The Effect of Engine Operating Conditions on Engine-out Particulate Matter from a Gasoline Direct-injection Engine during Cold-start.

Author(s):  
Ian Whelan ◽  
William Smith ◽  
David Timoney ◽  
Stephen Samuel
2017 ◽  
Vol 61 (4) ◽  
pp. 329-341 ◽  
Author(s):  
Maria Bogarra ◽  
Jose Martin Herreros ◽  
Cruz Hergueta ◽  
Athanasios Tsolakis ◽  
Andrew P. E. York ◽  
...  

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Samuel Ayad ◽  
Swapnil Sharma ◽  
Rohan Verma ◽  
Naeim Henein

Detection of combustion-related phenomena such as misfire, knock, and sporadic preignition is very important for the development of electronic controls needed for the gasoline direct injection engines to meet the production goals in power, fuel economy, and low emissions. This paper applies several types of combustion ionization sensors, and a pressure transducer that directly senses the in-cylinder combustion, and the knock sensor which is an accelerometer that detects the impact of combustion on engine structure vibration. Experimental investigations were conducted on a turbocharged four-cylinder gasoline direct injection engine under operating conditions that produce the above phenomena. One of the cylinders is instrumented with a piezo quartz pressure transducer, MSFI (multi-sensing fuel injector), a stand-alone ion current probe, and a spark plug applied to act as an ion current sensor. A comparison is made between the capabilities of the pressure transducer, ion current sensors, and the knock sensor in detecting the above phenomena. The signals from in-cylinder combustion sensors give more accurate information about combustion than the knock sensor. As far as the feasibility and cost of their application in production vehicles, the spark plug sensor and MSFI appear to be the most favorable, followed by the stand-alone mounted sensor which is an addition to the engine.


2016 ◽  
Vol 18 (5-6) ◽  
pp. 560-572 ◽  
Author(s):  
Alla Zelenyuk ◽  
Jacqueline Wilson ◽  
Dan Imre ◽  
Mark Stewart ◽  
George Muntean ◽  
...  

Author(s):  
He Ma ◽  
Ziyang Li ◽  
Mohamad Tayarani ◽  
Guoxiang Lu ◽  
Hongming Xu ◽  
...  

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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