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NASA NTRS2024

Mission and Vehicle-Level Updates for the Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) Concept Aircraft

NASA created the PEGASUS concept with the goal of lowering mission energy (a surrogate for operating cost) compared to other regional aircraft by leveraging electrified aircraft propulsion (EAP). Since its inception, researchers have explored multiple facets of PEGASUS in varying fidelity but have not completed a rigorous, integrated design. The goal of this memorandum is to provide an updated design using recent studies and improved methods. This memorandum explores the initial vehicle concept and concept of operations, while considering ways to improve both the mission concept of operations and the integrated vehicle-level performance. Additionally, the design and analysis methodologies for EAP-enabled aircraft concepts are improved in several areas. This research incorporates new propulsion-airframe integration and wing weight surrogates to model the impacts of wingtip propulsors on the configuration. Detailed weight and balance calculations enable calculating dynamic stability and flight qualities within the conceptual design environment. Ultimately, the vehicle is optimized to reduce "well-to-wake" equivalent CO2, CO2e, rather than minimizing either fuel (or total energy) consumption or maximum takeoff weight. Using fuel/energy or takeoff weight leads to conflicting optima for hybrid-electric aircraft. Two aircraft are developed to provide points of comparison for PEGASUS: an advanced conventional turboprop vehicle and a hybrid-electric variant. The results show that the PEGASUS concept can reduce CO2e relative to the advanced turboprop or a hybrid-electric propulsion architecture, albeit with an increase in maximum takeoff weight. PEGASUS's maximum takeoff weight is 55% heavier than the advanced conventional turboprop but releases 18% less CO2e for a 400 nmi mission. Over the same mission, PEGASUS's maximum takeoff weight is 47% heavier than the comparator hybrid-electric vehicle but releases 12% less CO2e. This study shows that the PEGASUS configuration reduces CO2e through its use of wingtip propulsors and that its benefit is not solely a result of switching to a hybrid-electric propulsion architecture. PEGASUS achieves this reduction in CO2e while maintaining satisfactory Level 1 or 2 flight qualities for all of its longitudinal- and lateral-directional modes.

Hybrid-electric↗

NASA NTRSDate not supplied

Key Performance Parameters for an Operational CIS-Lunar NTP Vehicle

Nuclear Thermal Propulsion (NTP) is in active development by NASA and DARPA. This paper presents an investigation into the effects of different values of key performance parameters (KPPs) of an NTP engine in the context of payload delivery missions between Earth and Lunar orbits. The high Isp afforded by NTP combined with the relatively large engine mass is best applied to missions where the payload mass is large and required ΔV high. Two missions considered are the round-trip Earth to Moon tug and a NRHO to low Lunar orbit tug. Chemical propulsion vehicles can generally achieve higher propellant mass fractions, similar payload mass and similar ΔV performance on these missions. When re-use of the vehicle is considered, the reduced propellant mass required by an NTP vehicle begins to add up over multiple refilling launches and trades more favorably. Analysis illustrates the impact of variation in NTP engine performance values, especially Isp, engine mass and thrust, on performance and the comparison to chemical propulsion. NTP transient and cooldown effects on the vehicle performance are examined. A variety of launch vehicles and hydrogen and ammonia NTP propellants are included in the analyses, and cryogenic fluid management system effects are accounted for.

NTP↗

NASA NTRSDate not supplied

Acoustic Measurements for the Moog S-250 Vehicle in Hover

Acoustic measurements for hover conditions and electric motor noise tests were conducted for the Moog S-250 research aircraft, an RPM-controlled quadcopter-type Urban Air Mobility (UAM) vehicle with four sets of contra-rotating rotors. The objectives of the study included determining the minimum far-field distance, the noise characteristics, and the potential for electric motor noise to contribute to the overall acoustic radiation for the full-scale UAM vehicle. Acoustic data for full-scale aircraft are critical for determining the impact of these vehicles on the surrounding communities. The results showed the far-field was reached by 8.1 single rotor diameters or 2.7 vehicle diameters as defined by the longest tip-to-tip rotor dimension for the vehicle. In hover, the peak acoustic radiation occurred at a declination angle of roughly 29° below the midplane between the upper and lower rotors. The lowest acoustic levels occurred below the aircraft. The electric motor noise studies, conducted with the rotors removed, showed motor noise radiated at shaft orders 17 – 20, whereas rotor noise covered the range of 2 – 24 shaft orders. There was some evidence that electric motor noise was present in previous ground run-up measurements.

Urban Air Mobility Noise↗

NASA NTRSDate not supplied

Aircraft Design Implications for Urban Air Mobility Vehicles Performing Public Good Missions

NASA has previously designed and described set of concept aircraft to serve as reference vehicles for Urban Air Mobility (UAM), to encourage public discussion and research. These vehicles are used in this paper to quantify how suitable UAM aircraft might be for missions other than their primary commercial design missions. A set of representative public good missions are described, along with design requirements and equipage. For two of these missions, the additional weight, power, and cost to facilitate a basic vehicle which may be built or configured with the ability to perform these missions is quantified. Special layout and other considerations which may impact vehicle design are described. For aircraft designed to the NASA UAM reference mission, the addition of some meaningful public good missions causes less than 10% growth in weight and power for fossil-fueled aircraft; advanced batteryelectric powered aircraft grow by a significantly larger amount and may only be possible with relaxed requirements. Meaningful public good missions with UAM vehicles are feasible, provided that public good mission requirements are considered and incorporated in the conceptual design stage of development.

Aircraft↗

NASA NTRSDate not supplied

Command and Control Concepts for an Lift Plus Cruise Electric Vertical Takeoff and Landing Vehicle

Electric Vertical Takeoff and Landing (eVTOL) vehicles have the potential to enable cost effective Urban Air Mobility (UAM) applications. Many of these vehicle concepts will takeoff vertically like a helicopter, transition to fly like an airplane, and then transition back to land vertically like a helicopter. However, these concepts may also pose several challenging handling and control problems, which must be addressed prior to safe and reliable urban operations. This study investigates some of these challenges by evaluating different command and control concepts for a conceptual Lift Plus Cruise vehicle designed by NASA’s Revolutionary Vertical Lift Technology (RVLT) project. Four different command concepts with increasing levels of automation are developed. The command and control architecture for these concepts is presented along with findings from the evaluation of these concepts in a series of three piloted studies in the Vertical Motion Simulator at NASA Ames Research Center, where pilots flew operationally relevant flight test maneuvers specifically designed to expose potential deficiencies. The higher-level control systems and the associated pilot interfaces were shown to improve performance and handling in many cases, especially for higher precision and lower to moderate aggression maneuvers. The benefits were limited for higher aggression tasks in environmentally stressing conditions, due to the slower response of the automation and inherent limitations of the vehicle design, which highlights the potential need for tradeoffs between concept of operations and vehicle capabilities

Thomas Lombaerts↗

NASA NTRSDate not supplied

HIRF Tolerance and Avoidance for Advanced Air Mobility Vehicles

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles may fly in similar airspace to Transport Category Rotorcraft, thereby requiring meeting the same stringent High-Intensity Radiated Fields (HIRF) certification requirements. In a previous effort, a proposed map-based approach protects a vehicle by keeping it away from high power sources at safe distances based on its tolerance level. By designing to a lower tolerance level, significant cost savings can be achieved at the cost of slightly more complex flight planning. However, too low a threshold can result in large avoidance areas, potentially reducing the vehicle operating space. This current effort suggests a minimum threshold for vehicles operating in an urban area. It is derived from analyzing regulatory transmitter data for New York City as a representative metropolitan. As a result, a vehicle can tolerate common lower-power transmitters by default and only needs to avoid far less common high-power sources. It is also found the existing HIRF requirements may be insufficient against many powerful transmitters such as weather radars and satellite uplink transmitters, and that the map-based approach can address this concern.

HIRF↗

NASA NTRSDate not supplied

HIRF Tolerance and Avoidance for Advanced Air Mobility Vehicles

Advanced Air Mobility (AAM), including Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles may fly in similar airspace to Transport Category Rotorcraft, thereby requiring meeting the same stringent High-Intensity Radiated Fields (HIRF) certification requirements. In a previous effort, a proposed map-based approach protects a vehicle by keeping it away from high power sources at safe distances based on its tolerance level. By designing to a lower tolerance level, significant cost savings can be achieved at the cost of slightly more complex flight planning. However, too low a threshold can result in large avoidance areas, potentially reducing the vehicle operating space. This current effort suggests a minimum threshold for vehicles operating in an urban area. It is derived from analyzing regulatory transmitter data for New York City as a representative metropolitan area. As a result, a vehicle can tolerate common lower-power transmitters by default and only needs to avoid far less common high-power sources. It is also found the existing HIRF requirements may be insufficient against many powerful transmitters such as weather radars and satellite uplink transmitters, and that the map-based approach can address this concern.

HIRF↗

DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2020

My vehicle is a data mine

In this talk we explore how analysis of vehicle data provides information of individual vehicle behaviors, information of other vehicles in the flow of traffic, and insights into the behavior of drivers. Over the last two decades traditional passenger vehicles have been transformed from integrated two-port electrical nodes to cyber-physical systems of communicating computational nodes whose individual state and control variables are shared on a standard controller area network (CAN) bus. As driver assistance systems have crept into vehicles as safety features, driver behaviors can be observed through analysis of the data streams on the CAN bus as these new nodes communicate with one another. The properties of these data streams, as well as architectures and approaches to gather the data, are important to consider when drawing conclusions on the relevance of the data in making decisions at varying levels of the information hierarchy. We will demonstrate several technical challenges associated with these data collection processes, as well as preliminary results that demonstrate application relevance of the data to behavior, traffic, and systems domains.

42 ENGINEERING↗

DOE OSTI2021

Space vehicle with customizable payload and docking station

A “black box” space vehicle solution may allow a payload developer to define the mission space and provide mission hardware within a predetermined volume and with predetermined connectivity. Components such as the power module, radios and boards, attitude determination and control system (ADCS), command and data handling (C&DH), etc. may all be provided as part of a “stock” (i.e., core) space vehicle. The payload provided by the payload developer may be plugged into the space vehicle payload section, tested, and launched without custom development of core space vehicle components by the payload developer. A docking station may facilitate convenient development and testing of the space vehicle while reducing handling thereof.

Judd, Stephen↗

DOE OSTI2021

Configurable vehicle seat and method therefor

A conformal seat insert for an adjustable vehicle seat, the conformal seat insert comprising an insert frame, the insert frame having one or more insert reference features for locating the insert frame on a seat frame of the vehicle seat in a predetermined position relative to the seat frame, and a contoured support surface formed in the insert frame, the contoured support surface having a crew reference point corresponding to an acromial point of a shoulder of a seat occupant of the adjustable vehicle seat, the crew reference point being a datum from which an eye position of the seat occupant is established relative to instrumentation of an aerospace vehicle in which the adjustable vehicle seat is located.

McCarley, Michael C.↗

DOE OSTI2021

Space vehicle system and payload interposer (PIP) board

A payload interposer (PIP) board provides an interface for hosting payloads on a space vehicle platform. Payload development may be performed via the PIP board in a manner that “abstracts” the hardware of the space vehicle from the payload developer. The PIP board may include a host side payload interface connector that connects to a space vehicle and a payload side payload interface connector that connects to a payload. Power, CDH, and other space vehicle functionality may thus be provided to the payload from the space vehicle via the PIP board.

Proicou, Michael↗

DOE OSTI2021

Human-automated vehicle interactions

This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.

Guo, Longxiang↗

DOE OSTI2021

HUMAN-AUTOMATED VEHICLE INTERACTIONS

Guo, Longxiang↗

DOE OSTI2023

Apparatus and system for controlling power to an air conditioning compressor for a vehicle

A climate control system for vehicles includes an internal combustion engine that may be coupled to selectively power a first motor generator, and an air conditioning compressor that may be selectively powered by one or both of the first motor generator and a second motor generator, or by the internal combustion engine. The system may include a rechargeable battery, and a vehicle controller having a vehicle state circuit structured to determine a vehicle operating condition value and a state-of-charge value of the rechargeable battery, and a coupling determination circuit structured to provide an internal combustion engine-first motor generator coupling command in response to the vehicle operating condition value and the state-of-charge value. In response to the internal combustion engine-first motor generator coupling command being provided as coupled, the internal combustion engine may power the first motor generator.

Kumar, Mahesh Madurai↗

DOE OSTI2024

"Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs"

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,"are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment leveraged a heterogeneous fleet of 100 longitudinally-controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this paper. The MegaController is a hierarchical control architecture, which consists of two main layers. The upper layer is called Speed Planner, and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock on-board sensors. The Speed Planner ingests live data feeds provided by third parties, as well as data from our own control vehicles, and uses both to perform the speed assignment. The architecture of the speed planner allows for modular use of standard control techniques, such as optimal control, model predictive control, kernel methods and others, including Deep RL, model predictive control and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers, or only some. Control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars, and electronic selection of ACC set points in others. The proposed architecture allows for the combination of all possible settings proposed above. Most configurations were tested throughout the ramp up to the MegaVandertest.

Lee, Jonathan↗

DOE OSTI2023

"Reducing Detailed Vehicle Energy Dynamics to Physics-Like Models"

The energy demand of vehicles, particularly in unsteady drive cycles, is affected by complex dynamics internal to the engine and other powertrain components. Yet, in many applications, particularly macroscopic traffic flow modeling and optimization, structurally simple approximations to the complex vehicle dynamics are needed that nevertheless reproduce the correct effective energy behavior. This work presents a systematic model reduction pipeline that starts from complex vehicle models based on the Autonomie software and derives a hierarchy of simplified models that are fast to evaluate, easy to disseminate in open-source frameworks, and compatible with optimization frameworks. The pipeline, based on a virtual chassis dynamometer and subsequent approximation strategies, is reproducible and is applied to six different vehicle classes to produce concrete explicit energy models that represent an average vehicle in each class and leverage the accuracy and validation work of the Autonomie software.

Khoudari, Nour↗

DOE OSTI2020

SMART Mobility. Connected and Automated Vehicles Capstone Report

The U.S. Department of Energy’s Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium is a multiyear, multi-laboratory collaborative, managed by the Energy Efficient Mobility Systems Program of the Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, dedicated to further understanding the energy implications and opportunities of advanced mobility technologies and services. The first three-year research phase of SMART Mobility occurred from 2017 through 2019 and included five research pillars: Connected and Automated Vehicles, Mobility Decision Science, Multi-Modal Freight, Urban Science, and Advanced Fueling Infrastructure. A sixth research thrust integrated aspects of all five pillars to develop a SMART Mobility Modeling Workflow to evaluate new transportation technologies and services at scale. This report summarizes the work of the Connected and Automated Vehicles (CAVs) Pillar. This Pillar investigated the energy, technology, and usage implications of vehicle connectivity and automation and identified efficient CAV solutions. For information about the other Pillars and about the SMART Mobility Modeling Workflow, please refer to the relevant Pillar’s Capstone Report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗