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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.

This paper presents calculations of engine flows by using the Partially-Averaged Navier Stokes (PANS) method (Girimaji [1]; [2]). The PANS is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. The PANS method was successfully used for many applications but mainly on static geometries, e.g. Basara et al. [3]; [4]. This is due to the calculation of the cut-off control parameter which requires that the resolved kinetic energy is known and this is usually obtained by suitably averaging of the resolved field. Such averaging process is expensive and impractical for engines as it would require averaging per cycles.

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.

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.

The Articulated Suspension Exploratory Platform (ASEP) is developed in an effort to improve the characteristics and capabilities of the existing recently developed Surface Ground Mobility Platform SGMP. Special attention is placed on the design of the passive suspension mechanism in order for the platform to be suitable for operation in remote and challenging environments. To improve the capacity of the suspension and the overall quality, different designs have been analyzed based on a number of system requirements. The advantages of the final design are its linear motion, obstacle capacities, slope climbing and down-hill stability, as well as compact size and low cost.

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.

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.

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.

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.

Sending humans to the moon and Mars in support of NASA’s Vision for Space Exploration (VSE) presents a variety of operational environments in which astronauts will need to wear a space suit, both inside the vehicle and during Extravehicular Activity (EVA). Four feasible suit architectures were proposed by NASA in terms of the number and type of suits needed to enable task performance in scenarios ranging from launch and entry operations to conducting EVA’s in microgravity and on planetary surfaces. This study was aimed at defining space suit operational and functional needs across the spectrum of mission elements called out in the VSE, identifying temporal and technical design drivers, and establishing appropriate trade variables with associated weighting factors for analyzing the proposed architecture options. Recommendations from the analysis are offered for consideration in selecting from the four options.

Military and civilian vehicles are moving towards more electrification, in response to the increasing demand for multi-mode missions, fuel consumption and emissions reduction, and dual use electrical and electronic components. Consequently, the vehicle electric load is increasing rapidly. For military vehicles, these electrical loads include: the loads for electric traction (EV and HEV), cabin climate conditioning, vehicle control and actuation, actuation by wire (X by wire), sensors, reconnaissance, communications, weapons etc. All these requirements need to be supported by an efficient, fast responding and high capacity energy storage system. The electric load of a vehicle can be decomposed into two components--- static and dynamic loads. The static component is slowly varying power with limited magnitude, whereas the dynamic load is fast varying power with large magnitude. The energy storage system, accordingly, comprises of two basic elements.

A concept of “driving situation awareness”-driven energy management system for parallel hybrid electric vehicles (HEVs) is introduced. The essential feature of the proposed energy management system is to assess the driving environment (in terms of facility type combined with traffic congestion level) using long and short term statistical features of the drive cycle. Subsequently, this knowledge is provided to a system that makes intelligent decisions with respect to the torque distribution and charge sustenance tasks. Simulation work was carried out for the validation of proposed system, and the results reveal its viability for energy management of parallel hybrid vehicles.

Due to their harsh operating environments, military vehicle drive trains have special requirements. These special requirements are usually represented by hill climbing ability, obstacle negotiation, battlefield cross country travel, hard acceleration, high speed, etc. These special requirements need the vehicle drive train to have a wider torque and speed range characteristics than commercial vehicles. We have proved that larger constant power ratio in electric motor can significantly enhance the vehicle acceleration performance. In other words, for the same acceleration performance, large constant power ratio can minimize the power rating of the traction motor drive, thus minimizing the power rating of the power source (batteries for instance). Actually, extension of the constant power range can also significantly enhance the gradeability, which is crucial for military vehicles.

A fuzzy logic technique is presented in this paper for sensorless speed and position identification of vector-controlled PWM inverterfed PMSM drives used in EV/HEV propulsion systems. Fuzzy logic is used to estimate the rotor speed and position. Operation of the drive is studied by numerical simulation. The performance for different drive conditions is also analyzed and the results are shown in the paper. Simulation results show that the proposed control method can be effectively used in controlling the PMSM drives with high performance for EV/HEV applications. It is found that the fuzzy logic system is reliable without using any speed or position sensor.