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A comprehensive 3D Computational Fluid Dynamics (CFD) with conjugate heat transfer (CHT) tool was developed in-house for a Tesla Model 3 electric motor. To accurately predict the power loss (heat generation) inside the electric motor, the electromagnetic process was solved to obtain the spatial-dependent power loss in the rotor, stator, and windings. CFD was utilized for simulating the coolant oil flow using the multiphase Volume of Fluid (VOF) approach and Finite Element Analysis (FEA) was used for simulating the thermal process within the solid domains. These three separate analysis modules (electromagnetic, fluid flow and thermal solid) were coupled strongly to enable two-way interactions. Thermal results obtained from the final converged simulations were compared to the test data obtained from the thermocouple measurements for the two most representative operating points of this e-motor and showed reasonable predictions with similar trend as observed in the test.

As the efforts to push capabilities of current engine hardware to their durability limits increases, more accurate and reliable analysis is necessary to ensure that designs are robust. This paper evaluates a method of Conjugate Heat Transfer (CHT) analysis for a gasoline and a diesel engine that combines combustion Computational Fluid Dynamics (CFD), engine Finite Element Analysis (FEA), and cooling jacket CFD with the goal of obtaining more accurate temperature distribution and heat loss predictions in an engine compared to standard de-coupled CFD and FEA analysis methods. This novel CHT technique was successfully applied to a 2.5 liter GM LHU gasoline engine at 3000 rpm and a 15.0 liter Cummins ISX heavy duty diesel engine operating at 1250 rpm. Combustion CFD simulations results for the gasoline and diesel engines are validated with the experimental data for cylinder pressure and heat release rate.

Diesel engines are facing increased competition from gasoline engines in the light-duty and small non-road segments, primarily due to the high relative cost of emissions control systems for lean-burn diesel engines. Advancements in gasoline engine technology have decreased the operating cost advantage of diesels and the relatively high initial-cost disadvantage is now too large to sustain a strong business position. SwRI has focused several years of research efforts toward enabling diesel engine combustion systems to operate at stoichiometric conditions, which allows the application of a low-cost three-way catalyst emission control system which has been well developed for gasoline spark-ignited engines. One of the main barriers of this combustion concept is the result of high smoke emissions from poor fuel/air mixing.

As the design of engines advances and continues to push the capabilities of current hardware closer to their durability limits, more accurate and reliable analysis is necessary to ensure that designs are robust. This research evaluates a method of conjugate heat transfer analysis for a diesel engine that combines the combustion CFD, Engine FEA, and cooling jacket CFD with the aim of getting more accurate heat loss predictions and a more accurate temperature distribution in the engine than with current analysis methods. A 15.0 L Cummins ISX heavy duty engine operating at 1250 RPM and 15 bar BMEP load is selected for this work. Spray combustion computational fluid dynamics (CFD) simulations are performed for the diesel engine and the results are validated with experimental data. Finite Element Analysis (FEA) simulations were performed in a separate software platform.

The presented work describes how spark calorimeter testing was used for parametric study and secondary circuit model calibration. Tests were conducted at different pressures, sparkplug gaps and supplied primary energies. The conversion efficiency increases and the spark duration decreases when the gas pressure or the sparkplug gap size is increased. Both gas pressure and sparkplug gas size increase the positive column voltage which represents part of the electrical energy delivered to the gas. The opposite direction occurs when the supplied primary energy is increased. The testing results were then used to calibrate the secondary circuit model which consisted of the sparkplug, the sparkplug gap and the secondary wiring. A step-by-step method was used to calibrate the three constants of the model to match the calculated delivered energy with test data during arc / glow phase.