrades to increase the overall performance of the speed extraction algorithm are presented and discussed, starting from the basic algorithm that has already demonstrated the methodology capability in a previous paper. In particular it has been considered a different signal sampling rate in order to extend the applicability of the methodology to a wider range of engines. Also a new processing procedure has been defined to increase the capability of the algorithm to tune on the frequency signal.