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In contrast to conventional powertrains from internal combustion engine vehicles (ICEV), the tribological performance of powertrains of electric vehicles (EVs) must be further evaluated by considering new critical operating conditions such as electrical environments. The operation of any type of electric motor produces shaft voltages and currents due to various hardware configurations and factors. Furthermore, the common application of inverters intensifies this problem. It has been reported that the induced shaft voltages and currents can cause premature failure problems in tribological components such as bearings and gears due to accelerated wear and/or fatigue. It is ascribed to effects of electric discharge machining (EDM), also named, sparking wear caused by shaft currents and poor or increasingly diminishing dielectric strength of lubricants. A great effort has been done to study this problem in bearings, but it has not yet been the case for gears.

A Dual Power Split Electronic Continuously Variable Transmission (DPS-ECVT) with an input-split, output coupled, split-power-path configuration is proposed for improving overall system efficiency and range for electric vehicles. By modulating the power split ratio between the mechanical (planetary gear meshes) and electrical (Motor Generator Units) driveline components, a continuous range of gear ratios operating at higher efficiency is obtained. The proposed concept leverages two power-split units that lead to significantly reduced power flow through the electrical drivelines (compared with single speed EV transmissions as well as single power-split E-CVTs) while providing the same overall ratio spread for transmission operation.

Object detection and tracking is a central aspect of perception for autonomous vehicles. While there has been significant development in this field in recent years, many perception algorithms still struggle to provide reliable information in challenging weather conditions which include night-time, direct sunlight, glare, fog, etc. To achieve full autonomy, there is a need for a robust perception system capable of handling such challenging conditions. In this paper, we attempt to bridge this gap by proposing an algorithm that combines the strength of automotive radars and infra-red thermal cameras. We show that these sensors complement each other well and provide reliable data in poor visibility conditions. We demonstrate the advantages of a thermal camera over a visible-range camera in these situations and employ YOLOv3 for object detection.

As autonomous vehicles continue to grow in popularity, it is imperative for engineers to gain greater understanding of vehicle modeling and controls under different situations. Most research has been conducted on on-road ground vehicles, yet off-road ground vehicles which also serve vital roles in society have not enjoyed the same attention. The dynamics for off-road vehicles are far more complex due to different terrain conditions and 3D motion. Thus, modeling for control applications is difficult. A potential solution may be the incorporation of empirical data for modeling purposes, which is inspired by recent machine learning advances, but requires less computation. This thesis proposal presents results for empirical modeling of an off-road ground vehicle, Polaris XP 900. As a first step, data was collected for 2D planar motion by obtaining several velocity step responses. Multivariable polynomial surface fits were performed for the step responses.

This paper discusses different computer vision techniques investigated by the authors for identifying Emergency Vehicles (EV). Two independent EV identification frameworks were investigated: (1) A one-stage framework where an object detection algorithm is trained on a custom dataset to detect EVs, (2) A two-stage framework where an object classification algorithm is implemented in series with an object detection pipeline to classify vehicles into EVs and non-EVs. A comparative study is conducted for different multi-spectral feature vectors of the image, against several classification models implemented in framework 2. Additionally, a user-defined feature vector is defined and its performance is compared against the other feature vectors. Classification outputs from each of the frameworks are compared to the ground truth, and results are quantitatively listed to conclude upon the ideal decision rule.

The dimensions of an automobile seat are important factors affecting a driver’s seating comfort, fit, and satisfaction. In this regard, seat engineers put forth tremendous efforts to evaluate the dimensions of a product seat until the dimensions are consistent with the design reference in a computer aided design (CAD). However, the existing evaluation process is heavily reliant on seat engineers’ manual tasks which are highly repetitive, labor intensive, and time-demanding tasks. The objective of this study is to develop an automated system that can efficiently and accurately evaluate seat products by comparing estimated seat dimensions from a CAD model or a 3D scan model. By using the developed system, the evaluation time for comparing 18 seat dimensions on CAD and scan models has been substantially reduced to less than one minute, which is 99% time saving compared to two hours in the manual process.

This paper investigates the effect of the cetane number (CN) of a diesel fuel on the energy balance between a light duty (1.9L) and medium duty (4.5L) diesel engine. The two engines have a similar stroke to bore (S/B) ratio, and all other control parameters including: geometric compression ratio, cylinder number, stroke, and combustion chamber, have been kept the same, meaning that only the displacement changes between the engine platforms. Two Coordinating Research Council (CRC) diesel fuels for advanced combustion engines (FACE) were studied. The two fuels were selected to have a similar distillation profile and aromatic content, but varying CN. The effects on the energy balance of the engines were considered at two operating conditions; a “low load” condition of 1500 rev/min (RPM) and nominally 1.88 bar brake mean effective pressure (BMEP), and a “medium load” condition of 1500 RPM and 5.65 BMEP.

A comprehensive analysis of engine performance and fuel consumption was carried out to study Low Heat Rejection (LHR) concepts in the conventional light-duty diesel engine. From most previous studies on LHR diesel engines, thermal-barrier coatings (TBCs) have been recognized as a conventional way of insulating engine parts; while for the cases studied in this paper, the LHR concept is realized by altering engine coolant temperature (ECT). This paper presents engine simulation of a multi-cylinder, four-stroke, 1.9L diesel engine operating at 1500 rpm with five cases having different ECTs. The simulated results have been validated against experimental data. Calibration strategy for the engine simulation model is detailed in a systematic methodology for a better understanding of this simulation-development process. The calibrated model predicts the performance and fuel consumption within tolerated uncertainties.

Research on dual-fuel engine systems is regaining interest as advances in combustion reveal enabling features for attaining high efficiencies. Although this movement is manifested by development of advanced modes of combustion (e.g., reactivity controlled compression ignition combustion, or RCCI), the possibility of gasoline / diesel conventional combustion exists, which is characterized by premixed gasoline and direct-injected diesel fuel at conventional diesel injection timing. This study evaluates the effects of operating parameter on fuel conversion efficiency for gasoline / diesel conventional combustion in a medium duty diesel engine. Through adjustment of gasoline ratio (mass basis), injection timing and rail pressure (with adjustments to diesel fuel quantity to hold torque constant), the combustion, performance and emissions are studied.

Future electronics and photonics systems, weapons systems, and environmental control systems in aircraft will require advanced thermal management technology to control the temperature of critical components. Two-phase Thermal Management Systems (TMS) are attractive because they are compact, lightweight, and efficient. However, maintaining stable and reliable cooling in a two-phase flow system presents unique design challenges, particularly for systems with parallel evaporators during thermal transients. Furthermore, preventing ingress of liquid into a vapor compressor during variable-gravity operation is critical for long-term reliability and life. To enable stable and reliable cooling, a highly stable two-phase system is being developed that can effectively suppress flow instability in a system with parallel evaporators. Flow stability is achieved by ensuring that only single-phase liquid enters the evaporators.

A major decision to make in design projects is the selection of the best technology to provide some needed system functionality. In making this decision, the designer must consider the range of technologies available and the performance of each. During the useful life of the product, the technologies composing the product evolve as research and development efforts continue. The performance evolution rate of one technology may be such that even though it is not initially a preferably technology, it becomes a superior technology after a few years. Quantifying the evolution of these technologies complicates the technology selection decision. The selection of energy storage technology in the design of an electric car is one example of a difficult decision involving evolving technologies.

Tradeoff studies are a common part of engineering practice. Designers conduct tradeoff studies in order to improve their understanding of how various design considerations relate to one another and to make decisions. Generally a tradeoff study involves a systematic multi-criteria evaluation of various alternatives for a particular system or subsystem. After evaluating these alternatives, designers eliminate those that perform poorly under the given criteria and explore more carefully those that remain. One limitation of current practice is that designers cannot combine the results of preexisting tradeoff studies under uncertainty. For deterministic problems, designers can use the Pareto dominance criterion to eliminate inferior designs. Prior work also exists on composing tradeoff studies performed under certainty using an extension of this criterion, called parameterized Pareto dominance.

As emission standards become more stringent, many studies have been carried out to understand and reduce the emissions from diesel combustion engines, among which nitric oxide (NO) emissions and soot are known to have the trade-off relation during combustion processes. One aspect of this trade-off is manifested by the role radiation heat transfer plays on post-flame gas temperature, thus affecting NO formation. For example, a decrease in in-cylinder soot decreases radiation heat transfer causing an increase in post-flame gas temperature and partially contributing to the corresponding soot-NO relationship with an increase in NO formation. This topic has re-emerged with the increased use of biodiesel; a potential explanation for the so-called "biodiesel NOx penalty" is biodiesel's inherently reduced in-cylinder soot.

Finding a replacement for fossil fuels is critical for the future of automotive transportation. The compression ignition (CI) engine is an important aspect of everyday life by means of transportation and shipping of materials. Biodiesel is a viable augmentation for conventional diesel fuel in compression ignition engines. Biodiesel-fuelled diesel engines produce less particulate matter (PM) relative to conventional diesel and biodiesel has the ability to be a carbon dioxide (CO₂) neutral fuel, which may come under government regulation as a greenhouse gas. Although biodiesel is a viable diesel replacement and has certain emissions benefits, it typically also has a known characteristic of higher oxides of nitrogen (NOx) emissions relative to petroleum diesel. Advanced modes of combustion such as low temperature combustion (LTC) have attained much attention due to ever-increasing emission standards, and could also help reduce NOx in biodiesel.

Low temperature combustion (LTC) modes for reciprocating engines have been demonstrated with relatively high thermal efficiencies. These new combustion modes involve various combinations of stratification, lean mixtures, high levels of exhaust gas recirculation (EGR), multiple injections, variable valve timings, two fuels, and other such features. LTC engines may be attractive in combination with low heat rejection (LHR) engine concepts. The current work is aimed at evaluating the thermodynamic advantages of such a LTC-LHR engine. A thermodynamic cycle simulation was used to evaluate the effect of cylinder wall temperature on the engine performance, emissions and second law characteristics. An automotive engine at 2000 rpm with a bmep of 900 kPa was considered. Both a conventional and a LTC design were compared. The LTC engine realized small gains in efficiency whereas the conventional engine did not realize any significant gains as the cylinder wall temperature was increased.

The need of upfront modeling, simulation and design optimization has been ever increasing during full vehicle product development process. The overall vehicle system and component subsystem performances remain critical considerations for making final product release decision. With these challenges in mind, the work of this paper discusses the development of feasible CAE methods, tools, and processes for multi-objective design optimization. A full integrated tractor trailer truck vehicle is used as an example to demonstrate this capability. The proposed approach allows several design objectives to be simultaneously optimized, which might otherwise be extremely difficult to achieve with experimental methods.

In the wake of global focus shifting towards the health and conservation of the planet, greater importance is placed upon the hazardous emissions of our fossil fuels, as well as their finite supply. These two areas remain intense topics of research in order to reduce greenhouse gas emissions and increase the fuel efficiency of vehicles, a sector which is a major contributor to society's global CO₂ emissions and consumer of fossil-fuel resources. A particular solution to this problem is the diesel engine, with its inherently fuel-lean combustion, which gives rise to low CO₂ production and higher efficiencies than other potential powertrain solutions. Diesel engines, however, typically exhibit higher nitrogen oxides (NOx) and soot engine-out emissions than their gasoline counterparts. NOx is an ingredient to ground-level ozone production and smoke is a possible carcinogen, both of which are facing stricter emissions regulations.

Due to its ease of use in diesel engines, its presumably lower carbon footprint, and its potential as a renewable fuel, biodiesel has attracted considerable attention in technological development and research literature. Much literature is devoted to evaluating the injection and combustion characteristics of biodiesel fuel using unit injectors, where injection pressure and timing are regulated within the same unit. The use of common rail fuel systems, where fuel pressure is now equally governed to each injector (of a multi-cylinder engine), may change the conventionally accepted impact of biodiesel on injection and combustion characteristics. The objectives of this study are to characterize the responses of an electronically-controlled common-rail fuel injector (in terms of timing and duration) when delivering either 100% palm olein biodiesel or 100% petroleum diesel for a diesel engine, and correlate potential changes in injector characteristics to changes in combustion.

An engine cycle simulation which included the second law of thermodynamics was used to examine the engine performance and the thermodynamic characteristics of a spark ignition engine as functions of the oxygen inlet concentration. A wide range of oxygen inlet concentrations (12% to 40% by volume) was considered. For oxygen inlet concentrations less than 21%(v), EGR was used, and for oxygen inlet concentrations greater than 21%(v), oxygen enriched inlet air was used. Two EGR configurations were considered: (1) cooled and (2) adiabatic. In general, engine efficiencies decreased, heat transfer increased, nitric oxide emissions increased, and the destruction of availability (exergy) decreased as the oxygen concentration increased.

Biodiesel remains an alternative fuel of interest for use in diesel engines. A common characteristic of biodiesel, relative to petroleum diesel, is a lowered heating value (or energy content of the fuel). A lower heating value of the fuel would, presuming all other parameters are equal, result in decreased engine torque. Since engine torque is often user-demanded, the lower heating value of the fuel generally translates into increased brake specific fuel consumption. Several literature report this characteristic of biodiesel. In spite of the wealth of fuel consumption characteristic data available for biodiesel, it is not clear how other engine performance parameters may change with the use of biodiesel. Characterizing these parameters becomes complicated when considering the interactions of the various engine systems, such as a variable geometry turbocharger with exhaust gas recirculation.