Energy Conversion and Management 172 (2018) 67–80             

Characterization of combustion anomalies in a hydrogen-fueled 1.4 L commercial spark-ignition engine by means of in-cylinder pressure, block-engine vibration, and acoustic measurements


Abnormal combustion phenomena are among the main hurdles for the introduction of hydrogen in the transportation sector through the use of internal combustion engines (ICEs). For that reason the challenge is to guarantee operation free from combustion anomalies at conditions close to the ones giving the best engine output (maximum brake torque and power). To this end, an early and accurate detection of abnormal combustion events is decisive in order to allow the electronic control unit deciding suitable correcting actions. In this work, an automotive size 4-cylinder 1.4 L naturally aspirated port-fuel injection spark ignition Volkswagen engine adapted to run on hydrogen has been investigated.

Three distinct methods (in-cylinder pressure, block-engine vibration and acoustic measurements) have been employed to detect abnormal combustion phenomena provoked through the enrichment of the hydrogen-air mixture fed to the cylinders under a wide range of engine speeds (1,000-5,000 rpm). It has been found that the high-frequency components of the in-cylinder pressure and block engine acceleration signals obtained after a Fourier transform analysis can be used for very sensitive detection of knocking combustion cycles. In the case of the ambient noise measurements, a spectral analysis in terms of third octave bands of the signal recorded by a microphone allowed an accurate characterization. Combustions anomalies could be detected through more intense octave bands at frequencies between 250 Hz and 4 kHz in the case of backfire and between 8 kHz and 20 kHz for knock. Computational fluid dynamics simulations performed indicated that some characteristics of the engine used such as the cylinder valves dimensions and the hydrogen flow rate delivered by the injectors play important roles conditioning the likelihood of suffering backfire events.