scholarly journals A Combined Experimental and Computational Fluid Dynamics Investigation of Particulate Matter Emissions from a Wall-Guided Gasoline Direct Injection Engine

Energies ◽  
2017 ◽  
Vol 10 (9) ◽  
pp. 1408 ◽  
Author(s):  
Davide Sciortino ◽  
Fabrizio Bonatesta ◽  
Edward Hopkins ◽  
Changho Yang ◽  
Denise Morrey
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particulate Matter ◽  
Direct Injection ◽  
Gasoline Direct Injection ◽  
Direct Injection Engine ◽  
Gasoline Direct Injection Engine ◽  
Particulate Matter Emissions

Effects of direct water injection and injector configurations on performance and emission characteristics of a gasoline direct injection engine: A computational fluid dynamics analysis

2019 ◽  
Vol 21 (8) ◽  
pp. 1520-1540 ◽  
Author(s):  
Ankit A Raut ◽  
J M Mallikarjuna
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Direct Injection ◽  
Water Injection ◽  
Gasoline Direct Injection ◽  
Water Evaporation ◽  
Emission Characteristics ◽  
Performance And Emission ◽  
Gasoline Direct Injection Engine ◽  
Direct Water Injection

In-cylinder water injection is a promising approach for reducing NOx and soot emissions from internal combustion engines. It allows one to use a higher compression ratio by reducing engine knock; hence, higher fuel economy and power output can be achieved. However, water injection can also affect engine combustion and emission characteristics if water injection and injector parameters are not properly set. Majority of the previous studies on the water injection are done through experiments. Therefore, subtle aspects of water injection such as in-cylinder interaction of water sprays, spatial distribution of water vapor, and effect on flame propagation are not clearly understood and rarely reported in literature due to experimental limitations. Thus, in the present article, a computational fluid dynamics investigation is carried out to analyze the effects of direct water injection under various injector configurations on water evaporation, combustion, performance, and emission characteristics of a gasoline direct injection engine. The emphasis is given to analyze in-cylinder water spray interactions, flame propagation, water spray droplet size distribution, and water vapor spatial distribution inside the engine cylinder. For the study, the water-to-fuel ratio is varied from 0 to 1. Various water injector configurations using nozzle hole diameters of 0.14, 0.179, and 0.205 mm, along with nozzle holes of 4, 5, 6, and 7, are considered for comparison in addition to the case of no_water. Computational fluid dynamics models used in this study are validated with the available data in literature. From the results, it is found that the emission and performance characteristics of the engine are highly dependent on water evaporation characteristics. Also, the water-to-fuel ratio of 0.6 with 6 number of nozzle holes and the nozzle diameter of 0.14 mm results in the highest indicated mean effective pressure and the lowest NOx, soot, and CO emissions compared to other cases considered.

Model-based computational intelligence multi-objective optimization for gasoline direct injection engine calibration

2018 ◽  
Vol 233 (6) ◽  
pp. 1391-1402 ◽  
Author(s):  
He Ma ◽  
Ziyang Li ◽  
Mohamad Tayarani ◽  
Guoxiang Lu ◽  
Hongming Xu ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Fuel Consumption ◽  
Computational Intelligence ◽  
Direct Injection ◽  
Gasoline Direct Injection ◽  
Multi Objective Optimization ◽  
Direct Injection Engine ◽  
Engine Calibration ◽  
Gasoline Direct Injection Engine ◽  
Calibration Approach

For modern engines, the number of adjustable variables is increasing considerably. With an increase in the number of degrees of freedom and the consequent increase in the complexity of the calibration process, traditional design of experiments–based engine calibration methods are reaching their limits. As a result, an automated engine calibration approach is desired. In this paper, a model-based computational intelligence multi-objective optimization approach for gasoline direct injection engine calibration is developed, which can optimize the engine’s indicated specific fuel consumption, indicated specific particulate matter by mass, and indicated specific particulate matter by number simultaneously, by intelligently adjusting the engine actuators’ settings through Strength Pareto Evolutionary Algorithm 2. A mean-value model of gasoline direct injection engine is developed in the author’s earlier work and used to predict the performance of indicated specific fuel consumption, indicated specific particulate matter by mass, and indicated specific particulate matter by number with given value of intake valves opening timing, exhaust valves closing timing, spark timing, injection timing, and rail pressure. Then a co-simulation platform is established for the introduced intelligence engine calibration approach in the given engine operating condition. The co-simulation study and experimental validation results suggest that the developed intelligence calibration approach can find the optimal gasoline direct injection engine actuators’ settings with acceptable accuracy in much less time, compared to the traditional approach.

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