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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.

This paper describes the methods adopted to improve the image quality of the all-around view system. This system uses multiple vehicle-mounted cameras to capture images of the circumstances around the vehicle. The images undergo viewpoint transformation and are synthesized to create a single image seen from a virtual perspective overhead. The specific methods discussed here concern optimization of the design parameters for the camera orientation and a camera calibration method that does not involve physical movement of the cameras.

The aim of this study is to gain a better understanding of the mechanism of knocking with respect to flame propagation behavior based on 3D simulations conducted with the Universal Coherent Flamelet Model. Flame propagation behavior under the influence of in-cylinder flow was analyzed on the basis of the calculated results and experimental visualizations. Tumble and swirl flows were produced in the cylinder by inserting various baffle plates in the middle of the intake port. A comparison of the measured and calculated flame propagation behavior showed good agreement for various in-cylinder flow conditions. The results indicate that in-cylinder flow conditions vary the flame propagation shape from the initial combustion period and strongly influence the occurrence of knocking.

Diesel engine exhaust aftertreatment components, especially the diesel particulate filter (DPF), are subject to various modes of degradation over their lifetimes. One particular adverse effect on the DPF is the significant rise in pressure drop due to the accumulation of engine lubricant-derived ash which coats the inlet channel walls effectively decreasing the permeability of the filter. The decreased permeability due to ash in the DPF can result in increased filter pressure drop and decreased fuel economy. A unique two-step approach, consisting of experimental measurements and direct numerical simulations using ultra-high resolution 3D imaging data, has been utilized in this study to better understand the effects of ash accumulation on engine aftertreatment component functionality.

The Engine-Out Particulate Matter (EOPM) was collected from a spark ignition engine operating in steady state using a heated quartz fiber filter. The samples were weighted to obtain an EOPMindex and were analyzed using Scanning Electron Microscopy. The EOP Mindex was not sensitive to the engine rpm and load. When the mixture is very rich (air equivalence ratio λ less than ∼ 0.7), the EOPM comprise mostly of soot particles from fuel combustion. In the lean to slightly rich region (0.8 < λ < 1.2), however, the EOPM are dominated by particles derived from the lubrication oil.

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.

This paper describes an image processing method for recognizing white lines on the road ahead to accomplish automatic lane tracking. The behavior of detected points on the white lines can be regarded as multi-channel time-series data. The stochastic behavior of each point correlates with not only its own past behavior but also the behavior of other points around it. Behavior is identified by using a multi-variable auto-regressive (AR) model. This method can estimate the road configuration ahead logically even if the points cannot be detected clearly because a line is discontinuous or is hidden by a forward vehicle.

A method has been developed for improving the ease of viewing images on an in-vehicle display while a vehicle is moving and reducing carsickness. An attempt was made to mitigate carsickness by reducing sensory conflict by controlling the position of displayed images in synchronization with vehicle motions and passenger head motions produced by vehicle acceleration / deceleration forces. In the case of moving images, experimental results showed that, in addition to image position control, providing visual clues for distinguishing between the motions of the images themselves and the control motions can effectively reduce carsickness. The results further indicated that this method of controlling the position of displayed images is also effective in improving the ease of viewing images in a moving vehicle.

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.

This paper presents a new method for calculating optical flow using data from a high frame-rate camera. We focused on a feature of image data captured with a high frame-rate camera in which objects do not move more than one pixel between successive frames. This approach eliminates repetitive processing for object identification among frames taken at different sampling times. High-speed processing hardware architecture was designed with sequential processing only, and the algorithm was implemented in a field programmable gate array. The resultant unit can calculate optical flow for a 640×120 pixel size image with a 480-Hz processing cycle and 0.5-μsec processing latency.

This paper describes a low-cost 48 × 48 element thermal imaging camera intended for use in measuring the temperature in a car interior for advanced air conditioning systems. The compact camera measures 46 × 46 × 60 mm. It operates under a program stored in the central processing unit and can measure the interior temperature distribution with an accuracy of ±0.7°C in range from 0 to 40°C. The camera includes a thermoelectric focal plane array (FPA) housed in a low-cost vacuum-sealed package. The FPA is fabricated with the conventional IC manufacturing process and micromachining technology. The chip is 6.5 × 6.5 mm in size and achieves high sensitivity of 4,300 V/W, which is higher than the performance reported for any other thermopile. This high performance has been achieved by optimizing the sensor's thermal isolation structure and a precisely patterned Au-black absorber that attains high infrared absorptivity of more than 90%.

The presence of liquid fuel inside the engine cylinder is believed to be a strong contributor to the high levels of hydrocarbon emissions from spark ignition (SI) engines during the warm-up period. Quantifying and determining the fate of the liquid fuel that enters the cylinder is the first step in understanding the process of emissions formation. This work uses planar laser induced fluorescence (PLIF) to visualize the liquid fuel present in the cylinder. The fluorescing compounds in indolene, and mixtures of iso-octane with dopants of different boiling points (acetone and 3-pentanone) were used to trace the behavior of different volatility components. Images were taken of three different planes through the engine intersecting the intake valve region. A closed valve fuel injection strategy was used, as this is the strategy most commonly used in practice. Background subtraction and masking were both performed to reduce the effect of any spurious fluorescence.

Simultaneous crank-angle-resolved measurements of gasoline vapor concentration, gas temperature, and liquid fuel droplet scattering were made with three-color infrared absorption in a direct-injection spark-ignition engine with premium gasoline. The infrared light was coupled into and out of the cylinder using fiber optics incorporated into a modified spark plug, allowing measurement at a location adjacent to the spark plug electrode. Two mid-infrared (mid-IR) laser wavelengths were simultaneously produced by difference-frequency-generation in periodically poled lithium niobate (PPLN) using one signal and two pump lasers operating in the near-infrared (near-IR). A portion of the near-IR signal laser residual provided a simultaneous third, non-resonant, wavelength for liquid droplet detection. This non-resonant signal was used to subtract the influence of droplet scattering from the resonant mid-IR signals to obtain vapor absorption signals in the presence of droplet extinction.

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.

This paper describes the numerical and experimental approaches that were applied to study swirl injectors that are widely used in direct-injection gasoline engines. As the numerical approach, the fuel and air flow inside an injector was first analyzed by using a two-phase flow analysis method [VOF (Volume of Fluid) model]. A time-series analysis was made of the flow though the injector and also of the air cavity that forms at the nozzle and influences fuel atomization. The calculated results made clear the process from initial spray formation to liquid film formation. Spray droplet formation was then analyzed with the synthesized spheroid particle (SSP) method. As the experimental approach, in order to measure the cavity factor that represents the liquid film thickness, nozzle exit flow velocities were measured by particle image velocimetry (PIV).

This paper describes an image processing system for tracking a traffic lane by recognizing white lines on the road ahead. The system utilizes the features of the white lines and the Hough transformation to detect white line candidate points in images taken with a CCD camera. The parameters of the road configuration and vehicle attitude are estimated with an extended Kalman filter. This system has been applied to achieve a lane-keeping assistance system that provides steering control based on the host vehicle’s lateral position in its lane.

Recently tailored blank sheets are widely and very often applied to car body's panels in order to reduce weight and number of automobile parts. The tailored blank sheets are produced by welding more than two metal sheets. The gap between edges of blank sheets before laser welding should be controlled for obtaining good quality tailored blank sheets. Therefore control of gap within 0.1mm between batting two blank sheets for production is one of main subjects for producing tailored blank sheets. This report presents not only a new mechanism on gap control but also a development of Finite Element Method (FEM) analysis for prediction of gap. The new mechanism has been applied successfully to produce good quality tailored blank sheets. The gap prediction simulation can reduce the time for gap control apparatus design.

Computer simulation of extravehicular activity (EVA) is increasingly being used in planning and training for EVA. A space suit model is an important, but often overlooked, component of an EVA simulation. Because of the inherent difficulties in collecting angle and torque data for space suit joints in realistic conditions, little data exists on the torques that a space suit’s wearer must provide in order to move in the space suit. A joint angle and torque database was compiled on the Extravehicular Maneuvering Unit (EMU), with a novel measurement technique that used both human test subjects and an instrumented robot. Using data collected in the experiment, a hysteresis modeling technique was used to predict EMU joint torques from joint angular positions. The hysteresis model was then applied to EVA operations by mapping out the reach and work envelopes for the EMU.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.