Search Results

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.

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.

Most studies on supervisory controllers of hybrid electric vehicles consider only fuel economy in the objective function. Taking into consideration the importance of the energy storage system health and its impact on the vehicle’s functionality, cost, and warranty, recent studies have included battery degradation as the second objective function by proposing different energy management strategies and battery life estimation methods. In this paper, a rule-based supervisory controller is proposed that splits the torque demand based not only on fuel consumption, but also on the battery capacity fade using the concept of severity factor. For this aim, the severity factor is calculated at each time step of a driving cycle using a look-up table with three different inputs including c-rate, working temperature, and state of charge of the battery. The capacity loss of the battery is then calculated using a semi-empirical capacity fade model.

After several decades of human spaceflight, the community of space-faring nations has accumulated a diverse and sometimes harrowing history of toxicological events that have plagued human space endeavors almost from the very beginning. Some lessons have been learned in ground-based test beds and others were discovered the hard way - when human lives were at stake in space. From such lessons one can build a risk-management framework for toxicological events to minimize the probability of a harmful exposure, while recognizing that we cannot predict all possible events. Space toxicologists have learned that relatively harmless compounds can be converted by air revitalization systems into compounds that cause serious harm to the crew.

In the design of a new space suit it is necessary to have requirements that define what mobility space suit joints should be capable of achieving in both a system and at the component level. NASA elected to divide mobility into its constituent parts -- range of motion (ROM) and torque -- in an effort to develop clean design requirements that limit subject performance bias and are easily verified. Unfortunately, the measurement of mobility can be difficult to obtain. Current technologies, such as the Vicon motion capture system, allow for the relatively easy benchmarking of range of motion (ROM) for a wide array of space suit systems. The ROM evaluations require subjects in the suit to accurately evaluate the ranges humans can achieve in the suit. However, when it comes to torque, there are significant challenges for both benchmarking current performance and writing requirements for future suits.

Shorter development times in the automotive industry are leading to the increased use of computer simulation in the vehicle design cycle to pre-optimize vehicle concepts. The focus of the work presented in this study is vehicle dynamic performance in different driving maneuvers. More specifically this paper presents a methodology for simulation-based parameter design of vehicles for excellent performance in multiple maneuvers. The model used in the study consists of eight degrees-of-freedom and has been validated previously. The vehicle data used is for a commercially available vehicle. A number of different driving scenarios (maneuvers) based on ISO standards for transient dynamic behavior are implemented and performance indices are calculated for each individual maneuver considered. Vehicle performance is assessed based on the performance indices.

With recent advances in electric vehicles, there is a plethora of powertrain topologies and components available in the market. Thus, the performance of electric vehicles is highly sensitive to the choice of various powertrain components. This paper presents a multi-objective optimization model that can optimally select component sizes for batteries, supercapacitors, and motors in regular passenger battery-electric vehicles (BEVs). The BEV topology presented here is a hybrid BEV which consists of both a battery pack and a supercapacitor bank. Focus is placed on optimal selection of the battery pack, motor, and supercapacitor combination, from a set of commercially available options, that minimizes the capital cost of the selected power components, the fuel cost over the vehicle lifespan, and the 0-60 mph acceleration time. Available batteries, supercapacitors, and motors are from a market survey.

This research proposes a control system for Spark Ignition (SI) engines with external Exhaust Gas Recirculation (EGR) based on model predictive control and a disturbance observer. The proposed Economic Nonlinear Model Predictive Controller (E-NMPC) tries to minimize fuel consumption for a number of engine cycles into the future given an Indicated Mean Effective Pressure (IMEP) tracking reference and abnormal combustion constraints like knock and combustion variability. A nonlinear optimization problem is formulated and solved in real time using Sequential Quadratic Programming (SQP) to obtain the desired control actuator set-points. An Extended Kalman Filter (EKF) based observer is applied to estimate engine states, combining both air path and cylinder dynamics. The EKF engine state(s) observer is augmented with disturbance estimation to account for modeling errors and/or sensor/actuator offset.

This paper proposes a novel 1-ϕ, Cuk based on-board electric vehicle (EV) charger with least power components. The proposed EV charger has a special feature to achieve power factor correction (PFC) at AC grid without requirement of the grid voltage and current sensors which cuts the cost and increases the power density of the EV charger along with robustness to noise. The automatic PFC at AC grid is accomplished by operating the output DC inductor in discontinuous conduction mode (DCM). The proposed EV charger necessitates a minimal number of power components for positive and negative half cycles of AC grid which improves the overall efficiency of the system. This is possible due to the combination of inverting and non-inverting Cuk converters are used for each half cycle of the AC grid. Further, the presence of output inductor in the EV charger reduces the ripples in the output current which is not common with all the existing chargers in the literature.

Multi-material design is one of the trending methods for automakers to achieve lightweighting cost-efficiently and meet stringent regulations and fuel efficiency concerns. Motivated by this trend, the hybrid single-shot (HSS) process has been recently introduced to manufacture thermoset-thermoplastic composites in one single integrated operation. Although this integration is beneficial in terms of reducing the cycle time, production cost, and manufacturing limitations associated with such hybrid structures, it increases the process complexity due to the simultaneous filling, forming, curing, and bonding actions occurring during the process. To overcome this complexity and have a better understanding on the interaction of these physical events, a quick yet accurate simulation of the HSS process based on an experimentally calibrated numerical approach is presented here to elucidate the effect of different process settings on the final geometry of the hybrid part.

Electrified transportation has received significant interest recently because of sustainable and clean energy goals. However, the degradation of electrical components such as energy storage systems raises system reliability and economic concerns. In this paper, a prognostic-based control strategy is proposed for hybrid electric vehicles (HEVs) to abate the degradation of energy systems. Degradation forecasting models of electrical components are developed to predict their degradation paths. The predicted results are then used to control HEVs in order to reduce the degradation of components.

Over the last couple decades, there has been a growing interest in incorporating commercial off-the-shelf (COTS) technologies and open standards in the design of human-rated spacecraft. This approach is intended to reduce development and upgrade costs, lower the need for new design work, eliminate reliance on individual suppliers, and minimize schedule risk. However, it has not traditionally been possible for COTS solutions to meet the high reliability and fault tolerance requirements of systems implementing critical spacecraft functions. Byzantine faults are considered particularly dangerous to such systems because of their ability to escape traditional means of fault containment and disrupt consensus between system components. In this paper, we discuss the design of a voting protocol using Time-Triggered Ethernet capable of achieving data integrity in the presence of a single Byzantine fault.

As engines are equipped with an increased number of control actuators to meet fuel economy targets they become more difficult to control and calibrate. The large number of control actuators encourages the investigation of physics-based control strategies to reduce calibration time and complexity. Of particular interest is spark timing control and calibration since it has a significant influence on engine efficiency, emissions, vibration and durability. Spark timing determination to achieve a desired combustion phasing is currently an empirical process that occurs during the calibration phase of engine development. This process utilizes a large number of stored surfaces and corrections to account for the wide range of operating environments and conditions that a given engine will experience. An obstacle to realizing feedforward physics-based combustion phasing control is the requirement for an accurate and fast combustion model.

Accurate in-cylinder air charge estimation is important for engine torque determination, controlling air-to-fuel ratio, and ensuring high after-treatment efficiency. Spark ignition (SI) engine technologies like variable valve timing (VVT) and exhaust gas recirculation (EGR) are applied to improve fuel economy and reduce pollutant emissions, but they increase the complexity of air charge estimation. Increased air-path complexity drives the need for cost effective solutions that produce high air mass prediction accuracy while minimizing sensor cost, computational effort, and calibration time. A large number of air charge estimation techniques have been developed using a range of sensors sets combined with empirical and/or physics-based models. This paper provides a technical review of research in this area, focused on SI engines.

The primary objectives of this study were to determine the factors that affect stability during locomotion in both lunar and martian gravity environments and to determine the criteria needed to enhance stability and traction. This study tested the effects of changing the speed of locomotion and the pattern of locomotion under three gravity conditions. The results showed that as the gravity level decreased, the amount of vertical and horizontal forces dropped significantly. The results also showed that there are some similarities across gravity levels with regard to changing the speed as well as the pattern of locomotion. In general, an increase in the speed resulted in an increase in the vertical and the horizontal forces. A change in the pattern of locomotion showed that even at reduced gravity, it will be more difficult to stop than compared to continue or start the motion.

Fuel efficiency improvement in automobiles has been a topic of great interest over the past few years, especially with the introduction of the new CAFE 2025 standards. Although there are multiple ways of improving the fuel efficiency of an automobile, lightweighting is one of the most common approaches taken by many automotive manufacturers. Lightweighting is even more significant in electric vehicles as it directly affects the range of the vehicle. Amidst this context of lightweighting, the use of composite materials as alternatives to metals has been proven in the past to help achieve substantial weight reduction. The focus of using composites for weight reduction has however been typically limited to major structural components, such as BiW and closures, due to high material costs. Secondary structural components which contribute approximately 30% of the vehicle weight are usually neglected by these weight reduction studies.

Designing an efficient cooling system with low power consumption is of high interest in the automotive engineering community. Heat generated due to the propulsion system and the on-board electronics in ground vehicles must be dissipated to avoid exceeding component temperature limits. In addition, proper thermal management will offer improved system durability and efficiency while providing a flexible, modular, and reduced weight structure. Traditional cooling systems are effective but they typically require high energy consumption which provides motivation for a paradigm shift. This study will examine the integration of passive heat rejection pathways in ground vehicle cooling systems using a “thermal bus”. Potential solutions include heat pipes and composite fibers with high thermal properties and light weight properties to move heat from the source to ambient surroundings.

A Total Organic Carbon (TOC) Analyzer has been developed for a Life Sciences Risk Mitigation Flight Experiment to be conducted on Spacehab and the Russian space station, Mir. Initial launch is scheduled for December 1996 (flight STS-81). The analyzer will be tested on the Orbiter in the Spacehab module, including when the Orbiter is docked at the Mir space station. The analyzer is scheduled to be launched again in May 1997 (STS-84) when it will be transferred to Mir. During both flights the analyzer will measure the quality of recycled and ground-supplied potable water on the space station. Samples will be archived for later return to the ground, where they will be analyzed for comparison to in-flight results. Water test samples of known composition, brought up with the analyzer, also will be used to test its performance in microgravity. Ground-based analyses of duplicates of those test samples will be conducted concurrently with the in-flight analyses.

The emphasis on vehicle fuel economy and tailpipe emissions, coupled with a trend toward greater system functionally, has prompted automotive engineers to develop on-board control systems with increased requirements and complexity. Mainstream engine controllers regulate fuel, spark, and other subsystems using custom solutions that incorporate off-the-shelf hardware components. Although the digital processor core and the peripheral electronics may be similar, these controllers are targeted to fixed engine architectures which limit their flexibility across vehicle platforms. Moreover, additional software needs are emerging as electronics continue to permeate the ground transportation sector. Thus, automotive controllers will be required to assume increased responsibility while effectively communicating with distributed hardware modules.

Autonomous vehicles have the potential to provide mobility to individuals who experience transportation disadvantages due to the inability to drive as a result of physical, cognitive or visual limitations/impairments as well as able-bodied individuals with no/limited desire to drive. Individuals who do not have easy access to transportation have social, academic, health, and career disadvantages in comparison to their peers. Fully autonomous vehicles have the potential to offer mobility solutions to these individuals. A user-centered design approach was utilized by a multidisciplinary team of engineers, human factors specialists, and designers to develop future vehicle features for a broad range of users.