Date of Award
5-2026
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Automotive Engineering
Committee Chair/Advisor
Dr. Benjamin Lawler
Committee Member
Dr. Robert Prucka
Committee Member
Dr. Harsh Sapra
Committee Member
Dr. Brian Gainey
Abstract
Vehicles are becoming increasingly complex to comply with the increasingly stringent regulations placed on all market sectors while still maintaining performance requirements. This increased complexity leads to increases in the cost and time it takes to develop and produce these next generation vehicles. To meet demand therefore, it becomes necessary to evaluate numerous design iterations using computer models. There are multiple levels of models that may be necessary for different purposes or use cases. All levels of modeling for virtual prototyping, however, require a level of validation and predictive ability to be useful. To this end, the following thesis presents several models for the analysis and performance prediction of diesel engines. A thermodynamic engine model is presented coupled to a finite element heat transfer model used for piston temperature prediction. This model is validated and applied to evaluate different engine architectures and designs specifically evaluating their heat transfer characteristics and piston temperatures. The combustion sub-model is shown to be critical to the predictive ability of the overall model, and the model implemented from existing literature is found to not have sufficient predictive abilities for the proposed application. To fill this gap, a novel, predictive combustion model is sought that is more closely tied to the fundamental fluid and chemical processes. Three-dimensional computational fluid dynamics simulations are run and analyzed to establish a firm understanding of the mixing and combustion process and fuel evolution with the cylinder to inform a zero-dimensional combustion model. Within the CFD simulations, a novel methodology is proposed and applied to track the fuel mass evolution. The in-cylinder turbulence is also closely analyzed considering the several contributors to turbulence in the diesel engine. This turbulence analysis is conducted using both RANS and LES turbulence models, the differences between the turbulence models are discussed through the results. Formixing controlled combustion, it is shown that the injection event dominates turbulence production and mixing process throughout the time of combustion. The bulk fluid motion from the intake and compression processes are shown to still be significant, though any combustion influence is shown to be negligible.
Ultimately, a combustion model is proposed that draws on the analogy between convective heat transfer and mass transfer deriving a new mixing correlation for mixing controlled combustion. The combustion model is validated and implemented into the thermodynamic engine cycle simulation model which is then validated against experimental data on a heavy-duty diesel engine. The predicted heat release rates across a number of targeted input parameter sweeps are shown to closely resemble the heat release in the real engine. Minimal changes to the tunable parameters are shown to be necessary when the model is applied to both medium- and light-duty engines. Finally, the model is shown to possess better predictive capabilities while requiring less calibration with less relative computational expense.
Recommended Citation
Gohn, James, "Development of a Mixing-Controlled Combustion Model for 0D Engine Modeling: Using High-Order Models to Guide the Formulation of Reduced-Order Models" (2026). All Dissertations. 4285.
https://open.clemson.edu/all_dissertations/4285