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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.

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.

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.

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.

Some of the mobility problems faced by the spinal cord injury patient are presented in this paper. Existing automobile hand controls for the handicapped are discussed and current efforts at evaluation and standardization of this equipment are described. Design constraints are outlined for the development of new equipment to allow the more severely handicapped to drive.

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.

Two parallel HEV control concepts: ‘thermostat’ and ‘power split’ are compared in this paper. To achieve a substantial improvement in fuel economy, the ‘thermostat’ or ‘on/off’ control technique intended to improve the fuel efficiency of a series HEV has been adopted and designed for parallel HEV. Among different ‘power split’ concepts developed for parallel hybrids only the ‘electrically assist’ algorithm is considered in this paper. These two control concepts are compared for three parallel HEV architectures: pre-transmission, post-transmission and continuous variable transmission hybrids. The comparison study also includes the effect of hybridization factor-the ratio of the electric power to the total propulsion power. The matrices of comparison are level of performance, energy consumption and exhaust emissions. The SAE J1711 partial charge test procedure is followed.

There is a clear trend towards Hybrid Electric Vehicles (HEV) due to the environmental concerns. On the other hand, with increasing hotel and ancillary loads and replacement of more engine driven mechanical and hydraulic loads with electrical loads, automotive systems are becoming more electric. This is the concept of More Electric Cars (MEC) which necessitates going to a higher voltage such as 42V for conventional cars. Can the evaluation of the 42V MEC smoothly lead to the Hybrid Electric Vehicles (HEV) and More Electric Hybrid Vehicles (MEHV)? In this paper, we investigate the feasibility of 42V & 14+42V electrical power systems for MEHV. Technical issues of such a solution are explored in detail.

Vehicle dynamics requires extended-speed, constant-power operation from the propulsion system in order to meet the vehicle's operating constraints (e.g., initial acceleration and gradeability) with minimum power. Decrease in power rating will decrease the volume of the energy storage system. However, extending the constant power operating range of the electric drives increases its rated torque, thereby, increasing motor volume and weight. This paper investigates the effect of extended constant power operation on battery driven electric vehicle (BEV) propulsion system taking the change in motor weight and battery volume into account. Five BEV systems with five traction drive having different base speeds are simulated for this study. The performances of the BEVs are obtained using FUDS and HWYFET drive cycles. Two EV-HEV software packages ‘V-ELPH’ developed by Texas A&M University and ‘ADVISOR’ from NREL are used for simulation testing.

Short circuit incidents on traction motors can cause ‘wheel-locking’ on the vehicle, and may have an adverse impact on vehicle stability. This paper investigates the necessity of fault-tolerant motors for EV and HEV traction applications. Reaction of resulting fault torques differ along with electric motor types and fault variety. The paper analyzes the short-circuit behavior of three basic motor types: permanent magnet, induction and switched reluctance motor. The analysis is based on the transient simulation of the three most common inverter short-circuit cases and their effect on vehicle stability.

The recent growing interest in electric vehicle (EV) and hybrid electric vehicle (HEV) demands for an efficient, reliable and economical motor drive for electric propulsion. However, searching for a suitable traction motor becomes quite involved when vehicle dynamics and system architecture are considered. This paper makes an in-depth investigation on two highly important traction motor characteristics, extended speed range-ability and energy efficiency, from vehicular system perspective. The influences of these two motor drive features on a pure EV, a post-transmission, and two pre-transmission parallel HEV with 20% and 50% hybridization are studied in this paper. Two EV-HEV software packages ‘V-ELPH’ developed by Texas A&M University and ‘ADVISOR’ from NREL are used for simulation purposes. Based on the results in this paper, a systematic method is developed regarding the selection of traction drives for EV and HEV propulsion systems.

An electromechanical gear is presented along with design examples utilizing the electromechanical gear in hybrid electric vehicle drive trains. The designs feature the electromechanical gear (the Transmotor) in place of traditional mechanical transmissions and/or gearing mechanisms. The transmotor is an electric motor suspended by its shafts, in which both the stator and the rotor are allowed to rotate freely. The motor thus can provide positive or negative rotational energy to its shafts by either consuming or generating electrical energy. A design example is included in which the transmotor is installed on the output shaft of an internal combustion engine. In this arrangement the transmotor can either increase or decrease shaft speed by applying or generating electrical power, allowing the ICE to operate with a constant speed.

The effect on vehicle performance of extending the constant power operating mode of electric drive motors for electric and hybrid vehicles is presented in this paper. Modern electric and hybrid vehicle designers have the selection of several technologies to choose from when selecting an electric drive motor. Each motor technology exhibits a particular torque vs. speed characteristic. Many of these technologies, most notably the switched reluctance machine, have capitalized on iron and copper utilization, extending their useful speed range. However, the extended speed capabilities of these motor drives have vehicle performance consequences. It is presented that vehicle performance is affected by changing the torque-speed characteristics of the drive motor. The extended constant power speed range motor can have smaller rated power than otherwise but suffer high speed passing performance.

The last quarter century has seen CO2 emissions increase at a steadily increasing rate. In the U.S.A. alone from 1970 to 1992 the CO2 emissions have increased from 5.5 billion metric tons of carbon dioxide to 6.6 bmt. The transportation industry contributes currently (1991 figures) 24.7% of the total emissions from the United States. Transportation utilization has grown faster, however, but more efficient vehicles allow for more travel without increasing the CO2 proportionally. The advancements made in the 1980s have reduced emissions by 21 million tons of CO2 per year on average. Electric Vehicles have been a proposed method of reducing the CO2 emissions due to transportation. Electric vehicles produce no emissions while driving, making them ideal candidates for heavily polluted and concentrated areas such as urban locations. However, it is debatable if electric vehicles are feasible on the global scale of CO2 reduction.

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.

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.