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Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.

Spray-wall interactions in diesel engines have a strong influence on turbulent flow evolution and mixing, which influences the engine’s thermal efficiency and pollutant-emissions behavior. Previous optical experiments and numerical investigations of a stepped-lip diesel piston bowl focused on how spray-wall interactions influence the formation of squish-region vortices and their sensitivity to injection timing. Such vortices are stronger and longer-lived at retarded injection timings and are correlated with faster late-cycle heat release and soot reductions, but are weaker and shorter-lived as injection timing is advanced. Computational fluid dynamics (CFD) simulations predict that piston bowls with more space in the squish region can enhance the strength of these vortices at near-TDC injection timings, which is hypothesized to further improve peak thermal efficiency and reduce emissions. The dimpled stepped-lip (DSL) piston is such a design.

A one-dimensional, non-equilibrium, compressible law of the wall model is proposed to increase the accuracy of heat transfer predictions from computational fluid dynamics (CFD) simulations of internal combustion engine flows on engineering grids. Our 1D model solves the transient turbulent Navier-Stokes equations for mass, momentum, energy and turbulence under the thin-layer assumption, using a finite-difference spatial scheme and a high-order implicit time integration method. A new algebraic eddy-viscosity closure, derived from the Han-Reitz equilibrium law of the wall, with enhanced Prandtl number sensitivity and compressibility effects, was developed for optimal performance. Several eddy viscosity sub-models were tested for turbulence closure, including the two-equation k-epsilon and k-omega, which gave insufficient performance.

To comply with increasingly stringent pollutant emissions regulations, diesel engine operation in a catalyst-heating mode is critical to achieve rapid light-off of exhaust aftertreatment catalysts during the first minutes of cold starting. Current approaches to catalyst-heating operation typically involve one or more late post injections to retard combustion phasing and increase exhaust temperatures. The ability to retard post injection timing(s) while maintaining acceptable pollutant emissions levels is pivotal for improved catalyst-heating calibrations. Higher fuel cetane number has been reported to enable later post injections with increased exhaust heat and decreased pollutant emissions, but the mechanism is not well understood. The purpose of this experimental and numerical simulation study is to provide further insight into the ways in which fuel cetane number affects combustion and pollutant formation in a medium-duty diesel engine.

Compliance with future ultra-low nitrogen oxide regulations with diesel engines requires the fastest possible heating of the exhaust aftertreatment system to its proper operating temperature upon cold starting. Late post injections are commonly integrated into catalyst-heating operating strategies. This experimental study provides insight into the complex interactions between the injection-strategy calibration and the tradeoffs between exhaust heat and pollutant emissions. Experiments are performed with certification diesel fuel and blends of diesel fuel with butylal and hexyl hexanoate. Further analyses of experimental data provide insight into fuel reactivity and oxygen content as potential enablers for improved catalyst-heating operation. A statistical design-of-experiments approach is developed to investigate a wide range of injection strategy calibrations at three different intake dilution levels.

Appropriate spray modeling in multidimensional simulations of diesel engines is well known to affect the overall accuracy of the results. More and more accurate models are being developed to deal with drop dynamics, breakup, collisions, and vaporization/multiphase processes; the latter ones being the most computationally demanding. In fact, in parallel calculations, the droplets occupy a physical region of the in-cylinder domain, which is generally very different than the topology-driven finite-volume mesh decomposition. This makes the CPU decomposition of the spray cloud severely uneven when many CPUs are employed, yielding poor parallel performance of the spray computation. Furthermore, mesh-independent models such as collision calculations require checking of each possible droplet pair, which leads to a practically intractable O(np2/2) computational cost, np being the total number of droplets in the spray cloud, and additional overhead for parallel communications.

Analysis-driven pre-calibration of a modern automotive engine is extremely valuable in significantly reducing hardware investments and accelerating engine designs compliant with stricter emission regulations. Advanced modelling tools, such as a Virtual Engine Model (VEM) using Computational Fluid Dynamics (CFD), are often used within the framework of a Design of Experiments for Powertrain Engineering (DEPE) with the goal of streamlining significant portions of the calibration process. The success of the methodology largely relies on the accuracy of analytical predictions, especially engine-out emissions. Results show excellent agreements in engine performance parameters (with R2 > 98%) and good agreements in NOx and combustion noise (with R2 > 87%), while the Carbon Monoxide (CO), Unburned Hydrocarbons (HC) and Smoke emissions predictions remain a challenge even with a large n-heptane mechanism consisting of 144 species and 900 reactions and refined mesh resolution.

A Machine Learning (ML) approach is presented to correlate in-cylinder images of early flame kernel development within a spark-ignited (SI) gasoline engine to early-, mid-, and late-stage flame propagation. The objective of this study was to train machine learning models to analyze the relevance of flame surface features on subsequent burn rates. Ultimately, an approach of this nature can be generalized to flame images from a variety of sources. The prediction of combustion phasing was formulated as a regression problem to train predictive models to supplement observations of early flame kernel growth. High-speed images were captured from an optically accessible SI engine for 357 cycles under pre-mixed operation. A subset of these images was used to train three models: a linear regression model, a deep Convolutional Neural Network (CNN) based on the InceptionV3 architecture and a CNN built with assisted learning on the VGG19 architecture.

Lagrangian spray modeling represents a critical boundary condition for multidimensional simulations of in-cylinder flow structure, mixture formation and combustion in internal combustion engines. Segregated models for injection, breakup, collision and vaporization are usually employed to pass appropriate momentum, mass, and energy source terms to the gas-phase solver. Careful calibration of each sub-model generally produces appropriate results. Yet, the predictiveness of this modeling approach has been questioned by recent experimental observations, which showed that at trans- and super-critical conditions relevant to diesel injection, classical atomization and vaporization behavior is replaced by a mixing-controlled phase transition process of a dense fluid. In this work, we assessed the shortcomings of classical spray modeling with respect to real-gas and phase-change behavior, employing a multicomponent phase equilibrium solver and liquid-jet theory.

In this work we studied the effects of piston bowl design on combustion in a small-bore direct-injection diesel engine. Two bowl designs were compared: a conventional, omega-shaped bowl and a stepped-lip piston bowl. Experiments were carried out in the Sandia single-cylinder optical engine facility, with a medium-load, mild-boosted operating condition featuring a pilot+main injection strategy. CFD simulations were carried out with the FRESCO platform featuring full-geometric body-fitted mesh modeling of the engine and were validated against measured in-cylinder performance as well as soot natural luminosity images. Differences in combustion development were studied using the simulation results, and sensitivities to in-cylinder flow field (swirl ratio) and injection rate parameters were also analyzed.

Sector mesh modeling is the dominant computational approach for combustion system design optimization. The aim of this work is to quantify the errors descending from the sector mesh approach through three geometric modeling approaches to an optical diesel engine. A full engine geometry mesh is created, including valves and intake and exhaust ports and runners, and a full-cycle flow simulation is performed until fired TDC. Next, an axisymmetric sector cylinder mesh is initialized with homogeneous bulk in-cylinder initial conditions initialized from the full-cycle simulation. Finally, a 360-degree azimuthal mesh of the cylinder is initialized with flow and thermodynamics fields at IVC mapped from the full engine geometry using a conservative interpolation approach. A study of the in-cylinder flow features until TDC showed that the geometric features on the cylinder head (valve tilt and protrusion into the combustion chamber, valve recesses) have a large impact on flow complexity.

Powertrain electrification could be a key enabler for compliance with future exhaust emission standards and carbon dioxide (CO2) emissions limits or a customer facing product differentiator. The main objective of this study was to assess the potential of electrified propulsion systems in achieving a substantial reduction in CO2 emissions when applied to a representative full-size heavy-duty (HD) truck compared to the baseline configuration. A representative full-size HD four-wheel drive (4WD) truck of adjusted loaded vehicle weight (ALVW) 4082 kg or 9000 lbs with a 6.6 L diesel engine was simulated with various electrified drive configurations over the combined US FTP-72 (Federal Test Procedure) cycle and the Highway Fuel Economy Test (HWFET). Every hybrid vehicle configuration used in the study was designed using representative battery pack and electric drive components.

Diesel piston bowl geometry can affect turbulent mixing and therefore it impacts heat-release rates, thermal efficiency, and soot emissions. The focus of this work is on the effects of bowl geometry and injection timing on turbulent flow structure. This computational study compares engine behavior with two pistons representing competing approaches to combustion chamber design: a conventional, re-entrant piston bowl and a stepped-lip piston bowl. Three-dimensional computational fluid dynamics (CFD) simulations are performed for a part-load, conventional diesel combustion operating point with a pilot-main injection strategy under non-combusting conditions. Two injection timings are simulated based on experimental findings: an injection timing for which the stepped-lip piston enables significant efficiency and emissions benefits, and an injection timing with diminished benefits compared to the conventional, re-entrant piston.

In light-duty direct-injection (DI) diesel engines, combustion chamber geometry influences the complex interactions between swirl and squish flows, spray-wall interactions, as well as late-cycle mixing. Because of these interactions, piston bowl geometry significantly affects fuel efficiency and emissions behavior. However, due to lack of reliable in-cylinder measurements, the mechanisms responsible for piston-induced changes in engine behavior are not well understood. Non-intrusive, in situ optical measurement techniques are necessary to provide a deeper understanding of the piston geometry effect on in-cylinder processes and to assist in the development of predictive engine simulation models. This study compares two substantially different piston bowls with geometries representative of existing technology: a conventional re-entrant bowl and a stepped-lip bowl. Both pistons are tested in a single-cylinder optical diesel engine under identical boundary conditions.

In light- and medium-duty diesel engines, piston bowl shape influences thermal efficiency, either due to changes in wall heat loss or to changes in the heat release rate. The relative contributions of these two factors are not clearly described in the literature. In this work, two production piston bowls are adapted for use in a single cylinder research engine: a conventional, re-entrant piston, and a stepped-lip piston. An injection timing sweep is performed at constant load with each piston, and heat release analyses provide information about thermal efficiency, wall heat loss, and the degree of constant volume combustion. Zero-dimensional thermodynamic simulations provide further insight and support for the experimental results. The effect of bowl geometry on wall heat loss depends on injection timing, but changes in wall heat loss cannot explain changes in efficiency.

Hybridization is a mainstream technology for automobiles, and its application is rapidly expanding in other fields. Marine propulsion is one such field that could benefit from electrification of the powertrain. In particular, for boats to sail in enclosed waterways, such as harbors, channels, lagoons, a pure electric mode would be highly desirable. The main challenge to accomplish hybridization is the additional weight of the electric components, in particular the batteries. The goal of this project is to replace a conventional 4-stroke turbocharged Diesel engine with a hybrid powertrain, without any penalty in terms of weight, overall dimensions, fuel efficiency, and pollutant emissions. This can be achieved by developing a new generation of 2-Stroke Diesel engines, and coupling them to a state-of-the art electric system. For the thermal units, two alternative designs without active valve train are considered: opposed piston and loop scavenged engines.

This work reports a CFD study on a 2-stroke (2-S) opposed piston high speed direct injection (HSDI) Diesel engine. The engine main features (bore, stroke, port timings, et cetera) are defined in a previous stage of the project, while the current analysis is focused on the assembly made up of scavenge ports, manifold and cylinder. The first step of the study consists in the construction of a parametric mesh on a simplified geometry. Two geometric parameters and three different operating conditions are considered. A CFD-3D simulation by using a customized version of the KIVA-4 code is performed on a set of 243 different cases, sweeping all the most interesting combinations of geometric parameters and operating conditions. The post-processing of this huge amount of data allow us to define the most effective geometric configuration, named baseline.

Growing awareness about CO2 emissions and their environmental implications are leading to an increase in the importance of thermal efficiency as criteria to design internal combustion engines (ICE). Heat transfer to the combustion chamber walls contributes to a decrease in the indicated efficiency. A strategy explored in this study to mitigate this efficiency loss is to promote low swirl conditions in the combustion chamber by using low swirl ratios. A decrease in swirl ratio leads to a reduction in heat transfer, but unfortunately, it can also lead to worsening of combustion development and a decrease in the gross indicated efficiency. Moreover, pumping work plays also an important role due to the effect of reduced intake restriction to generate the swirl motion. Current research evaluates the effect of a dedicated injection strategy to enhance combustion process when low swirl is used.

In this work, linear, non-linear and a generalized renormalization group (RNG) two-equation RANS turbulence models of the k-epsilon form were compared for the prediction of turbulent compressible flows in diesel engines. The object-oriented, multidimensional parallel code FRESCO, developed at the University of Wisconsin, was used to test the alternative models versus the standard k-epsilon model. Test cases featured the academic backward facing step and the impinging gas jet in a quiescent chamber. Diesel engine flows featured high-pressure spray injection in a constant volume vessel from the Engine Combustion Network (ECN), as well as intake flows in a high-swirl diesel engine. For the engine intake flows, a model of the Sandia National Laboratories 1.9L light-duty single cylinder optical engine was used.

A quasi-dimensional model for a direct injection diesel engine was developed based on experiments at Sandia National Laboratory. The Sandia researchers obtained images describing diesel spray evolution, spray mixing, premixed combustion, mixing controlled combustion, soot formation, and NOx formation. Dec [1] 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 developed to capture diesel combustion throughout its life span. The compression, expansion, and gas exchange stages are modeled via zero-dimensional single zone calculations.