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High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

This paper describes the development of a fracture finite element (FE) model for laser screw welding (LSW) and validation of the model with experimental results. LSW was developed and introduced to production vehicles by Toyota Motor Corporation in 2013. LSW offers superb advantages such as increased productivity and short pitch welding. Although the authors had previously developed fracture FE models for conventional resistance spot welding (RSW), a fracture model for LSW has not been developed. To develop this fracture model, many comprehensive experiments were conducted. The results revealed that LSW had twice as many variations in fracture modes compared to RSW. Moreover, fracture mode bifurcations were also found to result from differences in clearance between welded plates. In order to analyze LSW fracture phenomena, detailed FE models using fine hexahedral elements were developed.

High frequency wind noise caused by turbulent flow around the front pillars of a vehicle is an important factor for customer perception of ride comfort. In order to reduce undesirable interior wind noise during vehicle development process, a calculation and visualization method for exterior wind noise with an acceptable computational cost and adequate accuracy is required. In this paper an index for prediction of the strength of exterior wind noise, referred to as Exterior Noise Power (ENP), is developed based on an assumption that the acoustic power of exterior wind noise can be approximated by the far field acoustic power radiated from vehicle surface. Using the well-known Curle’s equation, ENP can be represented as a surface integral of an acoustic intensity distribution, referred to as Exterior Noise Power Distribution (ENPD). ENPD is estimated from turbulent surface pressure fluctuation and mean convective velocity in the vicinity of the vehicle surface.

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.

In this paper, we will introduce a stereo vision system developed as a sensor for a vehicle's front monitor. This system consists of three parts; namely, a stereo camera that collects video images of the forward view of the vehicle, a stereo ECU that processes its output image, and a near-infrared floodlight for illuminating the front at night. We were able to develop an obstacle detection function for the Pre-Crash Safety System and also a traffic lane detection function for a Lane-Keeping Assist System. Especially in regard to the obstacle detection function, we were able to achieve real-time processing of the disparity image calculations that had formerly required long processing times by using two types of recently developed LSIs.

Due to regulations for even lower levels of pollutants in exhaust gas, development of advanced combustion techniques and increasingly efficient catalysts has become more crucial than ever. One of the essential technologies to achieve this goal is an advanced measurement method, which can detect the characteristics of exhaust gas, such as temperature and chemical compositions, in real-time to clarify their reaction mechanisms. A direct and fast response (1ms) measurement technique was developed based on diode laser absorption spectroscopy and applied to practical engine exhaust measurement to prove the validity of this technology for various applications such as clarification of engine start phenomena and improvement of EGR controls.

Temperature stratification plays an important role in HCCI combustion. The onsets of auto-ignition and combustion duration are sensitive to the temperature field in the engine cylinder. Numerical simulations of HCCI engine combustion are affected by the use of wall boundary conditions, especially the temperature condition at the cylinder and piston walls. This paper reports on numerical studies and experiments of the temperature field in an optical experimental engine in motored run conditions aiming at improved understanding of the evolution of temperature stratification in the cylinder. The simulations were based on Large-Eddy-Simulation approach which resolves the unsteady energetic large eddy and large scale swirl and tumble structures. Two dimensional temperature experiments were carried out using laser induced phosphorescence with thermographic phosphors seeded to the gas in the cylinder.

Non-evaporating diesel sprays have been simulated utilizing the ETAB and the WAVE atomization and breakup models and have been compared with experimental data. The experimental penetrations and widths were determined from back-lit spray images and the droplet sizes have been measured by means of a Malvern particle sizer. The model evaluation criteria include the spray penetration, the spray width and the local droplet size. The comparisons have been performed for variations of the injection pressure, the gas density and the fuel viscosity. The fuel nozzle exit velocities used in the simulations have been computed with a special code that considers the effect of in-nozzle cavitation. The simulations showed good overall agreement with experimental data. However, the capabilities of the models to predict the droplet size for different fuels could be improved.

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.

Increasing fuel injection pressure has enabled reduction of diesel emissions while retaining the advantage of the high thermal efficiency of diesel engines. With production diesel injectors operating in the range from 300 to 2400 bar, there is interest in injection pressures of 3000 bar and higher for further emissions reduction and fuel efficiency improvements. Fundamental understanding of diesel spray characteristics including very early injection and non-vaporizing spray penetration is essential to improve model development and facilitate the integration of advanced injection systems with elevated injection pressure into future diesel engines. Studies were conducted in an optically accessible constant volume combustion vessel under non-vaporizing conditions. Two advanced high pressure multi-hole injectors were used with different hole diameters, number of holes, and flow rates, with only one plume of each injector being imaged to enable high frame rate imaging.

The paper describes an experimental activity on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel at engine-like conditions. The influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio) has been studied by spraying fuel in an optically-accessible constant-volume combustion vessel. A high-speed imaging system, capable of acquiring Mie-scattering and Schlieren images in a near simultaneous fashion mode along the same line of sight, has been developed at the Michigan Technological University using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies have been performed at three injection pressures (70, 120 and 180 MPa), 23.9 kg/m3 ambient gas density and 900 K gas temperature in the vessel.

The projected frontal area of a vehicle has a significant impact on aerodynamic drag, and thus is an important parameter, for vehicle development, benchmarking, and modeling. However, determining vehicle frontal area can be tedious, time consuming, expensive, or inaccurate. Existing methods include analysis of engineering drawings, vehicle projections, 3D scanners, planimeter measurements from photographs, and estimations using vehicle dimensions. Currently accepted approximation methods can be somewhat unreliable. This study focuses on introducing a method to find vehicle frontal area using digital images and subtraction functions via MATLABs' Image Processing Toolbox. In addition to an overview of the method, this paper describes several variables that were examined to optimize and improve the process such as camera position, surface glare, and vehicle shadow effects.

The increase in automobile accidents has heightened the awareness of safety in the general public, and serious safety measures have been pushed forward in various countries. Although those efforts have achieved a certain level of success, more effective methods are needed to cope with further increases of automobile ownership.Besides the collision safety, measures that prevent accidents or reduce the possibility of accidents will now be necessary to reduce the number of injuries.Here, we will present the current development status and issues for an obstacle recognition system that reduces the likelihood of accidents by utilizing radars and image sensors.

This paper describes a method for assisting pedestrians to cross a road. As motorization develops, pedestrian protection techniques are becoming more and more important. Advanced driving assistance systems (ADAS) are improving rapidly to provide even greater safety. However, since the accident risk of pedestrians remains high, the development of an advanced walking assistance system for pedestrian protection may be an effective means of reducing pedestrian accidents. Crossing a road is one of the highest risk events, and is a complex phenomenon that consists of many dynamically changing elements such as vehicles, traffic signals, bicycles, and the like. A road crossing assistance system requires three items: real-time situational recognition, a robust decision-making function, and reliable information transmission. Edge devices equipped with autonomous systems are one means of achieving these requirements.

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.

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.

This paper describes the development of a fatigue life prediction method for Laser Screw Welding (LSW). Fatigue life prediction is used to assess the durability of automotive structures in the early design stages in order to shorten the vehicle development time. The LSW technology is a spot-type joining method similar to resistance spot welding (RSW), and has been developed and applied to body-inwhite structures in recent years. LSW can join metal panels even when a clearance exists between the panels. However, as a result of this favorable clearance-allowance feature of LSW, a concave shape may occur at the nugget part of the joint. These LSW geometric features, the concavity of nuggets and the clearance between panels, are thought to affect the local stiffness behavior of the joint. Therefore, while assessing the fatigue life of LSW, it is essential to estimate the influence of these factors adequately for the representation of the local stiffness behavior of the joint.

Based on RADAR and LiDAR measurements of deer with RADAR and LiDAR in the Spring and Fall of 2014 [1], we report the best fit statistical models. The statistical models are each based on time-constrained measurement windows, termed test-points. Details of the collection method were presented at the SAE World Congress in 2015. Evaluation of the fitness of various statistical models to the measured data show that the LiDAR intensity of reflections from deer are best estimated by the extreme value distribution, while the RCS is best estimated by the log-normal distribution. The value of the normalized intensity of the LiDAR ranges from 0.3 to 1.0, with an expected value near 0.7. The radar cross-section (RCS) varies from -40 to +10 dBsm, with an expected value near -14 dBsm.

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.