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The automotive and aerospace industries are increasingly using the light-weight material to improve the vehicle performance. However, using light-weight material can increase the airborne and structure-borne noise. A special attention needs to be paid in designing the structures and measuring their dynamics. Conventionally, the structure is excited using an impulse hammer or a mechanical shaker and the response is measured using uniaxial or multi-axial accelerometers to obtain the dynamics of the structure. However, using contact-based transducers can mass load the structure and provide data at a few discrete points. Hence, obtaining the true dynamics of the structure conventionally can be challenging. In the past few years, stereo-photogrammetry and three-dimensional digital image correlation have received special attention in collecting operating data for structural analysis. These non-contact optical techniques provide a wealth of distributed data over the entire structure.

Clean snowmobile technology has been developed using methods which can be applied in the real world with a minimal increase in cost. Specifically, a commercially available snowmobile using a two cylinder, four-stroke engine has been modified to run on high-blend ethanol (E-85) fuel. Additionally, a new exhaust system which features customized catalytic converters and mufflers to minimize engine noise and exhaust emissions has developed. Finally, a number of additional improvements have been made to the track to reduce friction and diminish noise. The results of these efforts include emissions reductions of 94% when compared with snowmobiles operating at the 2012 U.S. Federal requirements.

Kettering University's entry for the 2006 Clean Snowmobile challenge utilizes a Polaris FST Switchback. This snowmobile having a two cylinder, four-stroke engine has been modified to run on ethanol (E-85). The student team has designed and built a new exhaust system which features customized catalytic converters to minimize engine out emissions. A number of improvements have been made to the track to reduce friction and diminish noise.

Kettering University has developed a cleaner and quieter snowmobile using technologies and innovative methods which can be applied in the real world with a minimal increase in cost. Specifically, a commercially available snowmobile using a two cylinder, four-stroke engine has been modified to run on high-blend ethanol (E-85) fuel. Further, a new exhaust system which features customized catalytic converters and mufflers to minimize engine noise and exhaust emissions has developed. A number of additional improvements have been made to the track to reduce friction and diminish noise. This paper provides details of the snowmobile development the results of these efforts on performance and emissions. Specifically, the Kettering University snowmobile achieved reductions of approximately 72% in CO, and 98% in HC+NOx when compared with the 2012 standard. Further, the snowmobile achieved a drive by noise level of 73 dbA while operating on hard packed snow.

Affordable clean snowmobile technology has been developed. The goals of this design included reducing exhaust emissions to levels which are below the U.S Environmental Protection Agency (EPA) 2012 standard. Additionally, noise levels were to be reduced to below the noise mandates of 78 dB(A). Further, this snowmobile can operate using any blend of gasoline and ethanol from E0 to E85. Finally, achieving these goals would be a hollow victory if the cost and performance of the snowmobile were severely compromised. Snowmobiling is, after all, a recreational sport; thus the snowmobile must remain fun to drive and cost effective to produce. The details of this design effort including performance data are discussed in this paper. Specifically, the effort to modify a commercially available snowmobile using a two cylinder, four-stroke engine is described. This snowmobile was modified to run on a range of ethanol blended fuels using a closed-loop engine control system.

Object avoidance for autonomous driving is a vital factor in safe driving. When a vehicle travels from any random start places to any target positions in the milieu, an appropriate route must prevent static and moving obstacles. Having the accurate depth of each barrier in the scene can contribute to obstacle prevention. In recent years, precise depth estimation systems can be attributed to notable advances in Deep Neural Networks and hardware facilities/equipment. Several depth estimation methods for autonomous vehicles usually utilize lasers, structured light, and other reflections on the object surface to capture depth point clouds, complete surface modeling, and estimate scene depth maps. However, estimating precise depth maps is still challenging due to the computational complexity and time-consuming process issues. On the contrary, image-based depth estimation approaches have recently come to attention and can be applied for a broad range of applications.

Lane marks are an important aspect for autonomous driving. Autonomous vehicles rely on lane mark information to determine a safe and legal path to drive. In this paper an approach to estimate lane lines on straight or slightly curved roads using a LiDAR unit for autonomous vehicles is presented. By comparing the difference in elevation of LiDAR channels, a drivable region is defined. The presented approach used in this paper differs from previous LiDAR lane line detection methods by reducing the drivable region from three to two dimensions exploring only the x-y trace. In addition, potential lane markings are extracted by filtering a range of intensity values as opposed to the traditional approach of comparing neighboring intensity values. Further, by calculating the standard deviation of the potential lane markings in the y-axis, the data can be further refined to specific points of interest.

Numerical simulations of lean Methanol combustion in a four-stroke internal combustion engine were conducted on a high-compression ratio engine. The engine had a removable integral injector ignition source insert that allowed changing the head dome volume, and the location of the spark plug relative to the fuel injector. It had two intake valves and two exhaust ports. The intake ports were designed so the airflow into the engine exhibited no tumble or swirl motions in the cylinder. Three different engine configurations were considered: One configuration had a flat head and piston, and the other two had a hemispherical combustion chamber in the cylinder head and a hemispherical bowl in the piston, with different volumes. The relative equivalence ratio (Lambda), injection timing and ignition timing were varied to determine the operating range for each configuration. Lambda (λ) values from 1.5 to 2.75 were considered.

Automakers looking to remake their traditional vehicle line-up into autonomous vehicles, Noise, Vibration, and Harshness (NVH) considerations for autonomous vehicles are soon to follow. While traditional NVH considerations still must be applied to carry-over systems, additional components are required for an autonomous vehicle to operate. These additional components needed for autonomy also require NVH analysis and optimization. Autonomous vehicles rely on a suite of sensors, including Light Detection and Ranging (LiDAR) and cameras placed at optimal points on the vehicle for maximum coverage and utilization. In this study, the NVH considerations of autonomous vehicles are examined, focusing on the additional perception equipment installed in autonomous vehicles.

A numerical study on the combustion of Methanol in a directly injected (DI) engine was conducted. The study considers the effect of the bowl-in-piston (BIP) geometry, swirl ratio (SR), and relative equivalence ratio (λ), on flame propagation and burn rate of Methanol in a 4-stroke engine. Ignition-assist in this engine was accomplished by a spark plug system. Numerical simulations of two different BIP geometries were considered. Combustion characteristics of Methanol under swirl and no-swirl conditions were investigated. In addition, the amount of injected fuel was varied in order to determine the effect of stoichiometry on combustion. Only the compression and expansion strokes were simulated. The results show that fuel-air mixing, combustion, and flame propagation was significantly enhanced when swirl was turned on. This resulted in a higher peak pressure in the cylinder, and more heat loss through the cylinder walls.

Three-dimensional transient simulations using KIVA-3V were conducted on a 4-stroke high-compression ratio, methanol-fueled, direct-injection (DI) engine. The engine had two intake ports that were designed to impart a swirling motion to the intake air. In some cases, the intake system was modified, by decreasing the ports diameter in order to increase the swirl ratio. To investigate the effect of adding shrouds to the intake valves on swirl, two sets of intake valves were considered; the first set consisted of conventional valves, and the second set of valves had back shrouds to restrict airflow from the backside of the valves. In addition, the effect of using one or two intake ports on swirl generation was determined by blocking one of the ports.

Objection detection using a camera sensor is essential for developing Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) vehicles. Due to the recent advancement in deep Convolution Neural Networks (CNNs), object detection based on CNNs has achieved state-of-the-art performance during daytime. However, using an RGB camera alone in object detection under poor lighting conditions, such as sun flare, snow, and foggy nights, causes the system's performance to drop and increases the likelihood of a crash. In addition, the object detection system based on an RGB camera performs poorly during nighttime because the camera sensors are susceptible to lighting conditions. This paper explores different pedestrian detection systems at low-lighting conditions and proposes a sensor-fused pedestrian detection system under low-lighting conditions, including nighttime. The proposed system fuses RGB and infrared (IR) thermal camera information.

This paper describes experiments conducted to determine the effect of multiple spark discharge ignition systems and spark plug electrode design on cold start performance of a dedicated E85 fueled vehicle. Tests were conducted using three different ignition configurations: OEM ignition and spark plugs, multiple spark discharge ignition with OEM spark plugs, and multiple spark discharge ignition with large gap circular electrode spark plugs. The multiple spark discharge ignition with OEM spark plugs showed a significant improvement in cold start performance over the OEM ignition, but the addition of the circular electrode spark plugs caused a decrease in cold start performance. The circular ground spark plugs did produce a higher ending coolant temperature than either of the other configurations.

Vehicles are in contact with the road surface through tires, and the interaction at the tire-road interface is usually the major source of vibrations that is experienced by the passengers in the vehicle. Thus, it is critical to measure the vibrational characteristics of the tires in order to improve the safety and comfort of the passengers and also to make the vehicle quieter. The measurement results can also be used to validate numerical models. In this paper, Digital Image Correlation (DIC) as a non-contact technique is used to measure the dynamics of a racing tire in static and rolling conditions. The Kettering University FSAE car is placed on the dynamometer machine for this experiment. A pair of high-speed cameras is used to capture high-resolution images of the tire in a close-up view. The images are processed using DIC to obtain strain and displacement of the sidewall of the tire during rolling. The experiment is performed for various testing speeds.