Evaluation of a Semiempirical, Zero-Dimensional, Multizone Model to Predict Nitric Oxide Emissions in DI Diesel Engines’ Combustion Chamber
| Autor: | Dimitrios T. Hountalas, Nicholas S. Savva |
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| Rok vydání: | 2016 |
| Předmět: |
Article Subject
020209 energy General Chemical Engineering Homogeneous charge compression ignition Energy Engineering and Power Technology 02 engineering and technology Diesel cycle QC251-338.5 Condensed Matter Physics Fuel injection Combustion Heat Automotive engineering Cylinder (engine) law.invention Diesel fuel Fuel Technology Internal combustion engine law 0202 electrical engineering electronic engineering information engineering Environmental science Combustion chamber Simulation |
| Zdroj: | Journal of Combustion, Vol 2016 (2016) |
| ISSN: | 2090-1976 2090-1968 |
| Popis: | In the present study, a semiempirical, zero-dimensional multizone model, developed by the authors, is implemented on two automotive diesel engines, a heavy-duty truck engine and a light-duty passenger car engine with pilot fuel injection, for various operating conditions including variation of power/speed, EGR rate, fuel injection timing, fuel injection pressure, and boost pressure, to verify its capability for Nitric Oxide (NO) emission prediction. The model utilizes cylinder’s basic geometry and engine operating data and measured cylinder pressure to estimate the apparent combustion rate which is then discretized into burning zones according to the calculation step used. The requisite unburnt charge for the combustion in the zones is calculated using the zone equivalence ratio provided from a new empirical formula involving parameters derived from the processing of the measured cylinder pressure and typical engine operating parameters. For the calculation of NO formation, the extended Zeldovich mechanism is used. From this approach, the model is able to provide the evolution of NO formation inside each burned zone and, cumulatively, the cylinder’s NO formation history. As proven from the investigation conducted herein, the proposed model adequately predicts NO emissions and NO trends when the engine settings vary, with low computational cost. These encourage its use for engine control optimization regarding NOxabatement and real-time/model-based NOxcontrol applications. |
| Databáze: | OpenAIRE |
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