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University of Texas – Austin

1. -1322-3556. Fuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling.

Degree: Mechanical Engineering, 2018, University of Texas – Austin

A research team developed the University of Texas Fuel Economy Model to estimate the fuel consumption of both light-duty and heavy-duty vehicles operated on Texas roads. One of the objectives of the model was to be as flexible as possible in order to be capable of simulating a variety of vehicles, payloads, and traffic conditions. For heavy-duty vehicles, there are no prescribed driving cycles, there are no coastdown coefficients available from the EPA, and we relied on experimental brake specific fuel consumption maps for a few heavy-duty diesel engines. Heavy-duty vehicle drive cycles highly depend upon the vehicle load, the grade of the road, the engine size, and the traffic conditions. In order to capture real driving conditions 54 drive cycles with three different Class 8 trucks, three weight configurations, three traffic congestion levels, and two drivers are collected. Drive cycles obtained in this research include road grade and vehicle speed data with time. Due to the lack of data from EPA for calculating the road load force for heavy-duty vehicles, coastdown tests were performed. To generate generic fuel maps for the fuel economy model, a direct injection quasi-dimensional diesel engine model was developed based on in-cylinder images available in the literature. Sandia National Laboratory researchers obtained various images describing diesel spray evolution, spray mixing, premixed combustion, mixing controlled combustion, soot formation, and NOx formation via imaging technologies. Dec combined all of the available images to develop a conceptual diesel combustion model to describe diesel combustion from the start of injection up to the quasi-steady form of the jet. The end of injection behavior was left undescribed in this conceptual model because no clear image was available due to the chaotic behavior of diesel combustion. A conceptual end-of-injection diesel combustion behavior model was proposed to capture diesel combustion in its life span. A full-cycle quasi-dimensional direct injection diesel engine model was developed that represents the physical models, utilizing the conceptual model developed from imaging experiments and available experiment-based spray models, of the in-cylinder processes. The compression, expansion, and gas exchange stages are modeled via zero-dimensional single zone calculations. A full cycle simulation is necessary in order to capture the initial conditions of the closed section of the cycle and predict the brake specific fuel consumption accurately. Advisors/Committee Members: Matthews, Ronald D. (advisor), Hall, Matthew John (advisor), Ellzey, Janet L. (committee member), Ezekoye, Ofodike A. (committee member), Biros, George (committee member), Roberts, Charles E. (committee member).

Subjects/Keywords: Quasi-dimensional; Diesel; Engine; Heavy-duty; Direct injection; Numerical; Modeling; Combustion; Coastdown; Drive cycle; Fuel economy; Mathematical; Vehicle; Simulation; Class 8

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APA (6th Edition):

-1322-3556. (2018). Fuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68397

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

-1322-3556. “Fuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling.” 2018. Thesis, University of Texas – Austin. Accessed October 19, 2018. http://hdl.handle.net/2152/68397.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

-1322-3556. “Fuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling.” 2018. Web. 19 Oct 2018.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-1322-3556. Fuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2018 Oct 19]. Available from: http://hdl.handle.net/2152/68397.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

-1322-3556. Fuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68397

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

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