Results for “electric powertrain”

NASA NTRSDate not supplied

Design and Development of an Aircraft Electric Powertrain Test Stand

Recent advancements in battery technology and power electronics are enabling novel approaches to powered flight that rely on fully electric or hybrid-electric powertrain systems. To mitigate the risk surrounding such unproven systems, it is necessary to characterize their performance on a component-wide and system-wide basis. In this paper, we discuss the design and development of an electric powertrain test stand that can collect high-fidelity data of motor, controller, and battery performance, thereby allowing us to determine system performance, efficiencies, and thermal characteristics.

test stand↗

NASA NTRSDate not supplied

Common Mode Current Challenges and Opportunities in Electric Powertrain Testing

During the development of novel electric powertrain (EP) components key parameters may be evaluated by test before a fully integrated EMI design is implemented. However, insufficiently mitigated EMI could impact the test equipment and test measurements. This risk is particularly valid with high voltage wide bandgap switching converters which enable high efficiency but can increase the EMI source function producing high levels of common mode (CM) current. Test facility equipment may be susceptible to the CM current from these converters causing test delays or measurement errors. Characterization of the common mode EMI of a powertrain component by analysis and/or measurement and assessment of the test facility EMC design can reduce this risk to yield efficient tests and successful measurements.

electromagnetic interference↗

NASA NTRSDate not supplied

Hybrid Modeling of Unmanned Aerial Vehicle Electric Powertrain for Fault Detection and Diagnostics

This paper shows the application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived principles and empirical equations, as well as fully connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. It has already been applied to Li-ion batteries in the past, and in this work, we extend the applications to other components of an electric powertrain, namely electronic speed controller with pulse-width modulation, and brushless DC motor with connected propeller. Training and testing of the model is carried out using experimental data from Li-ion battery discharge and powertrain testing in a laboratory environment.

Physics-Informed Machine Learning↗

NASA NTRS2026

AC and DC Fault Management for Megawatt Electrified Aircraft Electrical Powertrains Task 3: Lifetime and Reliability of Electrical Insulators

This research project was a collaborative investigation between researchers at the RTX Technology Research Center (RTRC) and the University of Texas at Austin and made a significant contribution to enabling electric aircraft. The transport of electric power between the points of generation and use requires power cables. These cables must be smaller, lighter and provide a more predictable life than power cables used in stationary applications. Consequently, this investigation provided heretofore unavailable information supporting the safety and reliability of smaller lighter power cables for electrified aircraft. In addition, the research identified key additional engineering data needed to support quantitative reliability assessments. Important advances included: • Demonstrated that at least one manufacturer can make a novel, smaller, lighter power cable that is free from serious defects. • Developed and published an appropriate analytical construct to describe the life of this novel cable. This is a necessary step for use in aviation where the understanding of remaining life is critical. • Demonstrated thermal-mechanical aging that suggested 1000+ flights before the thermal-mechanical processes produced defects large enough that the defect growth was accelerated electrically. • Showed that electrical aging took place at two rates. The first possibly lasting weeks to months and the second possibly days to weeks. If robust, this provides a good diagnostic for cable replacement. • Demonstrated that the traditional electrical testing of cable materials using manufactured voids can be misleading due to the size of the voids. Emerging laser drilling technology permitted demonstration that the physics of failure in realistically small voids is different from that in the unrealistically large voids used in earlier research, which is very important for high-quality, high-performance, small aircraft cables. Although this project represents a significant contribution to the specifics of cable aging in the aircraft environment, important additional research remains to be completed, including: • Non-uniform thermal cycling by applying the heat from the center conductor to maximize thermal stress next to the core area where the electric gradient is the strongest. This builds on the uniform thermal cycling that has been completed. • The augmentation of the thermal-mechanical failure rate by electrical processes. Better understanding of these time constants strongly affects the ability to predict life. • Termination design: Terminations provide not only electrical reflection potential, but a location for a series arc fault and an area where ozone can diffuse into the center conductor and negatively affect cable insulation. • The abrasion and ozone resistance of the cable jacket. • Pressure cycling as an accelerant of thermal, mechanical, and/or electrical aging. • Possible methods for online PD detection and offline PD localization

model↗

NASA NTRS2024

AC and DC Fault Management for Megawatt Electrified Aircraft Electrical Powertrains - Task 2: Power Quality Filtering Using Nanocrystalline Soft Magnetic Inductor

The NASA RTAPS program on AC and DC Fault Management for Megawatt Electrified Power Train is a multi-year joint project with Pratt & Whitney (P&W), Collins Aerospace (CA), and RTX Technology Research Center (RTRC). This research program focuses on the high-voltage distribution issues that present a significant technological obstacle in the adoption of Electrified Aviation Propulsion (EAP) systems. One challenge to the adoption of high-voltage distribution systems with power electronic converters is the need for filter elements to limit the generation and propagation of noise, protect the cable systems from premature aging and prevent against excessive heating within subcomponents due to high-frequency induced currents. While increased distribution voltages aide in reducing the cable mass for a fixed power system, the associated mass with the filtering elements for power electronic converter can grow with increasing distribution voltages – thereby mitigating any benefit associated with increasing the distribution system voltage. To enable high-voltage distribution systems with high system specific power densities, new magnetic materials must be developed. Therefore, the second task of the NASA RTAPS program is associated with the design and application of advanced soft magnetic components for Megawatt class electric propulsion systems, specifically the motor drive system. This report covers the collaborative work between NASA Glenn Research Center (GRC), RTRC, P&W and CA in the development of three types of magnetic components over the span of the three-year program. These critical magnetic components are the DC side EMI filter, which limits the propagation of harmful electromagnetic noise to the rise of the distribution system, and the AC side damping with the dv/dt filter, which limits the fast rise time of the power electronic converter output voltage to limit the degradation on the cable/motor insulation systems. Each of these components are investigated from component level design and are optimized at the system level with a combined modelling and testing effort. In the final experimental evaluation of the NASA developed soft magnetic material with a dv/dt filter, a commercial-off-the-shelf (COTS) magnetic core and the GRC magnetic core are optimized and loaded at 320Arms to evaluate their difference in performance. After a run time of 30 minutes in a MW-class motor driver at RTRC, the NASA GRC cores were found to not only offer a lower temperature rise of nearly 25°𝐶, but also a reduction in measured core loss of 25% (12.75W to 9.5W).

Elecrified Aircraft Propulsion↗

NASA NTRSDate not supplied

Controls for Electrified Aircraft Propulsion

Advanced electrified aircraft propulsion (EAP) concepts with integrated power, propulsion, and thermal systems require the development of equally sophisticated controllers to fly safe and efficient missions. Hybrid electric aircraft utilize electric machines mechanically coupled to the engine shafts to extract and insert power for a variety of purposes. Additionally, electric machines may drive propulsive fans pulling from a combination of on-board energy storage devices and engine extracted power. NASA’s investment in hybrid electric aircraft hardware-in-the-loop testing enables controls research on representative engine models using a novel emulation and scaling methodology. High-voltage, high-power electrical powertrain presents several technical risks at altitude. High-power requires high efficiency to minimize losses. Superconducting electric machines and power distribution research at NASA has identified key challenges with potential controls solutions. These risks necessitate the development of controllers robust to model uncertainty, disturbances, and fault conditions. System health management and fault detection schemes play an important role in a multi-layer controls approach that utilizes a supervisor which oversees inner loops for the highly coupled power, propulsion, and thermal systems. Such a supervisory controller enables coordinates energy transfer between engines, energy storage devices, electric machines, propulsors, and heat exchangers. Existing methods have shown an improvement in engine operability using the hybrid electric powertrain.

Halle E Buescher↗

NASA NTRSDate not supplied

Establishing Electrified Aircraft Propulsion Concepts—How AATT identified viable propulsion concepts and established foundational technologies

In the mid 2000’s NASA challenged the aeronautics industry to identify the routes for achieving ambitious improvements in fuel burn, emission, and noise reductions. These so-called “N+3” studies were exploring broad changes three commercial aircraft generations, or nominally 30 years, in the future. Many intriguing propulsion-airframe integrated solutions were proposed and pursued, which incorporated technologies such as high-aspect-ratio wings, boundary-layer ingestion, and hybrid-electric powertrains. When the Advanced Air Transport Technology (AATT) Project introduced “Technical Challenge 5.2-Establish viable concept for 5-10 MW hybrid gas-electric propulsion system for a commercial transport aircraft” in 2014, industry was very skeptical that electrified propulsion could make a significant impact in commercial air transport over the subsequent 30 years. Yet there were many practical reasons why improvements in electric power system and electric powertrains were advancing at a rapid rate and could lead to paradigm changes in aircraft propulsion. The challenge to the aeronautics community was to discover how to harness this power revolution and apply it to aircraft propulsion. This talk summarizes the approaches and achievements from the Hybrid Gas-Electric Propulsion Concept Technical Challenge that concluded in 2019. The balanced portfolio of concepts studies anchored with practical technology development demonstrated that electrified aircraft propulsion is an aircraft revolution whose time has come.

electric propulsion↗

NASA NTRSDate not supplied

Electrified Aircraft Propulsion Controls Hardware Testing

Electrified Aircraft Propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn and emissions. To realize this potential for single-aisle aircraft, control technology challenges associated with EAP designs are increasing the demand for Hardware-In-the-Loop (HIL) studies that address the tightly coupled electrical powertrain and turbofan propulsion systems. Reconfigurable HIL testbeds enable the study of integrated supervisory control and control approaches that augment engine shaft torques to improve performance. This paper presents an overview of conceptual EAP controls architecture testing in two HIL testbeds. The NASA Electric Aircraft Testbed provides the ability for megawatt class electric powertrain testing for technology maturation. A 100 kilowatt testbed, the Hybrid Propulsion Emulation Rig, allows for rapid controls technology trade studies. In both testbeds, controls testing is performed by implementing the electrical power system in hardware while turbomachinery is emulated via electric machines that are commanded by a real-time model and controls. A novel scaling algorithm is applied to emulate the inertial loads of the turbomachinery that causes the electric machines to respond in a fashion similar to that of the full-scale propulsion system they represent. Results demonstrate desired control performance at both testbed scales for the conceptual EAP architecture.

Electrified Aircraft Propulsion↗

NASA NTRSDate not supplied

Electrified Aircraft Propulsion Controls Hardware Testing

Electrified Aircraft Propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn and emissions. To realize this potential for single-aisle aircraft, control technology challenges associated with EAP designs are increasing the demand for Hardware-In-the-Loop (HIL) studies that address the tightly coupled electrical powertrain and turbofan propulsion systems. Reconfigurable HIL testbeds enable the study of integrated supervisory control and control approaches that augment engine shaft torques to improve performance. This paper presents an overview of conceptual EAP controls architecture testing in two HIL testbeds. The NASA Electric Aircraft Testbed provides the ability for megawatt class electric powertrain testing for technology maturation. A 100 kilowatt testbed, the Hybrid Propulsion Emulation Rig, allows for rapid controls technology trade studies. In both testbeds, controls testing is performed by implementing the electrical power system in hardware while turbomachinery is emulated via electric machines that are commanded by a real-time model and controls. A novel scaling algorithm is applied to emulate the inertial loads of the turbomachinery that causes the electric machines to respond in a fashion similar to that of the full-scale propulsion system they represent. Results demonstrate desired control performance at both testbed scales for the conceptual EAP architecture.

Electrified Aircraft Propulsion↗

NASA NTRS2018

Design and Performance of a Hybrid-Electric Fuel Cell Flight Demonstration Concept

As electric powertrain and propulsion-airframe integration technologies advance, airborne electric propulsion concepts appear to be on the cusp of disrupting or transforming aviation markets. One of the many challenges to this transformation lies within the onboard energy storage and generation technologies. State-of-the-art battery technology is heavy and lacks support infrastructure; purely combustion-based solutions to electrical power generation suffer from increased inefficiency as compared to a traditional combustion powertrain. This paper explores another alternative: a hybrid-electric, solid oxide fuel cell power system. This power system reforms traditional fuels to feed fuel cells that generate electrical power for the aircraft electric powertrain. A representative power system is designed based on the requirements for NASA’s X-57 Mod II electric flight demonstrator platform, and is shown to exceed system feasibility goals of 300 W/kg and 60% efficiency in at least one configuration. The hybrid-electric fuel cell power system is shown to be competitive with the range performance of a combustion-based power architecture and comparable in mission energy cost to a battery-electric power system.

Borer, Nicholas K.↗

NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗

NASA NTRS2013

SILHIL Replication of Electric Aircraft Powertrain Dynamics and Inner-Loop Control for V&V of System Health Management Routines

Software-in-the-loop and Hardware-in-the-loop testing of failure prognostics and decision making tools for aircraft systems will facilitate more comprehensive and cost-effective testing than what is practical to conduct with flight tests. A framework is described for the offline recreation of dynamic loads on simulated or physical aircraft powertrain components based on a real-time simulation of airframe dynamics running on a flight simulator, an inner-loop flight control policy executed by either an autopilot routine or a human pilot, and a supervisory fault management control policy. The creation of an offline framework for verifying and validating supervisory failure prognostics and decision making routines is described for the example of battery charge depletion failure scenarios onboard a prototype electric unmanned aerial vehicle.

Verification and Validation↗

NASA NTRS2017

Prognostics and Health Monitoring: Application to Electric Vehicles

As more and more autonomous electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of remaining useful life of the systemssubsystems, specifically the electrical powertrain. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle.Our research approach is to develop a system level health monitoring safety indicator either to the pilotautopilot for the electric vehicles which runs estimation and prediction algorithms to estimate remaining useful life of the vehicle e.g. determine state-of-charge in batteries. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Prognostics↗

NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

No abstract available

Kulkarni, Chetan↗

NASA NTRS2022

Specific Power and Efficiency Projections of Electric Machines and Circuit Protection Exploration for Aircraft Applications

The purpose of this paper is to generate specific power and efficiency projections through the year 2050 for electric machines for aircraft applications. A general literature review was performed to identify the types of electric machines that are commonly used and which types have the biggest potential for future aircraft applications due to their high specific power and efficiency. A database with historical data was built to include parameters such as weight [kg], rated power [kW], specific power [kW/kg], RPM, efficiency, year, motor cooling type, application type and motor type to allow for trend identification and accurate projections. Once the data was gathered, multiple curve fits on the historical data were generated and extrapolated to produce the projections for specific power according to conservative, nominal and aggressive projection scenarios. A different process was followed for the efficiency projections due to the scattered nature of the data. A state of the art (SoA) value for efficiency was identified through literature review and was used to create the conservative, nominal and aggressive projections for the time frames of 2030, 2040, and 2050. The efficiency and the specific power projections of EMs for 2050 are 0.989 and 50kW/kg respectively. This paper will also be examining circuit protection as it is an additional component of electric powertrains.

electric machines↗

NASA NTRSDate not supplied

System Health Management for a Series/Parallel Partial Hybrid Powertrain with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple interacting subsystems, making them much more complex than traditional aircraft propulsion systems in terms of integration and control. Electrification enables aircraft to have distributed thrust-producing fans that the flight control system can leverage for enhanced maneuverability, further increasing the control complexity. A NASA concept aircraft, the SUbsonic Single Aft eNgine (SUSAN) Electrofan, is such a vehicle. SUSAN is a series/parallel partial hybrid-electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed and implemented. This paper describes the development of some of these algorithms for system health management applied to the powertrain of the SUSAN concept aircraft.

Electrified Aircraft Propulsion↗

NASA NTRSDate not supplied

System Health Management for a Series/Parallel Partial Hybrid Powertrain with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple interacting subsystems, making them much more complex than traditional aircraft propulsion systems in terms of integration and control. Electrification enables aircraft to have distributed thrust-producing fans that the flight control system can leverage for enhanced maneuverability, further increasing the control complexity. A NASA concept aircraft, the SUbsonic Single Aft eNgine (SUSAN) Electrofan, is such a vehicle. SUSAN is a series/parallel partial hybrid-electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed and implemented. This paper describes the development of some of these algorithms for system health management applied to the powertrain of the SUSAN concept aircraft.

Electrified Aircraft Propulsion↗

NASA NTRS2024

System Health Management for a Series/Parallel Partial Hybrid Powertrain with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple interacting subsystems, making them much more complex than traditional aircraft propulsion systems in terms of integration and control. Electrification enables aircraft to have distributed thrust-producing fans that the flight control system can leverage for enhanced maneuverability, further increasing the control complexity. A NASA concept aircraft, the SUbsonic Single Aft eNgine (SUSAN) Electrofan, is such a vehicle. SUSAN is a series/parallel partial hybrid-electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed and implemented. This paper describes the development of some of these algorithms for system health management applied to the powertrain of the SUSAN concept aircraft.

Electrified Aircraft Propulsion↗