Search Results

This paper addresses a three dimensional (3D) mission domain coverage control problem combined with camera pose control to align towards specific objects of interest. We consider an unmanned ground vehicle (UGV) based on a unicycle kinematics model with an onboard camera sensor based on a visual perspective sensor model. The coverage control problem has been researched in large part for planar domains, which is however not sufficient for real world applications for UGV navigation. Furthermore, in contrast to coverage control of points in the environment, when dealing with objects of interest, it is more amicable to consider that there exist certain orientations to which the camera must align itself to properly cover the object and make ‘sense’ of it. Hence, we seek to derive both UGV coverage control law for 3D mission domains and onboard camera pose control considering target orientation.

Triggered explosions are increasingly becoming common in the world today leading to the loss of precious lives under the most unexpected circumstances. In most scenarios, ordinary citizens are the targets of such attacks, making it essential to design countermeasures in open areas as well as in mobility systems to minimize the destructive effects of such explosive-induced blasts. It would be rather difficult and to an extent risky to carry out physical experiments mimicking blasts in real world scenarios. In terms of mechanics, the problem is essentially one of fluid-structure interaction in which pressure waves in the surrounding air are generated by detonating an explosive charge which then have the potential to cause severe damage to any obstacle on the path of these high-energy waves.

A dimensionless relationship that estimates the maximum bearing load of a 4-cylinder 4-stroke in-line engine has been found. This relationship may assist the design engineer in choosing a desired counterweight mass. It has been demonstrated that: 1) the average bearing load increases with engine speed and 2) the maximum bearing load initially decreases with engine speed, reaches a minimum, then increases quickly with engine speed. This minimum refers to a transition speed at which the contribution of the inertia force overcomes the contribution of the maximum pressure force to the maximum bearing load. The transition speed increases with an increase of counterweight mass and is a function of maximum cylinder pressure and the operating parameters of the engine.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

In automotive body manufacturing the dies for blanking/trimming/piercing are under most severe loading condition involving high contact stress at high impact loading and large number of cycles. With continuous increase in sheet metal strength, the trim die service life becomes a great concern for industries. In this study, competing trim die manufacturing routes were compared, including die raw materials produced by hot-working (wrought) vs. casting, edge-welding (as repaired condition) vs. bulk base metals (representing new tools), and the heat treatment method by induction hardening vs. furnace through-heating. CaldieTM, a Uddeholm trademarked grade was used as trim die material. The mechanical tests are performed using a WSU developed trimming simulator, with fatigue loading applied at cubic die specimen’s cutting edges through a tungsten carbide rod to accelerate the trim edge damage. The tests are periodically interrupted at specified cycles for measurement of die edge damage.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Hat-sections, single and double, made of steel are frequently encountered in automotive body structural components. These components play a significant role in terms of impact energy absorption during vehicle crashes thereby protecting occupants of vehicles from severe injury. However, with the need for higher fuel economy and for compliance to stringent emission norms, auto manufacturers are looking for means to continually reduce vehicle body weight either by employing lighter materials like aluminum and fiber-reinforced plastics, or by using higher strength steel with reduced gages, or by combinations of these approaches. Unlike steel hat-sections which have been extensively reported in published literature, the axial crushing behavior of hat-sections made of fiber-reinforced composites may not have been adequately probed.

Described in this paper is a component test methodology to evaluate the door trim armrest performance in an Insurance Institute for Highway Safety (IIHS) side impact test and to predict the SID-IIs abdomen injury metrics (rib deflection, deflection rate and V*C). The test methodology consisted of a sub-assembly of two SID-IIs abdomen ribs with spine box, mounted on a linear bearing and allowed to translate in the direction of impact. The spine box with the assembly of two abdominal ribs was rigidly attached to the sliding test fixture, and is stationary at the start of the test. The door trim armrest was mounted on the impactor, which was prescribed the door velocity profile obtained from full-vehicle test. The location and orientation of the armrest relative to the dummy abdomen ribs was maintained the same as in the full-vehicle test.

Low-pressure cooled EGR (LP-cEGR) systems can provide significant improvements in spark-ignition engine efficiency and knock resistance. However, open-loop control of these systems is challenging due to low pressure differentials and the presence of pulsating flow at the EGR valve. This research describes a control structure for Low-pressure cooled EGR systems using closed loop feedback control along with internal model control. A Smith Predictor based PID controller is utilized in combination with an intake oxygen sensor for feedback control of EGR fraction. Gas transport delays are considered as dead-time delays and a Smith Predictor is one of the conventional methods to address stability concerns of such systems. However, this approach requires a plant model of the air-path from the EGR valve to the sensor.

Automotive multiplexing allows sharing information among various intelligent modules inside an automotive electronic system. In order to achieve an optimum functionality, the information should be exchanged among various electronic modules in real time. New features are introduced in automobiles such as Intelligent Vehicle Highway System (IVHS), intelligent transportation support system, engine immobilizers, night vision assistance system, and automated collision avoidance and notification system. The inclusion of such features increases the data traffic over the multiplexing bus. Also, these features require very high speed and expensive bus. Data reduction techniques are used to send the data over a transmission media at high speed. Using the data reduction techniques, we will be able to include new features in automobiles without the need of a high speed bus. Since the automotive environment is different, a special data reduction algorithm is mandated.

Designing a vehicle for superior crash safety performance in consumer rating tests such as US-NCAP is a compelling target in the design of passenger vehicles. In today’s context, there is also a high emphasis on making a vehicle as lightweight as possible which calls for an efficient design. In modern vehicle design, these objectives can only be achieved through Computer-Aided Engineering (CAE) for which a detailed CAD (Computer-Aided Design) model of a vehicle is a pre-requisite. In the absence of the latter (i.e. a matured CAD model) at the initial and perhaps the most crucial phase of vehicle body design, a rational approach to design would be to resort to a knowledge-based methodology which can enable crash safety assessment of an assumed design using artificial intelligence techniques such as neural networks.

Diesel engine exhaust poses an ongoing threat to human health as well as to the environment. Automotive exhaust treatment systems have been developed over the years to reduce the large amount of diesel particulate matter (DPM) released to the atmosphere. Current systems can be categorized as selective catalytic reduction, catalytic converters, and diesel particulate filters. This study presents an emission system that focuses on the removal of exhaust particles using Brownian diffusion of DPM toward fog drops followed by cyclonic separation of DPM rich fog drops. The experimental system consisted of a 13.2 kW diesel engine, heat exchanger to cool the exhaust to saturation temperature, ultrasonic fogger, cyclone separator, and recovery of waste particulate. Representative emission tests have been performed at five different diesel engine speeds and corresponding crankshaft loads.

The design of transportation vehicles, whether passenger or commercial, typically involves a lengthy process from concept to prototype and eventual manufacture. To improve competitiveness, original equipment manufacturers are continually exploring ways to shorten the design process. The application of digital tools such as computer-aided-design and computer-aided-engineering, as well as model-based computer simulation enable team members to virtually design and evaluate ideas within realistic operating environments. Recent advances in machine learning (ML)/artificial intelligence (AI) can be integrated into this paradigm to shorten the initial design sequence through the creation of digital agents. A digital agent can intelligently explore the design space to identify promising component features which can be collectively assessed within a virtual vehicle simulation.

In this paper, we proposed a distributed Engineering Computer Aided Learning System. Instead of attending engineering teaching sessions, engineering students are able to interact with the software to gain the same amount of teaching materials. Besides, they will interact with other engineering students from other Engineering schools. The proposed software has the ability to examine the student step by step to reach certain goals. The training and the examination will be different based on the student level and his learning process. Using this system the role of excellent professor can be achieved. The software will have two sessions, i.e. test session and learning session. The software provides the capability of knowledge sharing between multi schools and different educational systems that can provide the students with a large set of training materials. The system was built using JAVA programming language.

The ever-growing concern to reduce the impact of transportation systems on environment has pushed automotive industry towards fuel-efficient and sustainable solutions. While several approaches have been used to improve fuel efficiency, the light-weighting of automobile components has proven broadly effective. A substantial effort is devoted to lightweighting body-in-white which contributes ~35% of total weight of vehicle. Closure systems, however, have been often overlooked. Closure systems are extremely important as they account for ~ 50% of structural mass and have a very diverse range of requirements, including crash safety, durability, strength, fit, finish, NVH, and weather sealing. To this end, a carbon fiber-reinforced thermoplastic composite door is being designed for an OEM’s mid-size SUV, that enables 42.5% weight reduction. In this work, several novel composite door assembly designs were developed by using an integrated design, analysis and optimization approach.

Android Automotive OS (AAOS) has been gaining popularity in recent years, with several OEMs across the world already deploying it or planning to in the near future. Besides the benefit of a well-known, customizable and secure operating system for OEMs, AAOS allows third-party app developers to offer their apps on vehicles of several manufacturers at the same time. Currently, there are 55 apps for AAOS that can be categorized as media, navigation or point-of-interest apps. Specifically the latter two categories allow the third-parties to collect certain sensor data directly from the vehicle. Furthermore, the latest version of AAOS also allows the OEM to configure and collect In-Vehicle Infotainment (IVI) and vehicle data (called OEM telemetry). However, increasing connectivity and integration with the in-vehicle network comes at the expense of user privacy. Previous works have shown that vehicular sensor data often contains personally identifiable information (PII).

Contemporary manufacturing systems are still evolving. The system elements, layouts, and integration methods are changing continuously, and ‘collaborative robots’ (CoBots) are now being considered as practical industrial solutions. CoBots, unlike traditional CoBots, are safe and flexible enough to work with humans. Although CoBots have the potential to become standard in production systems, there is no strong foundation for systems design and development. The focus of this research is to provide a foundation and four tier framework to facilitate the design, development and integration of CoBots. The framework consists of the system level, work-cell level, machine level, and worker level. Sixty-five percent of traditional robots are installed in the automobile industry and it takes 200 hours to program (and reprogram) them.

An experimental fuel surrogate validation approach is proposed for a compression ignition application, and applied to validate a Jet-A POSF 4658 fuel surrogate. The approach examines the agreement of both physical and chemical properties of surrogate and target fuels during validation within a real compression-ignition engine environment during four sequential but distinct combustion phases. In-cylinder Mie Scattering measurements are applied to evaporating sprays to compare the behavior of the surrogate, its target fuel, and for reference, n-heptane. Early mixture formation and low temperature reaction behavior were investigated using 2-D broadband chemiluminescence imaging, while high temperature ignition and combustion chemistry were studied using OH chemiluminescence imaging. The optical measurements were combined with cylinder pressure-based combustion analysis, including ignition delay and premixed burn duration, to validate the global behavior of the surrogate.

Variant modeling techniques have been developed to allow systems engineers to model multiple similar variants in a product line as a single variant model. In this paper, we expand on this past work to explore the extent to which variant modeling in SysML can be applied to a broad range of dissimilar systems, covering the entire domain of ground vehicles, in single reference architecture model. Traditionally, a system’s structure is decomposed into subsystems and components. However, this method is found to be ineffective when modeling variants that are functionally similar but structurally different. We propose to address this challenge by first decomposing the system not only by subsystem but also by high-level function. This pattern is particularly useful for situations where two variants perform the same function, but one variant performs the function using one subsystem, whereas the other variant performs the same function using one or more different subsystems.