Experimental investigation of cyclic variations in HCCI combustion parameters for gasoline like fuels using statistical methods
•Combustion phasing is analyzed by fitting probability density functions.•Combustion stability improves on increasing intake air temperature.•Test conditions with late start of combustion have larger cyclic variations.•Large deviations from normal distribution in combustion duration for knocking/mis...
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Veröffentlicht in: | Applied energy 2013-11, Vol.111, p.310-323 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Combustion phasing is analyzed by fitting probability density functions.•Combustion stability improves on increasing intake air temperature.•Test conditions with late start of combustion have larger cyclic variations.•Large deviations from normal distribution in combustion duration for knocking/misfire.•GEV distribution covers full range of distribution shapes for combustion duration/phasing.
Homogeneous Charge Compression Ignition (HCCI) engines have potential for excellent fuel economy and extremely low emissions of NOx and PM. HCCI engines however do not have any direct control on the start of combustion timings, which makes HCCI combustion control extremely challenging. Characterization of cyclic variations of various combustion parameters is required for design and development of closed loop control of HCCI engines. Combustion stability and cycle-to-cycle variations of HCCI combustion parameters using gasoline like fuels (methanol, ethanol and butanol) were investigated in a modified four-cylinder, four-stroke engine. The experiments were conducted by varying the intake air temperature (Ti) and relative air–fuel ratio (λ) as well as engine speed. In the steady state engine operation, cylinder pressure signals for 2000 consecutive engine cycles were acquired for each test condition. From this large volume of experimental data collected, cyclic variations of various combustion parameters were analyzed. To evaluate the cycle-to-cycle variations of HCCI combustion parameters, statistical parameters such as coefficient of variation (COV) and standard deviation of each parameter were calculated for all test conditions. Combustion phasing was also analyzed by fitting different probability density functions (statistical distributions). Best-fit distribution for all test conditions can then be used for predicting and controlling the HCCI combustion timing for engine control. |
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ISSN: | 0306-2619 1872-9118 |
DOI: | 10.1016/j.apenergy.2013.05.004 |