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Turbocharger compressors are limited in their operating range at low mass flows by compressor surge, thus restricting internal combustion engine operation at low engine speeds and high mean effective pressures. Since the exact location of the surge line in the compressor map depends on the whole gas exchange system, a safety margin towards surge must be provided. Accurate early surge detection could reduce this margin. During surge, the compressor outlet pressure fluctuates periodically. The Hurst exponent of the compressor outlet pressure is applied in this paper as an indicator to evaluate how close to the surge limit the compressor operates. It is a measure of the time-series memory that approaches zero for anti-persistence of the time series. That is, a Hurst exponent close to zero means a high statistical preference that a high value is followed by a low value, as during surge.

On-engine surge detection could help in reducing the safety margin towards surge, thus allowing higher boost pressures and ultimately low-end torque. In this paper, experimental data from a truck turbocharger compressor mounted on the engine is investigated. A short period of compressor surge is provoked through a sudden, large drop in engine load. The compressor housing is equipped with knock accelerometers. Different signal treatments are evaluated for their suitability with respect to on-engine surge detection: the signal root mean square, the power spectral density in the surge frequency band, the recently proposed Hurst exponent, and a closely related concept optimized to detect changes in the underlying scaling behavior of the signal. For validation purposes, a judgement by the test cell operator by visual observation of the air filter vibrations and audible noises, as well as inlet temperature increase, are also used to diagnose surge.

The compressor surge line of automotive turbochargers can limit the low-end torque of an engine. In order to determine how close the compressor operates to its surge limit, the Hurst exponent of the pressure signal has recently been proposed as a criterion. The Hurst exponent quantifies the fractal properties of a time series and its long-term memory. This paper evaluates the outcome of applying Hurst exponent based criterion on time-resolved pressure signals, measured simultaneously at different locations in the compression system. Experiments were performed using a truck-sized turbocharger on a cold gas stand at the University of Cincinnati. The pressure sensors were flush-mounted at different circumferential positions at the inlet of the compressor, in the diffuser and volute, as well as downstream of the compressor.