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The focus of this paper is to discuss the modeling and control of intake plenum pressure on the Powertrain Control Research Laboratory's (PCRL) Single-Cylinder Engine (SCE) transient test system using a patented device known as the Intake Air Simulator (IAS), which dynamically controls the intake plenum pressure, and, subsequently, the instantaneous airflow into the cylinder. The IAS exists as just one of many devices that the PCRL uses to control the dynamic boundary conditions of its SCE transient test system to make it “think” and operate as though it were part of a Multi-Cylinder Engine (MCE) test system. The model described in this paper will be used to design a second generation of this device that utilizes both continuously and discretely actuating valves working in parallel.

An experimental study has been completed which evaluated the effectiveness of using double, triple and rate shaped injections to simultaneously reduce particulate and NOx emissions. The experiments were done using a single cylinder version of a Caterpillar 3406 heavy duty D.I. diesel engine. The fuel system used was a common rail, electronically controlled injector that allowed flexibility in both the number and duration of injections per cycle. Injection timing was varied for each injection scheme to evaluate the particulate vs. NOx tradeoff and fuel consumption. Tests were done at 1600 rpm using engine load conditions of 25% and 75% of maximum torque. The results indicate that a double injection with a significantly long delay between injections reduced particulate by as much as a factor of three over a single injection at 75% load with no increase in NOx. Double injections with a smaller dwell gave less improvement in particulate and NOx at 75% load.

The SAE AutoDrive Challenge II is a four-year collegiate competition dedicated to developing a Level 4 autonomous vehicle by 2025. In January 2023, the participating teams each received a Chevy Bolt EUV. Within a span of five months, the second phase of the competition took place in Ann Arbor, MI. The authors of this contribution, who participated in this event as team Wisconsin Autonomous representing the University of Wisconsin–Madison, secured second place in static events and third place in dynamic events. This has been accomplished by reducing reliance on the actual vehicle platform and instead leveraging physical analogs and simulation. This paper outlines the software and hardware infrastructure of the competing vehicle, touching on issues pertaining sensors, hardware, and the software architecture employed on the autonomous vehicle. We discuss the LiDAR-camera fusion approach for object detection and the three-tier route planning and following systems.

Droplet vaporization models that are currently employed in simulating diesel engine sprays are based on a quasi-steady, low-pressure formulation. This formulation does not adequately represent many high-pressure effects, such as non-ideal gas behavior, solubility of gases into liquid, pressure dependence of liquid- and gas-phase thermophysical properties, and transient liquid transport in the droplet interior. More importantly, the quasi-steady assumption becomes increasingly questionable as the ambient pressure approaches and /or exceeds the fuel critical pressure. In the present study, a high-pressure, quasi-steady vaporization model is developed. Except for the quasi-steady assumption that is retained in the model, it incorporates all the other high-pressure effects.

The three-dimensional computer code, KIVA, is being modified to include state-of-the-art submodels for diesel engine flow and combustion. Improved and/or new submodels which have already been implemented are: wall heat transfer with unsteadiness and compressibility, laminar-turbulent characteristic time combustion with unburned HC and Zeldo'vich NOx, and spray/wall impingement with rebounding and sliding drops. Progress on the implementation of improved spray drop drag and drop breakup models, the formulation and testing of a multistep kinetics ignition model and preliminary soot modeling results are described. In addition, the use of a block structured version of KIVA to model the intake flow process is described. A grid generation scheme has been developed for modeling realistic (complex) engine geometries, and initial computations have been made of intake flow in the manifold and combustion chamber of a two-intake-valve engine.

Progress on the development and validation of a CFD model for diesel engine combustion and flow is described. A modified version of the KIVA code is used for the computations, with improved submodels for liquid breakup, drop distortion and drag, spray/wall impingement with rebounding, sliding and breaking-up drops, wall heat transfer with unsteadiness and compressibility, multistep kinetics ignition and laminar-turbulent characteristic time combustion models, Zeldovich NOx formation, and soot formation with Nagle Strickland-Constable oxidation. The code also considers piston-cylinder-liner crevice flows and allows computations of the intake flow process in the realistic engine geometry with two moving intake valves. Significant progress has been made using a modified RNG k-ε turbulence model, and a multicomponent fuel vaporization model and a flamelet combustion model have been implemented.

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.

This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

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.

Large-scale flows in internal combustion engines directly affect combustion duration and emissions production. These benefits are significant given increasingly stringent emissions and fuel economy requirements. Recent efforts by engine manufacturers to improve in-cylinder flows have focused on the design of specially shaped intake ports. Utility engine manufacturers are limited to simple intake port geometries to reduce the complexity of casting and cost of manufacturing. These constraints create unique flow physics in the engine cylinder in comparison to automotive engines. An experimental study of intake-generated flows was conducted in a four-stroke spark-ignition utility engine. Steady flow and in-cylinder flow measurements were made using three simple intake port geometries at three port orientations. Steady flow measurements were performed to characterize the swirl and tumble-generating capability of the intake ports.

The University of Wisconsin - Madison FutureCar Team has designed and built a lightweight, charge sustaining, parallel hybrid-electric vehicle for entry into the 1999 FutureCar Challenge. The base vehicle is a 1994 Mercury Sable Aluminum Intensive Vehicle (AIV), nicknamed the “Aluminum Cow,” weighing 1275 kg. The vehicle utilizes a high efficiency, Ford 1.8 liter, turbo-charged, direct-injection compression ignition engine. The goal is to achieve a combined FTP cycle fuel economy of 23.9 km/L (56 mpg) with California ULEV emissions levels while maintaining the full passenger/cargo room, appearance, and feel of a full-size car. Strategies to reduce the overall vehicle weight are discussed in detail. Dynamometer and experimental testing is used to verify performance gains.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

A numerical simulation and optimization study was conducted for a medium speed direct injection diesel engine. The engine's operating characteristics were first matched to available experimental data to test the validity of the numerical model. The KIVA-3V ERC CFD code was then modified to allow independent spray events from two rows of nozzle holes. The angular alignment, nozzle hole size, and injection pressure of each set of nozzle holes were optimized using a micro-genetic algorithm. The design fitness criteria were based on a multi-variable merit function with inputs of emissions of soot, NOx, unburned hydrocarbons, and fuel consumption targets. Penalties to the merit function value were used to limit the maximum in-cylinder pressure and the burned gas temperature at exhaust valve opening. The optimization produced a 28.4% decrease in NOx and a 40% decrease in soot from the baseline case, while giving a 3.1% improvement in fuel economy.

A study of statistical optimization of engine operating parameters was conducted. The objective of the study was to develop a strategy to efficiently optimize operating parameters of diesel engines with multiple injection and EGR capabilities. Previous studies have indicated that multiple injections with EGR can provide substantial simultaneous reductions in emissions of particulate and NOx from heavy-duty diesel engines, but careful optimization of the operating parameters is necessary in order to receive the full benefit of these combustion control techniques. The goal of the present study was to optimize the control parameters to reduce emissions and brake specific fuel consumption. An instrumented single-cylinder heavy-duty diesel engine was used with a prototype mechanically actuated (cam driven) fuel injection system.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

A study of partially premixed combustion (PPC) with non-oxygenated 91 pump octane number1 (PON) commercially available gasoline was performed using a heavy-duty (HD) compression-ignition (CI) 2.44 l Caterpillar 3401E single-cylinder oil test engine (SCOTE). The experimental conditions selected were a net indicated mean effective pressure (IMEP) of 11.5 bar, an engine speed of 1300 rev/min, an intake temperature of 40°C with intake and exhaust pressures of 200 and 207 kPa, respectively. The baseline case for all studies presented had 0% exhaust gas recirculation (EGR), used a dual injection strategy a -137 deg ATDC pilot SOI and a -6 deg ATDC main start-of-injection (SOI) timing with a 30/70% pilot/main fuel split for a total of 5.3 kg/h fueling (equating to approximately 50% load). Combustion and emissions characteristics were explored relative to the baseline case by sweeping main and pilot SOI timings, injection split fuel percentage, intake pressure, load and EGR levels.

The noise characteristics of four camera systems representative of those typically used for laser-imaging experiments (a back-illuminated slow-scan camera, a frame-straddling slow-scan camera, an intensified slow-scan camera and an intensified video-rate camera) were investigated, and the results are presented as a function of the signal level and illumination level. These results provide the maximum possible signal-to-noise ratio for laser-imaging experiments, and represent the limit of quantitative signal interpretation. A calibration strategy for engine data that limits the uncertainties associated with thermodynamic and optical correction was presented and applied to engine data acquired with two of the camera systems. When a rigorous analysis of the signal is performed it is seen that shot noise limits the quantitative interpretation of the data for most typical laser-imaging experiments, and obviates the use of single-pixel data.

We present an approach in which we use simulation to capture the two-way coupling between the dynamics of a vehicle and that of a fluid that sloshes in a tank attached to the vehicle. The simulation is carried out in and builds on support provided by two modules: Chrono::FSI (Fluid-Solid Interaction) and Chrono::Vehicle. The dynamics of the fluid phase is governed by the mass and momentum (Navier-Stokes) equations, which are discretized in space via a Lagrangian approach called Smoothed Particle Hydrodynamics. The vehicle dynamics is the solution of a set of differential algebraic equations of motion. All equations are discretized in time via a half-implicit symplectic Euler method. This solution approach is general - it allows for fully three dimensional (3D) motion and nonlinear transients. We demonstrate the solution in conjunction with the simulation of a vehicle model that performs a constant radius turn and double lane change maneuver.

The lift-off length plays a significant role in spray combustion as it influences the air entrainment upstream of the lift-off location and hence the soot formation. Accurate prediction of lift-off length thus becomes a prerequisite for accurate soot prediction in lifted flames. In the present study, KIVA-3v coupled with CHEMKIN, as developed at the Engine Research Center (ERC), is used as the CFD model. Experimental data from the Sandia National Labs. is used for validating the model predictions of n-heptane lift-off lengths and soot formation details in a constant volume combustion chamber. It is seen that the model predictions, in terms of lift-off length and soot mass, agree well with the experimental results for low ambient density (14.8 kg/m3) cases with different EGR rates (21% O2 - 8% O2). However, for high density cases (30 kg/m3) with different EGR rates (15% O2 - 8% O2) disagreements were found.

A non-intrusive sensing technique to determine start of combustion for mixing-controlled compression-ignition engines was developed based on an accelerometer mounted to the engine block of a 4-cylinder automotive turbo-diesel engine. The sensing approach is based on a physics-based conceptual model for the signal generation process that relates engine block acceleration to the time derivative of heat release rate. The frequency content of the acceleration and pressure signals was analyzed using the magnitude-squared coherence, and a suitable filtering technique for the acceleration signal was selected based on the result. A method to determine start of combustion (SOC) from the acceleration measurements is presented and validated.