Combustion control is one of the key factors to obtain better performances and lower pollutant emissions for diesel, spark ignition and HCCI engines.
An algorithm that allows estimating, as an example, the mean indicated torque for each cylinder, could be easily used in control strategies, in order to carry out cylinders trade-off, control the cycle to cycle variation, or detect misfires. A tool that allows evaluating the 50% of Mass Fraction Burned (MFB50), or the net Cumulative Heat Release (CHRNET), or the ROHR peak value (Rate of Heat Release), could be used to optimize spark advance or to detect knock in gasoline engines and to optimize injection pattern in diesel engines. Modern management systems are based on the control of the mean indicated torque produced by the engine: they need a real or virtual sensor in order to compare the measured value with the target one. Many studies have been performed in order to obtain an accurate and reliable over time torque estimation. The aim of this PhD activity was to develop two different algorithms: the first one is based on the instantaneous engine speed fluctuations measurement. The speed signal is picked up directly from the sensor facing the toothed wheel mounted on the engine for other control purposes. The engine speed fluctuation amplitudes depend on the combustion and on the amount of torque delivered by each cylinder. The second algorithm processes in-cylinder pressure signals in the angular domain. In this case a crankshaft encoder is not necessary, because the angular reference can be obtained using a standard sensor wheel. The results obtained with these two methodologies are compared in order to evaluate which one is suitable for on board applications, depending on the accuracy required.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:2934 |
| Date | 30 April 2010 |
| Creators | Rinaldi, Matteo <1980> |
| Contributors | Moro, Davide |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | Italian |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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