Spark Ignition Engine Performance During Warm-Up

1989 ◽  
Author(s):  
A. J. Sorrell ◽  
C. R. Stone
Keyword(s):  
Engine Performance ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Warm Up

scholarly journals Spark ignition engine performance, standard emissions and particulates using GDI, PFI-CNG and DI-CNG systems

Fuel ◽  
2021 ◽  
Vol 293 ◽  
pp. 120454
Author(s):  
Mindaugas Melaika ◽  
Gilles Herbillon ◽  
Petter Dahlander
Keyword(s):  
Engine Performance ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Performance Standard

scholarly journals Numerical Study of Engine Performance and Emissions for Port Injection of Ammonia into a Gasoline\Ethanol Dual-Fuel Spark Ignition Engine

2021 ◽  
Vol 11 (4) ◽  
pp. 1441
Author(s):  
Farhad Salek ◽  
Meisam Babaie ◽  
Amin Shakeri ◽  
Seyed Vahid Hosseini ◽  
Timothy Bodisco ◽  
...  
Keyword(s):  
Numerical Study ◽  
Combustion Process ◽  
Engine Performance ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Combustion Model ◽  
Dual Fuel ◽  
Spark Ignition Engines ◽  
Performance And Emissions ◽  
Hc Emissions

This study aims to investigate the effect of the port injection of ammonia on performance, knock and NOx emission across a range of engine speeds in a gasoline/ethanol dual-fuel engine. An experimentally validated numerical model of a naturally aspirated spark-ignition (SI) engine was developed in AVL BOOST for the purpose of this investigation. The vibe two zone combustion model, which is widely used for the mathematical modeling of spark-ignition engines is employed for the numerical analysis of the combustion process. A significant reduction of ~50% in NOx emissions was observed across the engine speed range. However, the port injection of ammonia imposed some negative impacts on engine equivalent BSFC, CO and HC emissions, increasing these parameters by 3%, 30% and 21%, respectively, at the 10% ammonia injection ratio. Additionally, the minimum octane number of primary fuel required to prevent knock was reduced by up to 3.6% by adding ammonia between 5 and 10%. All in all, the injection of ammonia inside a bio-fueled engine could make it robust and produce less NOx, while having some undesirable effects on BSFC, CO and HC emissions.

Comparison of Random Forest and Neural Network in Modelling the Performance and Emissions of a Natural Gas Spark Ignition Engine

2021 ◽  
pp. 1-20
Author(s):  
Jinlong Liu ◽  
Qiao Huang ◽  
Christopher Ulishney ◽  
Cosmin E. Dumitrescu
Keyword(s):  
Neural Network ◽  
Random Forest ◽  
Natural Gas ◽  
Internal Combustion Engines ◽  
Engine Performance ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Data Driven ◽  
Ann Model ◽  
Mean Square Errors

Abstract Machine learning (ML) models can accelerate the development of efficient internal combustion engines. This study assessed the feasibility of data-driven methods towards predicting the performance of a diesel engine modified to natural gas spark ignition, based on a limited number of experiments. As the best ML technique cannot be chosen a priori, the applicability of different ML algorithms for such an engine application was evaluated. Specifically, the performance of two widely used ML algorithms, the random forest (RF) and the artificial neural network (ANN), in forecasting engine responses related to in-cylinder combustion phenomena was compared. The results indicated that both algorithms with spark timing, mixture equivalence ratio, and engine speed as model inputs produced acceptable results with respect to predicting engine performance, combustion phasing, and engine-out emissions. Despite requiring more effort in hyperparameter optimization, the ANN model performed better than the RF model, especially for engine emissions, as evidenced by the larger R-squared, smaller root-mean-square errors, and more realistic predictions of the effects of key engine control variables on the engine performance. However, in applications where the combustion behavior knowledge is limited, it is recommended to use a RF model to quickly determine the appropriate number of model inputs. Consequently, using the RF model to define the model structure and then employing the ANN model to improve the model's predictive capability can help to rapidly build data-driven engine combustion models.

scholarly journals Performance and Emissions of a Spark Ignition Engine Operated with Gasoline Supplemented with Pyrogasoline and Ethanol

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4671
Author(s):  
Luís Durão ◽  
Joaquim Costa ◽  
Tiago Arantes ◽  
F. P. Brito ◽  
Jorge Martins ◽  
...  
Keyword(s):  
Fossil Fuels ◽  
Agricultural Land ◽  
Synergistic Effects ◽  
Engine Performance ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Ternary Mixtures ◽  
Partial Replacement ◽  
Chemical Compositions ◽  
Waste Biomass

The partial replacement of fossil fuels by biofuels contributes to a reduction of CO2 emissions, alleviating the greenhouse effect and climate changes. Furthermore, fuels produced from waste biomass materials have no impact on agricultural land use and reduce deposition of such wastes in landfills. In this paper we evaluate the addition of pyrolysis biogasoline (pyrogasoline) as an additive for fossil gasoline. Pyrogasoline was produced from used cooking oils unfit to produce biodiesel. This study was based on a set of engine tests using binary and ternary mixtures of gasoline with 0, 2.5, and 5% pyrogasoline and ethanol. The use of ternary blends of gasoline and two different biofuels was tested with the purpose of achieving optimal combustion conditions and lower emissions, taking advantage of synergistic effects due to the different properties and chemical compositions of those biofuels. The tests were performed on a spark-ignition engine, operated at full load (100% throttle, or WOT—wide open throttle) between 2000 and 6000 rpm, while recording engine performance and exhaust gases pollutants data. Binary mixtures with pyrogasoline did not improve or worsen the engine’s performance, but the ternary mixtures (gasoline + pyrogasoline + ethanol) positively improved the engine’s performance with torque gains between 0.8 and 3.1% compared to gasoline. All fuels presented CO and unburned hydrocarbons emissions below those produced by this type of engine operated under normal (fossil) gasoline. On the other hand, NOx emissions from oxygenated fuels had contradictory behaviour compared to gasoline. If we consider the gains achieved by the torque with the ternary mixtures and reductions in polluting emissions obtained by mixtures with pyrogasoline, a future for this fuel can be foreseen as a partial replacement of fossil gasoline.

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