An investigation to determine the complexity and feasibility of combustion & NOx modelling in modern GTDI engines

Richardson, Danny (2021) An investigation to determine the complexity and feasibility of combustion & NOx modelling in modern GTDI engines. Masters thesis, University of Wales Trinity Saint David.

Richardson, Danny (2021) MSc An investigation to determine the complexity and feasibility of combustion.pdf - Accepted Version
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This paper has been written to demonstrate the common difficulties regarding achievement of respectable results when trying to predict NOx production in a GTDI engine using two zone combustion modelling and a variation of what is typically referred to as the “Zeldovich” model. The investigation assessed 3 collective data sets from two Ford Motor Company EcoBoost engines, their 4-cyl 1.5L and their 3-cyl 1L. With the data including various load conditions at induvial engine speed sites that correspond tabulated data reference sites that Ford produce to generate a map of calibration and combustion characteristics. The process began with the 1.5L because it was known to the be the ‘hardest’ to model because there was a lack of very specific data that is key to “accurately” predict production of NOx during combustion using the methodology discussed. That data included; EGR% in-cylinder, Lambda UEGO which is dynamometer measured and not PCM, and various other useful data like EOI, stated valve overlap, and CAC temperatures etc. Despite these issues the results for the 1.5L were shown to be able to predict production with some degree of accuracy, regarding trend and not value. The models of the 1L were then developed because the data that was seemingly missing of the 1.5L was available for the 1L and the effects on results were profound. The model immediately showed excellent modelling of trend, but also the values themselves considering the rate or decomposition wasn’t modelled, only the forward rate production. Given the clear success of the 1L model the third data set was measured cylinder pressure over 500 cycles for each cylinder and this enable a very relevant study about how sensitive the techniques used are, especially when the conditions were apparently very similar through the testing, the prediction results vary a considerable amount. It did happen to over-predict production when averaged across the total, but it is within an acceptable margin of error considering only forward production is considered and given the multitude of other assumptions that need to be made. With this obvious effect on accuracy of results using the more accurately defined AFR, because it was measured in-cylinder on the 1L engine, it was thought best that a 1D simulation developed in Ricardo WAVE would be the most useful and logical next step to enhance influencing data of the 1.5L engine. There were limitations encountered regarding ability to measure important components of the 1.5L engine because neither the full intake, nor exhaust system was available. Along with the constraints of “stripping” down engine parts, i.e. the turbo charger, to measure as accurately as possible to then influence the model exclusively again because the turbochargers pressure ratio dependence for mass air flow is extremely sensitive. As the model was developed it became clear that despite being able to show some correlation at lower engine speeds and controlling the model across all other aspects to be as similar as possible to Ford’s measured data, there is still issues in the model that result in incorrect MAF. This error was causing poor correlation of results and ultimately voided results of in-cylinder predictions trapped of AFR and internal EGR%. Ultimately the fundamental issue is more measurements of components are required, specifically the waste gate area because this is arguably the most influential element for controlling the turbocharger and therefore results.

Item Type: Thesis (Masters)
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Divisions: Institutes and Academies > Wales Institute for Science & Art (WISA) > Academic Discipline: Engineering
Depositing User: Natalie Williams
Date Deposited: 10 May 2023 14:01
Last Modified: 10 May 2023 14:01

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