The introduction of natural gas (NG) in the road transport market is proceeding through bifuel vehicles, which, endowed of a double-injection system, can run either with gasoline or with NG. A third possibility is the simultaneous combustion of NG and gasoline, called double-fuel (DF) combustion: the addition of methane to gasoline allows to run the engine with stoichiometric air even at full load, without knocking phenomena, increasing engine efficiency of about 26% and cutting pollutant emissions by 90%. The introduction of DF combustion into series production vehicles requires, however, proper engine calibration (i.e., determination of DF injection and spark timing maps), a process which is drastically shortened by the use of computer simulations (with a 0D two zone approach for in-cylinder processes). An original knock onset prediction model is here proposed to be employed in zero-dimensional simulations for knock-safe performances optimization of engines fueled by gasoline-NG mixtures or gasoline-methane mixtures. The model takes into account the negative temperature coefficient (NTC) behavior of fuels and has been calibrated using a considerable amount of knocking in-cylinder pressure cycles acquired on a Cooperative Fuel Research (CFR) engine widely varying compression ratio (CR), inlet temperature, spark advance (SA), and fuel mixture composition, thus giving the model a general validity for the simulation of naturally aspirated or supercharged engines. As a result, the auto-ignition onset is predicted with maximum and mean error of 4.5 and 1.4 crank angle degrees (CAD), respectively, which is a negligible quantity from an engine control standpoint.

Pipitone, E., Beccari, S. (2018). A Comprehensive Model for the Auto-Ignition Prediction in Spark Ignition Engines Fueled With Mixtures of Gasoline and Methane-Based Fuel. JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER, 141(4) [10.1115/1.4041675].

A Comprehensive Model for the Auto-Ignition Prediction in Spark Ignition Engines Fueled With Mixtures of Gasoline and Methane-Based Fuel

Pipitone, Emiliano;Beccari, Stefano
2018-01-01

Abstract

The introduction of natural gas (NG) in the road transport market is proceeding through bifuel vehicles, which, endowed of a double-injection system, can run either with gasoline or with NG. A third possibility is the simultaneous combustion of NG and gasoline, called double-fuel (DF) combustion: the addition of methane to gasoline allows to run the engine with stoichiometric air even at full load, without knocking phenomena, increasing engine efficiency of about 26% and cutting pollutant emissions by 90%. The introduction of DF combustion into series production vehicles requires, however, proper engine calibration (i.e., determination of DF injection and spark timing maps), a process which is drastically shortened by the use of computer simulations (with a 0D two zone approach for in-cylinder processes). An original knock onset prediction model is here proposed to be employed in zero-dimensional simulations for knock-safe performances optimization of engines fueled by gasoline-NG mixtures or gasoline-methane mixtures. The model takes into account the negative temperature coefficient (NTC) behavior of fuels and has been calibrated using a considerable amount of knocking in-cylinder pressure cycles acquired on a Cooperative Fuel Research (CFR) engine widely varying compression ratio (CR), inlet temperature, spark advance (SA), and fuel mixture composition, thus giving the model a general validity for the simulation of naturally aspirated or supercharged engines. As a result, the auto-ignition onset is predicted with maximum and mean error of 4.5 and 1.4 crank angle degrees (CAD), respectively, which is a negligible quantity from an engine control standpoint.
2018
Settore ING-IND/08 - Macchine A Fluido
Pipitone, E., Beccari, S. (2018). A Comprehensive Model for the Auto-Ignition Prediction in Spark Ignition Engines Fueled With Mixtures of Gasoline and Methane-Based Fuel. JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER, 141(4) [10.1115/1.4041675].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/326348
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