Search Results

Modeling and simulation are commonly used in all stages of the design process. This is particularly vital to the success of systems engineering projects where the system under consideration is complex and involves interactions between many interdisciplinary subsystems. In the refining stages of the design process (after concept selection), models and simulations can be used to refine and optimize a system with respect to the decision maker’s objectives. In this paper, a dynamic model of a hydraulic backhoe serves as a test-bed for a large-scale sensitivity analysis and subsequent optimization of the most significant design parameters. The model is optimized under uncertainty with respect to a multi-attribute utility function that includes fuel consumption, cost of the key components, and machine performance.

The fuel-ambient mixture in vaporized fuel jets produced by liquid sprays is fundamental to the performance and operation of engines. Unfortunately, experimental difficulties limit the direct measurement of local fuel-ambient mixture, inhibiting quantitative assessment of mixing. On the other hand, measurement of global quantities, such as the jet penetration rate, is relatively straightforward. Simplified models to predict local fuel-ambient mixture have also been developed, based on these global parameters. However, experimental data to validate these models over a range of conditions is needed. In the current work, we perform measurements of jet global quantities such as vapor-phase penetration, liquid-phase penetration, spreading angle, and nozzle flow coefficients over a range of conditions in a high-temperature, high-pressure vessel.

Power-split hybrid-electric vehicles (HEVs) employ two power paths between the internal combustion (IC) engine and the driven wheels routed through gearing and electric machines (EMs) composing an electrically variable transmission (EVT). The EVT allows IC engine control such that rotational speed can be independent of vehicle speed at all times. By breaking the rigid mechanical connection between the IC engine and the driven wheels, the EVT allows the IC engine to operate in the most efficient region of its characteristic brake specific fuel consumption (BSFC) map. If the most efficient IC engine operating point produces more power than is requested by the driver, the excess IC engine power can be stored in the energy storage system (ESS) and used later. Conversely, if the most efficient IC engine operating point does not meet the power request of the driver, the ESS delivers the difference to the wheels through the EMs.

Turboelectric propulsion is a technology that can potentially reduce aircraft noise, increase fuel efficiency, and decrease harmful emissions. In a turbo-electric system, the propulsor (fans) is no longer connected to the turbine through a mechanical connection. Instead, a superconducting generator connected to a gas turbine produces electrical power which is delivered to distributed fans. This configuration can potentially decrease fuel burn by 10% [1]. One of the primary challenges in implementing turboelectric electric propulsion is designing the power distribution system to transmit power from the generator to the fans. The power distribution system is required to transmit 40 MW of power from the generator to the electrical loads on the aircraft. A conventional aircraft distribution cannot efficiently or reliably transmit this large amount of power; therefore, new power distribution technologies must be considered.

This paper presents a comparative analysis of two different power-split hybrid-electric vehicle (HEV) powertrains using backward-looking simulations. Compared are the front-wheel drive (FWD) Toyota Hybrid System II (THS-II) and the FWD General Motors Allison Hybrid System II (GM AHS-II). The Toyota system employs a one-mode electrically variable transmission (EVT), while the GM system employs a two-mode EVT. Both powertrains are modeled with the same assumed mid-size sedan chassis parameters. Each design employs their native internal combustion (IC) engine because the transmission's characteristic ratios are designed for the respective brake specific fuel consumption (BSFC) maps. Due to the similarities (e.g., power, torque, displacement, and thermal efficiency) between the two IC engines, their fuel consumption and performance differences are neglected in this comparison.

In this study we identify components of a typical biodiesel fuel and estimate both their individual and mixed thermo-physical and transport properties. We then use the estimated mixture properties in computational simulations to gauge the extent to which combustion is modified when biodiesel is substituted for conventional diesel fuel. Our simulation studies included both conventional diesel combustion (DI) and premixed charge compression ignition (PCCI). Preliminary results indicate that biodiesel ignition is significantly delayed due to slower liquid evaporation, with the effects being more pronounced for DI than PCCI. The lower vapor pressure and higher liquid heat capacity of biodiesel are two key contributors to this slower rate of evaporation. Other physical properties are more similar between the two fuels, and their impacts are not clearly evident in the present study.

A plug-in hybrid electric vehicle (PHEV) design with design parameters electric motor size, engine size, battery capacity, and battery chemistry type, is optimized with minimum cost as a measure of merit. The PHEV is required to meet a fixed set of performance constraints consisting of 0-60 mph acceleration, 50-70 mph acceleration, 0-30 mph acceleration in all electric operation, top speed, grade ability, and all electric range. The optimization is carried out for values of all electric range of 10, 20, and 40 miles. The social and economic impacts of the optimum designs in terms of reduced gasoline consumption and carbon emissions reduction are calculated. Argonne National Laboratory's Powertrain Systems Analysis Toolkit is used to simulate the performance and fuel economy of the PHEV designs. The costs of different PHEV components and the present value of battery replacements over the vehicle's life are used to determine the design's drivetrain cost.

The design of complex systems, such as commercial aircraft, has drastically changed since the middle 1970's. Budgetary and airline requirements have forced many aerospace companies to reduce the amount of time and monetary investments in future revolutionary concepts and design methods. The current NASA administration has noticed this shift in aviation focus and responded with the “Three Pillars for Success” program. This program is a roadmap for the development of research, innovative ideas, and technology implementation goals for the next 20 years. As a response to this program, the Aerospace Systems Design Laboratory at Georgia Tech is developing methods whereby forecasting techniques will aid in the proper assessment of future vehicle concepts. This method is called Technology Impact Forecasting (TIF). This method is applied to a medium-range, intra-continental, commercial transport concept.

This paper outlines a comprehensive, structured, and robust methodology for decision making in the early phases ofaircraft design. The proposed approach is referred to as the Technology Identification, Evaluation, and Selection (TIES) method. The seven-step process provides the decision maker/designer with an ability to easily assess and trade-off the impact of various technologies in the absence of sophisticated, time-consuming mathematical formulations. The method also provides a framework where technically feasible alternatives can be identified with accuracy and speed. This goal is achieved through the use of various probabilistic methods, such as Response Surface Methodology and Monte Carlo Simulations. Furthermore, structured and systematic techniques are utilized to identify possible concepts and evaluation criteria by which comparisons could be made.

The objective of this paper is to examine ways in which to implement probabilistic design methods in the aircraft engine preliminary design process. Specifically, the focus is on analytically determining the impact of uncertainty in engine component performance on the overall performance of a notional large commercial transport, particularly the impact on design range, fuel burn, and engine weight. The emphasis is twofold: first is to find ways to reduce the impact of this uncertainty through appropriate engine cycle selections, and second is on finding ways to leverage existing design margin to squeeze more performance out of current technology. One of the fundamental results shown herein is that uncertainty in component performance has a significant impact on the overall aircraft performance (it is on the same order of magnitude as the impact of the cycle itself).

Battery modeling is of major concern for Hybrid Electric Vehicle (HEV) and Electric vehicle (EV) modeling. The major issue lies in characterizing the battery power output in relation to battery's State of Charge (SOC) in various application conditions. In particular, the challenge is associated with the difficulty that the characteristic parameters of the battery, i.e. the accurate data on the open circuit voltage and the internal resistance are hardly obtainable in practical conditions. In this paper, a battery capacity representation and a practical way of battery modeling is introduced for simulation model development based on the experimental data. A realistic way of battery SOC representation is generated from the battery output data. Empirical formulation is derived from the data to correlate the battery current, voltage output with the battery SOC.

The Georgia Tech FutureTruck Team has designed a strong parallel split-hybrid powertrain for the model year 2002 Ford Explorer SUV. The modified powertrain uses a Lincoln LS 3.0L, V-6, DOHC, aluminum engine driving the rear axle. An AC-150 from AC Propulsion is coupled to the front wheels through a 3.75:1 Auburn Gear speed reducer. This split-hybrid structure fits well into the Explorer and is to manufacture. The interior cabin has been maintained in a stock configuration by carefully integrating the added instrumentation and electric drive controls into the dash and console. The toque-blending hybrid electric control is designed to be charge sustaining such that the refueling procedures match those of the stock vehicle. When fully operational, this powertrain is expected to yield a net 25% increase in fuel efficiency while lowering emissions without any sacrifice in customer acceptability.

This paper attempts to assess the benefits of a unique distributed propulsion concept, known as the Multi-Gas Generator Fan (MGGF) system, over conventional turbofan engines on civilian vertical takeoff and landing (VTOL) applications. The MGGF-based system has shown the potential to address the fundamental technical challenge in designing a VTOL aircraft: the significant mismatch between the power requirements at lift-off/hover and cruise. Vehicle-level performance and sizing studies were implemented using the Grumman Design 698 tilt-nacelle V/STOL aircraft as a notional personal air vehicle (PAV), subjected to hypothetical single engine failure (SEF) emergency landing requirements and PAV mission requirements.

The objective of this paper is to develop a generalized loss management model to account for the usage of thermodynamic work potential in vehicles of any type. The key to accomplishing this is creation of a differential representation for vehicle loss as a function of operating condition. This differential model is then integrated through time to obtain an analytical estimate for total usage (and loss) of work potential consumed by each loss mechanism present during vehicle operation. The end result of this analysis is a better understanding of how the work potential initially present in the fuel, batteries, etc. is partitioned amongst all losses relevant to the vehicle's operation. The loss partitioning estimated from this loss management model can be used in conjunction with cost accounting systems to gain a better understanding of underlying drivers on vehicle manufacturing and operating costs.

Fuel supercriticality has recently received significant attention due to the elevated pressures and temperatures that directly-injected (DI) fuel sprays encounter in modern internal combustion (IC) engines. This paper presents a theoretical examination of conventional and alternative DI fuels at conditions relevant to the operation of compression ignition (CI) engines. The focus is to identify the conditions under which the injected liquid fuel can bypass the atomization process and directly transition to a diffusional mixing regime with the chamber gas. Evaluating the microscopic length-scales of the phase boundary associated with the injection of liquid nitrogen into its own vapor, it is found that the conventional threshold based on the interfacial Knudsen number (i.e. Kn = 0.1) does not adequately quantify the direct transition between sub- and supercriticality. Instead, a threshold that is an order of magnitude smaller is more appropriate for this purpose.

Using measurable physical input variables, an implementable control algorithm for parallel architecture plug-in and non-plug-in hybrid electric vehicle (PHEV and HEV) powertrains is presented. The control of the electric drive is based on an algebraic mapping of the accelerator pedal position, the battery state-of-charge (SOC), and the vehicle velocity into a motor controller input torque command. This mapping is developed using a sequential linearization control (SLC) methodology. The internal combustion engine (ICE) control uses a modified accelerator pedal to throttle plate angle using an adjustable gain parameter that, in turn, determines the sustained battery SOC. Searches over an admissible control space or the use of pre-defined look-up tables are thus avoided. Actual on-road results for a Ford Explorer with a through-the-road (TTR) hybrid powertrain using this control methodology are presented.

This paper presents a detailed design study and associated considerations supporting the development of high-performance plug-in hybrid electric vehicles (PHEVs). Due to increasingly strict governmental regulations and increased consumer demand, automotive manufacturers have been tasked with the reduction of fuel consumption and greenhouse gas (GHG) emissions. PHEV powertrains can provide a needed balance in terms of fuel economy and vehicle performance by exploiting regenerative braking, pure electric vehicle operation, engine load-point shifting, and power-enhancing hybrid traction modes. Thus, properly designed PHEV powertrains can reduce fuel consumption while increasing vehicle utility and performance.

Hybrid-electric gas turbine generators are considered a promising technology for more efficient and sustainable air transportation. The Ohio State University is leading the NASA University Leadership Initiative (ULI) Electric Propulsion: Challenges and Opportunities, focused on the design and demonstration of advanced components and systems to enable high-efficiency hybrid turboelectric powertrains in regional aircraft to be deployed in 2030. Within this large effort, the team is optimizing the design of the battery energy storage system (ESS) and, concurrently, developing a supervisory energy management strategy for the hybrid system to reduce fuel burn while mitigating the impact on the ESS life. In this paper, an energy-based model was developed to predict the performance of a battery-hybrid turboelectric distributed-propulsion (BHTeDP) regional jet.

Societal demands of recent years have increasingly pressured the development of greener technologies in all sectors of the nation's transportation infrastructure, including that of civilian aviation. This study explores the concept of electric-drive aeropropulsion, aided by high-temperature superconducting technology, as an enabler for enhancing the environmental characteristics at the air-vehicle level. Potential improvements in the areas of aircraft noise, emissions, and energy efficiency are discussed in the context of supporting the latest strategic goals of leading governmental organizations.