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Testing of ducted fuel injection (DFI) in a single-cylinder engine with production-like hardware previously showed that adding a duct structure increased soot emissions at the full load, rated speed operating point [1]. The authors hypothesized that the DFI flame, which travels faster than a conventional diesel combustion (CDC) flame, and has a shorter distance to travel, was being re-entrained into the on-going fuel injection around the lift-off length (LOL), thus reducing air entrainment into the on-going injection. The engine operating condition and the engine combustion chamber geometry were duplicated in a constant pressure vessel. The experimental setup used a 3D piston section combined with a glass fire deck allowing for a comparison between a CDC flame and a DFI flame via high-speed imaging. CH* imaging of the 3D piston profile view clearly confirmed the re-entrainment hypothesis presented in the previous engine work.

The steering assembly is a part of an automotive suspension system that provides control and stability. It provides control of direction, stability, and control over placement of the car. Optimization of the vehicle in weight results in enhanced performance and low fuel consumption, more so for an all-terrain race car. Optimization in this paper loosely refers to weight reduction and achieving the optimum stiffness to weight ratio of each component. This research encompasses various aspects linked to conceptualizing, designing, analysing, optimizing, and finally manufacturing the steering sub-system. Analytical calculations for mechanical design were performed using data from various experiments and jigs. CAD was developed using SolidWorks, and various analyses were performed using Altair HyperWorks. Finite Element Analysis (FEA) was primarily used to build stress plots and locate weak spots aiding optimization.

An automobile seat’s thermal performance can be challenging to quantify since it requires comprehensive human subject testing. Seat manufacturers must rely on subjective ratings to understand how the construction of a seat and its underlying heating and cooling technology may compare to other seats. Other factors may influence seat ratings published by global marketing information services companies (e.g., JD Power and Associates). In particular, occupants may be biased by the vehicle class in which a seat is installed and by how much the contribution of a specific vehicle’s HVAC system performance affects the perception of seat thermal comfort. Therefore, there is a need for an objective testing methodology that does not rely on human participants but is still capable of producing a thermal performance rating in terms of established thermal comfort scales.

Off road navigation demands ground robots to traverse complex and often changing terrain. Classification and assessment of terrain can improve path planning strategies by reducing travel time and energy consumption. In this paper we introduce a terrain classification and assessment framework that relies on both exteroceptive and proprioceptive sensor modalities. The robot captures an image of the terrain it is about to traverse and records corresponding vibration data during traversal. These images are manually labelled and used to train a support vector machine (SVM) in an offline training phase. Images have been captured under different lighting conditions and across multiple locations to achieve diversity and robustness to the model. Acceleration data is used to calculate statistical features that capture the roughness of the terrain whereas angular velocities are used to calculate roll and pitch angles experienced by the robot.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

Autonomous ground vehicles can use a variety of techniques to navigate the environment and deduce their motion and location from sensory inputs. Visual Odometry can provide a means for an autonomous vehicle to gain orientation and position information from camera images recording frames as the vehicle moves. This is especially useful when global positioning system (GPS) information is unavailable, or wheel encoder measurements are unreliable. Feature-based visual odometry algorithms extract corner points from image frames, thus detecting patterns of feature point movement over time. From this information, it is possible to estimate the camera, i.e., the vehicle’s motion. Visual odometry has its own set of challenges, such as detecting an insufficient number of points, poor camera setup, and fast passing objects interrupting the scene. This paper investigates the effects of various disturbances on visual odometry.

Surrogate targets are used throughout the automotive industry to safely and repeatably test Advanced Driver Assistance Systems (ADAS) and will likely find similar applications in tests of Automated Driving Systems. For those test results to be applicable to real-world scenarios, the surrogate targets must be representative of the real-world objects that they emulate. Early target development efforts were generally divided into those that relied on sophisticated radar measurement facilities and those that relied on ad-hoc measurements using automotive grade equipment. This situation made communication and interpretation of results between research groups, target developers and target users difficult. SAE J3122, “Test Target Correlation - Radar Characteristics”, was developed by the SAE Active Safety Systems Standards Committee to address this and other challenges associated with target development and use. J3122 addresses four topics.

There has been a great effort expended in identifying causes of Hydro-Carbon (HC) and Particulate Matter (PM) emissions resulting from poor spray preparation, leading to characterization of fueling behavior near nozzle. It has been observed that large droplet size is a primary contributor to HC and PM emission. Imaging technologies have been developed to understand the break-up and consistency of fuel spray. However, there appears to be a lack of studies of the spray characteristics at the End of Injection (EOI), near nozzle, in particular, the effect that tip deposits have on the EOI characteristics. Injector tip deposits are of interest due to their effect on not only fuel spray characteristics, but also their unintended effect on engine out emissions. Using a novel imaging technique to extract near nozzle fuel characteristics at EOI, the impact of tip deposits on Gasoline Direct Injection (GDI) fuel injectors at the EOI is being examined in this work.

The Society of Automotive Engineers Fatigue Design & Evaluation Committee [SAE FD&E] is actively working on a total life project for weldments, in which the welding residual stress is a key contributor to an accurate assessment of fatigue life. Physics-based welding process simulation and various types of residual stress measurements were pursued to provide a representation of the residual stress field at the failure location in the fatigue samples. A well-controlled and documented robotic welding process was used for all sample fabrications to provide accurate inputs for the welding simulations. One destructive (contour method) residual stress measurement and several non-destructive residual stress measurements-surface X-ray diffraction (XRD), energy dispersive X-ray diffraction (EDXRD), and neutron diffraction (ND)-were performed on the same or similarly welded samples.

The liquid fuel spray impingement onto surfaces occurs in both spark ignited and compression ignited engines. It causes a fundamental issue affecting the preparation of air-fuel mixture prior to the combustion, further, affecting engine performance and emissions. To better understand the underlying mechanism of spray interaction with a solid surface, the physics of a single droplet impact on a heated surface was experimentally investigated. The experimental work was conducted at four surface temperatures where a single diesel droplet was injected from a precision syringe pump with a specific droplet diameter and impact velocity. A high-speed camera was used to visualize the droplet impingement process. Images from the selected test condition (We = 52 to 925, Re = 789 to 3330 based on initial droplet impingement parameters) were analyzed to qualify the impinging outcomes and quantify the post-impingement characteristics.

High fidelity engine simulation requires realistic fuel models. Although typical automotive fuels consist of more than few hundreds of hydrocarbon species, researches show that the physical and chemical properties of the real fuels could be represented by appropriate surrogate fuel models. It is desirable to represent the fuel using the same set of physical and chemical surrogate components. However, when the reaction mechanisms for a certain physical surrogate component is not available, the chemistry of the unmatched physical component is described using that of a similar chemical surrogate component at the expense of accuracy. In order to reduce the prediction error while maintaining the computational efficiency, a method of on-the-fly reactivity adjustment (ReAd) of chemical reaction mechanism along with fuel re-distribution based on reactivity is presented and tested in this study.

Tumble motion plays a significant role in modern spark-ignition engines in that it promotes mixing of air/fuel for homogeneous combustion and increases the flame propagation speed for higher thermal efficiency and lower combustion variability. Cycle-by-cycle variations in the flow near the spark plug introduce variability to the initial flame kernel development, stretching, and convection, and this variability is carried over to the entire combustion process. The design of current direct-injection spark-ignition engines aims to have a tumble flow in the vicinity of the spark plug at the time of ignition. This work investigates how the flow condition changes in the vicinity of the spark plug throughout the late compression stroke via high-speed imaging of a long ignition discharge arc channel and its stretching, and via flow field measurement by particle imaging velocimetry.

Objective of this work is the incorporation of the flame stretch effects in an Eulerian-Lagrangian model for premixed SI combustion in order to describe ignition and flame propagation under highly inhomogeneous flow conditions. To this end, effects of energy transfer from electrical circuit and turbulent flame propagation were fully decoupled. The first ones are taken into account by Lagrangian particles whose main purpose is to generate an initial burned field in the computational domain. Turbulent flame development is instead considered only in the Eulerian gas phase for a better description of the local flow effects. To improve the model predictive capabilities, flame stretch effects were introduced in the turbulent combustion model by using formulations coming from the asymptotic theory and recently verified by means of DNS studies. Experiments carried out at Michigan Tech University in a pressurized, constant-volume vessel were used to validate the proposed approach.

This paper aims to extend the existing Volume of Fluid (VOF) model by implementing an evaporation sub-model in an open source Computational Fluid Dynamics (CFD) software, OpenFOAM. The paper applies the new model to numerically study the evaporation of spherical n-heptane droplets impinging on a hot wall at atmospheric pressure and a temperature above the Leidenfrost temperature. Volume of Fluid (VOF) method is chosen to track the liquid gas interface and the capability of VOF method implemented in interDyMFoam solver of OpenFOAM to simulate hydrodynamics during droplet-droplet interaction and droplet-film interaction is explored. Firstly, the in-built solver is used to simulate problems in isothermal conditions and the simulation results are compared qualitatively with the published results to validate the solver. A numerical method for modeling heat and mass transfer during evaporation is implemented in conjunction with the VOF.

Extensive studies have addressed diesel sprays under non-vaporizing, vaporizing and combusting conditions respectively, but further insights into the mechanism by which combustion alters the macroscopic characteristics including the spray penetration and the shape of the spray under diesel engine conditions are needed. Contradictory observations are reported in the literature regarding the combusting diesel spray penetration compared to the inert conditions, and it is an objective of this study to provide further insights and analyses on the combusting spray characteristics by expanding the range of operating parameters. Parameters varied in the studies are charge gas conditions including oxygen levels of 0 %, 15%, 19%, charge densities of 22.8 & 34.8 kg/m3, and charge temperatures of 800, 900 & 1050 K for injection pressures of 1200, 1500, and 1800 bar with a single-hole injector with a nozzle diameter of 100 μm.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.

Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.

Although soot-formation processes in diesel engines have been well characterized during the mixing-controlled burn, little is known about the distribution of soot throughout the combustion chamber after the end of appreciable heat release during the expansion and exhaust strokes. Hence, the laser-induced incandescence (LII) diagnostic was developed to visualize the distribution of soot within an optically accessible single-cylinder direct-injection diesel engine during this period. The developed LII diagnostic is semi-quantitative; i.e., if certain conditions (listed in the Appendix) are true, it accurately captures spatial and temporal trends in the in-cylinder soot field. The diagnostic features a vertically oriented and vertically propagating laser sheet that can be translated across the combustion chamber, where “vertical” refers to a direction parallel to the axis of the cylinder bore.

To reduce the number and severity of accidents, automakers have invested in active safety systems to detect and track neighboring vehicles to prevent accidents. These systems often employ RADAR and LIDAR, which are not degraded by low lighting conditions. In this research effort, reflections from deer were measured using two sensors often employed in automotive active safety systems. Based on a total estimate of one million deer-vehicle collisions per year in the United States, the estimated cost is calculated to be $8,388,000,000 [1]. The majority of crashes occurs at dawn and dusk in the Fall and Spring [2]. The data includes tens of thousands of RADAR and LIDAR measurements of white-tail deer. The RADAR operates from 76.2 to 76.8 GHz. The LIDAR is a time-of-flight device operating at 905 nm. The measurements capture the deer in many aspects: standing alone, feeding, walking, running, does with fawns, deer grooming each other and gathered in large groups.