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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 work aims to present the application of mode coupling to a Formula Student racing vehicle and propose a solution. The major modes of a vehicle are heave, pitch, roll, and warp. All these modes are highly coupled – which means changing suspension rates or geometry will affect all of them – while alleviating some and making others worse characteristics. Decoupling these modes, or at least some of them, would provide more control over suspension setup and more refined race car dynamics for a given layout of the racetrack. This could improve mechanical grip and yield significant performance improvements in closed-circuit racing. If exploited well, this approach could also assist in the operation of the vehicle at an optimal kinematic state of the suspension systems, to gain the best wheel orientations and maximize grip from the tires under the high lateral accelerations and varied excitations seen on a typical road course.

As automated driving becomes more common, simulation of vehicle dynamics and control scenarios are increasingly important for investigating motion control approaches. In this work, a study of the differences between the Pure Pursuit and Stanley autonomous vehicle controllers, based on vehicle dynamics responses, is presented. Both are geometric controllers that use only immediate vehicle states, along with waypoint data, to control a vehicle’s future direction as it proceeds from point to point, and both are among the most popular lateral controllers in use today. The MATLAB Automated Driving Toolbox is employed to implement and virtually test the Pure Pursuit and Stanley lateral controllers in different driving scenarios. These include low intensity scenarios such as city driving, and emergency maneuvers such as the moose test.

Safety is considered one of the most important parameters when designing a ground vehicle. The adverse effect of weather on a vehicle can lead to a surge in safety issues and accidents. Several safety assistance systems are available in modern vehicles, which are designed to lessen the negative effects of weather hazards. Although these safety systems can intervene during crucial conditions to avoid accidents, driving a vehicle on snowy or icy terrain can still be a challenging task. Road conditions with the least tire-road friction often results in poor vehicle handling, and without any kind of safety system it can lead to mishaps. With the use of Adams Car software and vehicle dynamics modeling, a realistic relationship between the vehicle and road surface may be established. The simulation can be used to have a better understanding of vehicle handling in snowy and icy conditions, tire-ice interaction, and tire modeling.

Rapid compression machines can be used to measure a fuel’s ignition delay time and develop an understanding of its resistance to autoignition. Continuing developments in engine design demand higher octane fuels that are resistant to autoignition. Substituted phenols are members of the aromatic hydrocarbon family, and aromatics like toluene are often added to pump-grade gasoline to increase the fuel octane number. Previous numerical and experimental studies have found that substituted phenols included at additive levels in gasoline surrogates, such as the toluene reference fuel in this study, may have a lengthening effect on the ignition delay time of the base fuel they are added to.

Since its implementation, exhaust gas recirculation has proven to be a reliable technique to control NOx emissions by lowering combustion temperature. Dilution with exhaust gas recirculation, whether in internal combustion engines or sequential-staged gas turbine combustors, affects flame reactivity and stability, which are related to the heat release rate and engine power. Another way to control emissions is to use hydrogen as a carbon-free alternative fuel, which is considered a milestone in the energy-decarbonization journey. However, the high reactivity of hydrogen is one of its hurdles and understanding this effect on laminar burning velocity is important. Flame propagation and burning velocity control the mixture reactivity and exothermicity and are related to abnormal combustion phenomena, such as flashback and knock. Therefore, understanding the effect of exhaust gas addition on the laminar burning velocity of hydrogen/air mixtures is imperative for engine design.

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.

LiDAR sensors are common in automated driving due to their high accuracy. However, LiDAR processing algorithm development suffers from lack of diverse training data, partly due to sensors’ high cost and rapid development cycles. Public datasets (e.g. KITTI) offer poor coverage of edge cases, whereas these samples are essential for safer self-driving. We address the unmet need for abundant, high-quality LiDAR data with the development of a synthetic LiDAR point cloud generation tool and validate this tool’s performance using the KITTI-trained PIXOR object detection model. The tool uses a single camera raycasting process and filtering techniques to generate segmented and annotated class specific datasets.

Aromatics have long been used in pump-grade gasoline to inhibit engine knock and enhance a fuel’s octane number, therefore this study focuses on how the addition of aromatics at 2% by mole affects the ignition characteristics of a Toluene Reference Fuel (TRF). The additives investigated in this study are the substituted phenols p-cresol and 2,6-xylenol. In addition to fuel composition, exhaust gas recirculation dilution can be used to lower the combustion temperature and consequently lengthen the ignition delay time of a given fuel-air mixture. This study replicated exhaust gas recirculation dilution by using N2, as it was inert and did not interfere with reactions between the fuel and oxidizer. Determination of whether the similar structures of p-cresol and 2,6-xylenol result in different autoignition inhibiting characteristics was performed on a rapid compression machine.

Autoignition delay times of two full blend gasoline fuels (high and low RON) were explored in a rapid compression machine. CO2 dilution by mass was introduced at 0%, 15%, and 30% levels with the O2:N2 mole ratio fixed at 1:3.76. This dilution strategy is used to represent exhaust gas recirculation (EGR) substitution in spark ignition (SI) engines by using CO2 as a surrogate for major EGR constituents(N2, CO2, H2O). Experiments were conducted over the temperature range of 650K-900K and at 10 bar and 20 bar compressed pressure conditions for equivalence ratios of (Φ =) 0.6-1.3. The full blend fuels were admitted directly into the combustion chamber for mixture preparation using the direct test chamber (DTC) approach. CO2 addition retarded the autoignition times for the fuels studied here. The retarding effect of the CO2 dilution was more pronounced in the NTC region when compared to the lower and higher temperature range.

Surface coatings are one of the most widely used routes to enhance the tribological properties of cylinder kits due to effective sealing capability with low friction coefficient and high wear resistance. In the current study, we have conducted the surface texture characterization of the coating on piston skirts and evaluated the impact of a novel Abradable Powder Coating (APC) on cylinder-kit performance in comparison to stock pistons. The surface texture and characteristic properties varying across the piston skirt are obtained and analyzed via a 3D optical profiler and OmniSurf3D software. The engine operating conditions are found through a combination of measurements, testing, and a calibrated GT-Power model. The variable surface properties along with other dimensions, thermodynamic attributes, flow characteristics and material properties are used to build a model in CASE (Cylinder-kit Analysis System for Engines)- PISTON for both an APC coated piston and a stock piston.

Cylinder-kit tribology has been a significant focus in developing internal combustion engines of lower emission, reduced friction and oil consumption, and higher efficiency. This work addresses the impact of ring-groove geometry on oil (liquid oil and oil vapor) transport and combustion gas flow in the cylinder kit, using a dynamic three-dimensional multiphase modeling methodology during the four-stroke cycle of a piston engine. The ring and groove geometry, along with the temperature and pressure conditions at the interface between piston and liner, trigger the oil and gas (combustion gases and oil vapor) transport. A study of the second ring dynamics is presented to investigate the effect of negative ring twist on the three-dimensional fluid flow physics. The oil (liquid oil and oil vapor) transport and combustion gas flow processes through the piston ring pack for the twisted and untwisted geometry configurations are compared.

Rapid Compression Machines (RCM) offer the ability to easily change the compression ratio and the pressure/mixture composition/temperature to gather ignition delay data at various engine relevant conditions. Therefore, RCMs with optical access to the combustion chamber can provide an effective way to analyze macroscopic spray characteristics needed to understand the spray injection process and for spray model development, validation and calibration at conditions that are suitable for engines. Fuel surrogates can help control fuel parameters, develop models for spray and combustion, and perform laser diagnostics with known fluorescence characteristics. This study quantifies and evaluates the macroscopic spray characteristics of multicomponent gasoline surrogates in comparison to their gasoline counterparts, under gasoline direct injection (GDI) engine conditions.

In this work autoignition delay times of two multi-component surrogates (high and low RON) were experimentally compared with their target full blend gasoline fuels. The study was conducted in a rapid compression machine (RCM) test facility and a direct test chamber (DTC) charge preparation approach was used for mixture preparation. Experiments were carried over the temperature range of 650K-900K and at 10 bar and 20 bar compressed pressure conditions for equivalence ratios of (Φ =) 0.6-1.3. Dilution in the reactant mixture was varied from 0% to 30% CO2 (by mass), with the O2:N2 mole ratio fixed at 1:3.76. This dilution strategy emulates exhaust gas recirculation (EGR) substitution in spark ignition (SI) engines. The multicomponent surrogate captured the reactivity trends of the gasoline-air mixtures reasonably well in comparison to the single component (iso-octane) surrogate.

Understanding cylinder-kit tribology is pivotal to durability, emission management, reduced oil consumption, and efficiency of the internal combustion engine. This work addresses the understanding of the fundamental aspects of oil transport and combustion gas flow in the cylinder kit, using simulation tools and high-performance computing. A dynamic three-dimensional multi-phase, multi-component modeling methodology is demonstrated to study cylinder-kit assembly tribology during the four-stroke cycle of a piston engine. The percentage of oil and gas transported through different regions of the piston ring pack is predicted, and the mechanisms behind this transport are analyzed. The velocity field shows substantial circumferential flow in the piston ring pack, leading to blowback into the combustion chamber during the expansion stroke.

Continuous efforts to improve thermal efficiency and reduce exhaust emissions of internal combustion engines have resulted in development of various solutions towards improved lean burn ignition systems in spark ignition engines. The Dual Mode, Turbulent Jet Ignition (DM-TJI) system is one of the leading technologies in that regard which offers higher thermal efficiency and reduced NOx emissions due to its ability to operate with very lean or highly dilute mixtures. Compared to other pre-chamber ignition technologies, the DM-TJI system has the distinct capability to work with a very high level of EGR dilution (up to ~40%). Thus, this system enables the use of a three-way catalyst (TWC). Auxiliary air supply for pre-chamber purge allows this system to work with such high EGR dilution rate. This work presents the results of experimental investigation carried out with a Dual Mode, Turbulent Jet Ignition (DM-TJI) optical engine equipped with a cooled EGR system.

Rapid changes in the automotive industry, including the growth of advanced vehicle controls and autonomy, are driving the need for more dedicated proving ground spaces where these systems can be developed safely. To address this need, Kettering University has created the GM Mobility Research Center, a 21-acre proving ground located in Flint, Michigan at the former “Chevy in the Hole” factory location. Construction of a proving ground on this site represents a beneficial redevelopment of an industrial brownfield, as well as a significant expansion of the test facilities available at the campus of Kettering University. Test facilities on the site include a road course and a test pad, along with a building that has garage space, a conference room, and an indoor observation platform. All of these facilities are available to the students and faculty of Kettering University, along with their industrial partners, for the purpose of engaging in advanced transportation research and education.

Previous studies have shown that several facility dependent factors can influence ignition delay times measured in a rapid compression machine. Compression ratio variation represents one such aspect of many facility-to facility differences in RCMs, and can have a major impact on measured ignition delay times due to changes in surface-area-to-volume ratio, initial conditions and compression duration even when the same compressed conditions are maintained. In this study, iso-octane, which exhibits two stage ignition delay and has a pronounced negative temperature coefficient (NTC) region, is used to investigate the effects of changing compression ratio on ignition delay. Resulting trends are also compared to previous results obtained with ethanol, which has very different combustion properties. Experiments were carried out for rich mixtures (ϕ = 1.3) of iso-octane and air over a compressed temperature range of 675-900 K at 20 bar compressed pressure.

The objective of this project is to analyze potential design changes that can improve the performance of helical spring in an independent suspension. The performance of the helical spring was based upon the result measure of maximum value of stress acting on it and the amount displacement caused when the spring undergoes loading. The design changes in the spring were limited to coil cross section, spring diameter (constant & variable), pitch and length of the spring. The project was divided into Stage I & Stage II. For Stage I, using all the possible combinations of these design parameters, linear stress analysis was performed on different spring designs and their Stress and displacement results were evaluated. Based on the results, the spring designs were classified as over designed or under designed springs.

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.