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Rising Above the Cloud - Toward High-Rate Delay-Tolerant Networking in Low-Earth Orbit

The High Data Rate Architecture (HiDRA) project is implementing a High-rate Delay Tolerant Networking (HDTN) capability that can support Low Earth Orbit (LEO) applications and environments. The present state of the effort, future work, and other elements of the work to date are described in this paper. This implementation is intended to support applications that run at 1+ Gbps, per the requirements of modern optical and high-frequency RF links. Uniquely, this implementation is also tuned to support relay and data trunking applications, which might require support for large numbers of small bundles per second. The design for this platform is based entirely on commercial-off-the-shelf (COTS) components, and possesses buffering capabilities in the 5 TB range. This document takes results from previous individual tests and integrates them to demonstrate results in the presence of a coherent use-case: consider a network aboard the ISS which intends to utilize an upcoming optical communications capability. For this use-case, orbital analysis software is used to analyze orbital dynamics, from which a list of access times are generated that might take in to account weather, schedule competition, etc. A variant of Contact Graph Routing (CGR) is applied to these windows to determine an optimal schedule. This schedule is then loaded into the HDTN prototype and, in conjunction with various measurement tools, a complete end-to-end analysis of HDTN's performance is conducted. Various bottlenecks (including storage) are identified: these bottlenecks are expected to help us focus our future work on the elements of the system that are most likely to present issues moving forward. Finally, we discuss possible paths for evolution beyond the present rates supported by the system, including (but not limited to) hardware acceleration.

Hylton, Alan

Required Filtering to Optimize Use of TOS

This presentation was originally given to ATD-2 industry partners at the Surface CDM (Collaborative Decision Making) Team (SCT) & Flow Evaluation Team (FET) meeting at NTX on 2/20/2020. The briefing presented lessons learned from Stormy 19, an overview of how terminal restrictions are handled by the ATD-2 system, and additional Trajectory Option Sets (TOS) route filtering capabilities planned for Stormy 20.

ATD-2

Integration of Advanced Concepts and Vehicles Into the Next Generation Air Transportation System: Introduction, Key Messages, and Vehicle Attributes - Volume 1

Raytheon, in partnership with NASA, is leading the way in ensuring that the future air transportation continues to be a key driver of economic growth and stability and that this system provides an environmentally friendly, safe, and effective means of moving people and goods. A Raytheon-led team of industry and academic experts, under NASA contract NNA08BA47C, looked at the potential issues and impact of introducing four new classes of advanced aircraft into the next generation air transportation system -- known as NextGen. The study will help determine where NASA should further invest in research to support the safe introduction of these new air vehicles. Small uncrewed or unmanned aerial systems (SUAS), super heavy transports (SHT) including hybrid wing body versions (HWB), very light jets (VLJ), and supersonic business jets (SSBJ) are the four classes of aircraft that we studied. Understanding each vehicle's business purpose and strategy is critical to assessing the feasibility of new aircraft operations and their impact on NextGen's architecture. The Raytheon team used scenarios created by aviation experts that depict vehicles in year 2025 operations along with scripts or use cases to understand the issues presented by these new types of vehicles. The information was then mapped into the Joint Planning and Development Office's (JPDO s) Enterprise Architecture to show how the vehicles will fit into NextGen's Concept of Operations. The team also identified significant changes to the JPDO's Integrated Work Plan (IWP) to optimize the NextGen vision for these vehicles. Using a proven enterprise architecture approach and the JPDO s Joint Planning Environment (JPE) web site helped make the leap from architecture to planning efficient, manageable and achievable. Very Light Jets flying into busy hub airports -- Supersonic Business Jets needing to climb and descend rapidly to achieve the necessary altitude Super-heavy cargo planes requiring the shortest common flight path -- are just a few of the potential new operations in the future National Airspace System. To assess the impact of these new scenarios on overall national airspace operations, the Raytheon team used the capabilities of a suite of tools such as NASA's Airspace Concepts Evaluation System (ACES), the Flight Optimization System (FLOPS), FAA's Aviation Environmental Design Tool (AEDT), Intelligent Automations Kinematic Trajectory Generator (KTG) and the Aviation Safety Risk Model (ASRM). Detailed metroplex modeling, surface delay models for super heavy transports, prioritized routing and corridors for supersonics business jets, and VLJ demand models are some of the models developed by the Raytheon team to study the effect of operating these new vehicles in the future NAS. Using this suite of models, several trade studies were conducted to evaluate these effects in terms of delays, equity in access, safety, and the environment. Looking at the impact of each vehicle, a number of critical issues were identified. The Raytheon team concluded that strict compliance to NextGen's 4-dimensional trajectory (4DT) management will be required to accommodate these vehicles unique operations and increased number of flights in the future air space system. The next section provides a discussion of this and the other key findings from our study.

Zellweger, Andres

Weasel works SA-150: Design study of a 100 to 150 passenger transport aircraft

As the year 2000 rapidly approaches, the airlines are faced with an extremely competitive and environmentally restrictive marketplace. In order to survive, commercial air carriers will need to find new ways to lower their direct operating costs, increase load factors and comply with tightening federal and international constraints. The SA-150 has been designed to meet these demands by focusing on the areas of aerodynamic efficiency, an improved level of passenger comfort, and a limited application of advanced technology. The SA-150 has been optimized for a 500 nmi. mission to help the airlines meet the challenges of the short haul, quick turnaround flight. With a maximum capacity of 124 passengers, and full baggage, the SA-150 is also capable of covering a range of 1500 nmi. This additional range capability will provide the airlines with flexibility when scheduling their routes. The aircraft features a 'V' tail, fly-by-wire system and is powered by two turbofans mounted under a twelve aspect ratio wing. The SA-150 will have an initial production run of 800 units and have a purchase price of $37.7 million in 1993 dollars.

Alkema, Kevin

New Horizons for a Practical and Performance-Optimized Solar System Internet

The High-rate Delay Tolerant Networking (HDTN) project at the NASA Glenn Research Center (GRC) is developing a performance-optimized Delay Tolerant Networking (DTN) implementation using the Bundle Protocol (BP) both for infusion in modern, distributed spacecraft systems and for foundational network research purposes. While one purpose of networking is to enable a returns-to-scale with communicating assets, it is recognized that neither the protocol nor its implementations may impose a bottleneck on data delivery if expected to be implemented. With this in mind, this paper explores the current status of the HDTN software, including its capabilities and also various performance metrics at the bundle layer, the convergence layers (e.g. performance-optimized Licklider Transmission Protocol, or LTP), and bundle storage and retrieval. This includes goals of software implementations that support multi-gigabit per second communications regardless of payload size. A discussion on the current software architecture and internal scheduling and routing is included. Interoperability with such extant DTN implementations as Interplanetary Overlay Network (ION) and DTN Marshall Enterprise Implementation (DTNME) are included. The research goals of the project are also listed, including Software-Defined Networking (SDN) and the theory of DTNs. A table-based filtration system for the Bundle Protocol (BP), called BP Filter, is also explored: this addition enables table-based policies within the context of a DTN for management purposes. Infusion begins with systems testing in the Johnson Space Center (JSC) Software Development and Integration Laboratory (SDIL), which supports International Space Station (ISS) Flight Software development, integration, and verification. Observations made from the results of testing in the SDIL and in flight testing are also discussed, pointing to a path for infusion into high data return low-earth orbit (LEO) missions. The paper concludes with areas for future work.

Delay Tolerant Networking

Demonstration of Prognostics-Enabled Decision Making Algorithms on a Hardware Mobile Robot Test Platform

Prognostics-enabled Decision Making (PDM) is an emerging research area that aims to integrate prognostic health information and knowledge about the future operating conditions into the process of selecting subsequent actions for the system. Previous work developing and testing PDM algorithms has been done in simulation; this paper describes the effort leading to a successful demonstration of PDM algorithms on a hardware mobile robot platform. The hardware platform, based on the K11 planetary rover prototype, was modified to allow injection of selected fault modes related to the rover’s electrical power subsystem. The PDM algorithms were adapted to the hardware platform, including development of a software module framework, a new route planner, and modifications to increase the algorithms’ robustness to sensor noise and system timing issues. A set of test scenarios was chosen to demonstrate the algorithms’ capabilities. The modifications to run with a hardware platform, the test scenarios, and the test results are described in detail. The results show a successful use of PDM algorithms on a hardware test platform to optimize mission planning in the presence of electrical system faults.

Prognosis

Common Methodology for Efficient Airspace Operations

Topics include: a) Developing a common methodology to model and avoid disturbances affecting airspace. b) Integrated contrails and emission models to a national level airspace simulation. c) Developed capability to visualize, evaluate technology and alternate operational concepts and provide inputs for policy-analysis tools to reduce the impact of aviation on the environment. d) Collaborating with Volpe Research Center, NOAA and DLR to leverage expertise and tools in aircraft emissions and weather/climate modeling. Airspace operations is a trade-off balancing safety, capacity, efficiency and environmental considerations. Ideal flight: Unimpeded wind optimal route with optimal climb and descent. Operations degraded due to reduction in airport and airspace capacity caused by inefficient procedures and disturbances.

Sridhar, Banavar

Gaussian Process for Flight Delay Prediction: Learning a Stochastic Process

This paper presents a machine-learning approach to predict flight delays. Whereas neural networks are extensively studied for predictive capabilities, they involve non-intuitive design and extensive analysis, particularly in training and optimization processes. Instead, the proposed framework employs Gaussian Processes as a supervised learning technique for flight delay prediction. This data-driven approach trains the model using prior information, specifically the mean and covariance tied to existing data. The proposed Gaussian Process Regression (GPR) model employs the day of flight as a pivotal feature for delay forecasting. We analyze flights from various routes and gauge the accuracy of the presented learning technique by comparing the predicted delays with the actual ones. Given the inherent challenges in precisely forecasting delays, we predict the delays with a 95 % confidence interval. Also, an error propagation analysis in the prediction horizon is carried out to determine the optimal time frame for prediction. The proposed method for flight delay prediction is important as airlines can strategize flight operations and issue timely advisories.

stochastic

Global Simulation of Aviation Operations

The simulation and analysis of global air traffic is limited due to a lack of simulation tools and the difficulty in accessing data sources. This paper provides a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASA's Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to present results on the evolution of global air traffic patterns from a concentration of traffic inside US, Europe and across the Atlantic Ocean to a more diverse traffic pattern across the globe with accelerated growth in Asia, Australia, Africa and South America. The simulation analyzes seasonal variation in the long-haul wind-optimal traffic patterns in six major regions of the world and provides potential time-savings of wind-optimal routes compared with either great circle routes or current flight-plans if available.

simulation

Workload Considerations in Urban Air Mobility

Urban air mobility (UAM) is receiving increased attention in aviation as a system for passenger and cargo-carrying new entrants in urban airspace. In order to develop a safe and efficient system, numerous possible concepts of operation for UAM are being explored throughout industry and research domains, the features and assumptions of which may differ according to near, medium and far term operations. Much of the current research into the development of UAM has dominantly focused on technological and engineering capabilities, such as vehicle development. Although these areas of research are essential to furthering UAM, research into the role of the human operator in UAM is limited. The research described in this paper aims to begin to address this gap by investigating the capabilities and implications of human operators as traffic managers in the UAM system, focusing on near-term UAM operations. A human in the loop air traffic control simulation was used to investigate the effect of UAM traffic density, airspace routes and communication procedures on subjective workload and efficiency-related task performance. Findings indicate that medium and high-density operations were associated with high workload. A reduction in verbal communications through a letter of agreement, and optimized routes, were associated with reduced workload and increased performance efficiency. However, even with these adjustments, reported workload remained high, particularly during the high-density scenario. Future research should focus on the human operator roles and responsibilities, and the amount of involvement, in UAM system management. Particular focus should be directed on the impact of reduced human operator involvement and increased automation, on the safety and efficiency of UAM operations and the integration of UAM with traditional air traffic management.

Edwards, Tamsyn

Thermostructural Properties Of Sic/Sic Panels With 2.5d And 3d Fiber Architectures

CMC hot-section components in advanced engines for power and propulsion will typically require high cracking strength, high ultimate strength and strain, high creep- rupture resistance, and high thermal conductivity in all directions. In the past, NASA has demonstrated fabrication of a variety of SiC/SiC flat panels and round tubes with various 2D fiber architectures using the high-modulus high-performance Sylramic-iBN Sic fiber and Sic-based matrices derived by CVI, MI, and/or PIP processes. The thermo- mechanical properties of these CMC have shown state-of-the-art performance, but primarily in the in-plane directions. Currently NASA is extending the thermostructural capability of these SiC/SiC systems in the thru-thickness direction by using various 2.5D and 3D fiber architectures. NASA is also using specially designed fabrication steps to optimize the properties of the BN-based interphase and Sic-based matrices. In this study, Sylramic-iBN/SiC panels with 2D plain weave, 2.5D satin weave, 2.5D ply-to-ply interlock weave, and 3D angle interlock fiber architectures, all woven at AITI, were fabricated using matrix densification routes previously established between NASA and GEPSC for CVI-MI processes and between NASA and Starfire-Systems for PIP processes. Introduction of the 2.5 D fiber architecture along with an improved matrix process was found to increase inter-laminar tensile strength from 1.5 -2 to 3 - 4 ksi and thru-thickness thermal conductivity from 15-20 to 30-35 BTU/ft.hr.F with minimal reduction in in-plane strength and creep-rupture properties. Such improvements should reduce thermal stresses and increase the thermostructural operating envelope for SiC/SiC engine components. These results are analyzed to offer general guidelines for selecting fiber architectures and constituent processes for high-performance SiC/SiC engine components.

Yun, H. M.

Application of fuel/time minimization techniques to route planning and trajectory optimization

Rising fuel costs combined with other economic pressures have resulted in industry requirements for more efficient air traffic control and airborne operations. NASA has responded with an on-going research program to investigate the requirements and benefits of using new airborne guidance and pilot procedures that are compatible with advanced air traffic control systems and that will result in more fuel efficient flight. The results of flight testing an airborne computer algorithm designed to provide either open-loop or closed-loop guidance for fuel efficient descents while satisfying time constraints imposed by the air traffic control system is summarized. Some of the potential cost and fuel savings that are obtained with sophisticated vertical path optimization capabilities are described.

Knox, C. E.

Design and simulation of a descent controller for strategic four-dimensional aircraft navigation

A time-controlled navigation system applicable to the descent phase of flight for airline transport aircraft was developed and simulated. The design incorporates the linear discrete-time sampled-data version of the linearized continuous-time system describing the aircraft's aerodynamics. Using optimal linear quadratic control techniques, an optimal deterministic control regulator which is implementable on an airborne computer is designed. The navigation controller assists the pilot in complying with assigned times of arrival along a four-dimensional flight path in the presence of wind disturbances. The strategic air traffic control concept is also described, followed by the design of a strategic control descent path. A strategy for determining possible times of arrival at specified waypoints along the descent path and for generating the corresponding route-time profiles that are within the performance capabilities of the aircraft is presented. Using a mathematical model of the Boeing 707-320B aircraft along with a Boeing 707 cockpit simulator interfaced with an Adage AGT-30 digital computer, a real-time simulation of the complete aircraft aerodynamics was achieved. The strategic four-dimensional navigation controller for longitudinal dynamics was tested on the nonlinear aircraft model in the presence of 15, 30, and 45 knot head-winds. The results indicate that the controller preserved the desired accuracy and precision of a time-controlled aircraft navigation system.

Lax, F. M.

Enhanced Multi-Modal Access to Planetary Exploration

Tomorrow's Interplanetary Network (IPN) will evolve from JPL's Deep-Space Network (DSN) and provide key capabilities to future investigators, such as simplified acquisition of higher-quality science at remote sites and enriched access to these sites. These capabilities could also be used to foster public interest, e.g., by making it possible for students to explore these environments personally, eventually perhaps interacting with a virtual world whose models could be populated by data obtained continuously from the IPN. Our paper looks at JPL's approach to making this evolution happen, starting from improved communications. Evolving space protocols (e.g., today's CCSDS proximity and file-transfer protocols) will provide the underpinning of such communications in the next decades, just as today's rich web was enabled by progress in Internet Protocols starting from the early 1970's (ARPAnet research). A key architectural thrust of this effort is to deploy persistent infrastructure incrementally, using a layered service model, where later higher-layer capabilities (such as adaptive science planning) are enabled by earlier lower-layer services (such as automated routing of object-based messages). In practice, there is also a mind shift needed from an engineering culture raised on point-to-point single-function communications (command uplink, telemetry downlink), to one in which assets are only indirectly accessed, via well-defined interfaces. We are aiming to foster a 'community of access' both among space assets and the humans who control them. This enables appropriate (perhaps eventually optimized) sharing of services and resources to the greater benefit of all participants. We envision such usage to be as automated in the future as using a cell phone is today - with all the steps in creating the real-time link being automated.

interplanetary network (IPN)

SatNet: A Benchmark for Satellite Scheduling Optimization

Satellites provide essential services such as networking and weather tracking, and the number of near-earth and deep space satellites are expected to grow rapidly in the coming years. Communications with terrestrial ground stations is one of the critical functionalities of any space mission. Satellite scheduling is a problem that has been scientifically investigated since the 1970s. A central aspect of this problem is the need to consider resource contention and satellite visibility constraints as they require line of sight. Due to the combinatorial nature of the problem, prior solutions such as linear programs and evolutionary algorithms require extensive compute capabilities to output a feasible schedule for each scenario. Machine learning based scheduling can provide an alternative solution by training a model with historical data and generating a schedule quickly with model inference. We present SatNet, a benchmark for satellite scheduling optimization based on historical data from the NASA Deep Space Network. We propose formulation of the satellite scheduling problem as a Markov Decision Process and use reinforcement learning (RL) policies to generate schedules. The nature of constraints imposed by SatNet differ from other combinatorial optimization problems such as vehicle routing studied in prior literature. Our initial results indicate that RL is an alternative optimization approach that can generate candidate solutions of comparable quality to existing state-of-the-practice results. However, we also find that RL policies overfit to the training dataset and do not generalize well to new data, thereby necessitating continued research on reusable and generalizable agents.

Wilson, Brian

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Momoh, James