The Application of Vibroacoustic Mean and Peak-to-Peak Estimates to Assess the Rapidly Changing Thermodynamic Process of Converting Energy Obtained from Various Fuel Compositions Using a CI Engine

This paper presents the effectiveness of representing the process of creating and burning a combustible mixture in vibroacoustic parameters of a compression ignition engine. Empirical engine tests allowed us to conduct analyses in terms of the operating conditions, fuel parameters, and fuel type. The influence of dimethyl ether on combustion efficiency was quantified using performance indicators, emission parameters, and vibration estimates (compared to diesel fuel). Mathematical models of combustion and its variability were created using the mean, peak-to-peak amplitude, root mean square error, and peak amplitudes of vibration accelerations, which were also represented using vibration graphics. Dimethyl ether positively influenced engine performance, emissions, and vibration reduction. The proposed method can predict combustion irregularities and detect their sources in engine designs with high kinetic energy, hybrid combustion modeling, and fuel composition identification. Dimethyl ether reduced hydrocarbons by 96–99%, particulate matter by 37–60%, and carbon monoxide by 2.5–19.5%, whereas nitrogen oxides increased by 1–8% (relative to diesel fuel). Emission models were created with accuracies of 0.88–0.96 (hydrocarbons), 0.80–0.98 (particulate matter), 0.95–0.99 (carbon monoxide), and 0.97–0.99 (nitrogen oxides). Dimethyl ether application reduced the mean amplitude of the vibrations in the range of 5.7–60.6% and the peak-to-peak amplitude in the range of 18.2–72.4%. The standard deviation of combustion was decreased by 8.8–49.1% (mean) and by 28.8–39.5% (peak-to-peak). The vibroacoustic models’ accuracy scores were 0.90–0.99 (diesel fuel) and 0.72–0.75 (dimethyl ether).