Statistical Analysis of Data Acquired from Propagating Flames in Gasoline Engines Using a Multiple Ion Probe

Multiple-ion-probe method consists of multiple ion probes placed on the combustion chamber wall, where each individual ion probe detects flame contact and records the time of contact. From the recorded data, it is also possible to indirectly visualize the inside of the combustion chamber, for example, as a motion animation of moving flame front. In this study, a thirty-two ion probes were used to record flames propagating in a two-stroke gasoline engine. The experiment recorded the combustion state in the engine for about 3 seconds under full load at about 6500 rpm, and about 300 cycles were recorded in one experiment. Twelve experiments were conducted under the same experimental conditions, and a total of 4,164 cycles of signal data were obtained in the twelve experiments. Two types of analysis were performed on this data: statistical analysis and machine learning analysis using a linear regression model. Statistical analysis calculated the average flame detection time and standard deviation of the flame detection time for all cycles, and confirmed that there is a strong correlation between them. The results show that the flame propagates with little turbulence immediately after ignition, and that the degree of turbulence increases with time. Analysis using machine learning with linear regression models revealed that the flame propagation state of a given cycle affected up to two cycles backward in the two-stroke gasoline engine tested.