Aronis, A., Cogo, V., Nora, M., Martins, M. et al., "Encoderless Data Acquisition System Applied to the Combustion Analysis of an Engine Operating on HCCI Combustion Mode," SAE Technical Paper 2017-36-0427, 2017.
Internal Combustion Engines (ICE) have their use highly disseminated in the most diverse operations. Exhaust gaseous emissions and fuel consumption have been on the scope for decades and therefore the necessity for research on more efficient and lower exhaust emission engines has increased. Considering the cost of equipment and software to develop ICE, the use of computational models is a key strategy to evaluate the behavior of the powertrain/vehicle and lower the instrumentation cost. In this sense, the present work shows the development of an algorithm to obtain a high-resolution crank angle (CA) position of an engine by means of a toothed wheel instead of a high-resolution incremental or absolute encoder. As a result, it enabled the analysis of performance and combustion parameters based on in-cylinder pressure signals acquired through a piezoelectric pressure transducer and the angular position of the crank train referenced by a Hall Effect sensor. The algorithm was built on MATLAB® and was used to generate the reference CA to the pressure signal. This data was compared to the standard results referenced by an incremental encoder with a 3600 pulses per revolution (0.1 degree/pulse). The top dead center position was found by means of thermodynamic calculations and compared to the mechanical reference. The in-cylinder pressure was dynamically pegged to the averaged intake manifold pressure, while the ratio of specific heats (gamma) was individually calculated for compression and expansion strokes. The data acquisition resolution was enhanced by digitally dividing the 60-2 toothed wheel into 3600 intervals. The comparison between the indicated mean effective pressure obtained by this means and that acquired through the commercial data acquisition system demonstrated a coefficient of correlation higher than 99% averaged on 100 consecutive cycles.