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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

AutoTG: Reinforcement Learning-Based Symbolic Optimization for AI-Assisted Power Converter Design

Power converters are pervasive in modern electronic component design. They can be found in all electronic devices from household appliances and cellphone chargers to vehicles. Currently, designing new circuit topologies is hard because it requires human expertise based on experience and is difficult to automate. However, artificial-intelligence-assisted design can significantly facilitate the development of new power converters and/or improve the final result. Intelligently designed highly efficient power converters can have a significant effect on many important attributes, such as power efficiency, layout size, cost, heat dissemination, energy requirements, etc. We propose Autonomous Topology Generator (AutoTG), a reinforcement-learning-based framework that generates power converter topology candidates based on user specifications, optimized for user preferences. By modeling power converter design as a symbolic optimization problem, we sequentially sample components in an autoregressive manner until new topologies are formed, providing both the topology specification and the sizing (magnitude of each component parameter) of the proposed power converter. Here, we provide an empirical evaluation and show that AutoTG is able to generate varied high-efficiency topologies within component restrictions based on user input and show that previously unknown topologies can be found for further evaluation.

(AI)-based design↗

Power converter design optimization

Utilizing the demonstrated capability of nonlinear programming algorithms, a practical design optimization approach for power converters is established to conceive a design to meet all power-circuit performance requirements and concurrently optimize a defined quantity such as weight or losses. In addition, to facilitate a cost-effective design, the computer-aided approach provides a means to readily assess (1) the weight-efficiency tradeoff, (2) impacts of converter requirements and component characteristics on a given design, and (3) optimum power system configurations.

Yu, Y.↗

Power Converter Design for the Europa Lander Motor Controller

This paper will outline the design and test results for the Europa Lander motor controller’s Power Conversion Slice. Europa Lander is a proposed NASA mission concept to send a stationary spacecraft to Jupiter’s Icy Moon, Europa, to search for subsurface biosignatures. The Power Conversion Card is one of the many technologies designed for this mission. The Power Conversion Card’s primary function is to convert the power supplied by the spacecraft battery to usable power for use within the motor controller. In addition, this card provides power system telemetry to the spacecraft computer. This card tolerates Europa’s harsh radiation environment within a protected vault to enable it to survive the external temperatures which can be as low as -184°C during the three-week mission. This design makes use of multiple commercially available radiation hardened electronics, including Cobham’s UT32M0R500 Arm Microcontroller along with VPT’s DC-DC Converters for power conversion. The microcontroller is used to collect local power system telemetry and assess card health autonomously without intervention from the spacecraft’s main computer. This paper will showcase the design behind the prototype and electrical testing results.

Lias, Malcolm↗

Quantifying Dynamic On-State Resistance of GaN HEMTs for Power Converter Design via a Survey of Low and High Voltage Devices

Designing and optimizing high switching frequency, ultra-efficient converters requires detailed knowledge of the behavior and parasitic parameters for both active and passive components. Recently, wide bandgap transistors have enabled simultaneous increases in both switching frequency and efficiency due to higher maximum operating junction temperature limits, lower dc on-state resistances, and reduced parasitic inductances and capacitances. Yet, the early acceptance of gallium-nitride (GaN) switches was plagued by detrimental dynamic on-state resistance effects. This complex phenomenon for GaN devices is characterized by deviations in on-state resistance from dc operating characteristics based on design choices such as the magnitude and duration of both voltage and current stress, switching mode, and junction temperature. While device manufacturers have made improvements compared to early generation devices, experimental evidence from a survey of commercial GaN transistors highlight measurable change in on-state resistance still exists due to variations in voltage stress during hard-switching operation. After sharing insights for obtaining low noise measurements, an analysis method along with two metrics are proposed to characterize dynamic on-state resistance measurements for power electronics designers. Furthermore, quantifying the performance of GaN devices with standardized metrics facilitates a fair comparison between different GaN device technologies during converter development, enables manufacturing qualification for GaN switches, and provides a benchmark to catalyze improvement for the next generation of GaN device development.

14 SOLAR ENERGY↗

Multiple-Winding Output Inductors for Power Converters

Design procedure developed for dc-to-dc power converters with multiple outputs having inductors wound on common core. With common core, minimum load current consistent with good output regulation is lower, output regulation is improved, and total inductor size and weight is reduced.

Mclyman, W. T.↗

Power Converter Circuit Design Automation using Parallel Monte Carlo Tree Search

The tidal waves of modern electronic/electrical devices have led to increasing demands for ubiquitous application-specific power converters. A conventional manual design procedure of such power converters is computation- and labor-intensive, which involves selecting and connecting component devices, tuning component-wise parameters and control schemes, and iteratively evaluating and optimizing the design. To automate and speed up this design process, we propose an automatic framework that designs custom power converters from design specifications using Monte Carlo Tree Search. Specifically, the framework embraces the upper-confidence-bound-tree (UCT), a variant of Monte Carlo Tree Search, to automate topology space exploration with circuit design specification-encoded reward signals. Moreover, our UCT-based approach can exploit small offline data via the specially designed default policy and can run in parallel to accelerate topology space exploration. Further, it utilizes a hybrid circuit evaluation strategy to substantially reduce design evaluation costs. Empirically, we demonstrated that our framework could generate energy-efficient circuit topologies for various target voltage conversion ratios. Compared to existing automatic topology optimization strategies, the proposed method is much more computationally efficient --- the sequential version can generate topologies with the same quality while being up to 67% faster. Here, the parallelization schemes can further achieve high speedups compared to the sequential version.

24 POWER TRANSMISSION AND DISTRIBUTION↗

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗

ML-ACCEPT: Machine-Learning-enhanced Automated Circuit Configuration and Evaluation of Power Converters

This project, ML-ACCEPT, took a significant step toward achieving the first objective of the DIFFERENTIATE program: to help engineers to more rapidly and cost-effectively consider a wider range of more novel concepts before selecting an engineering-optimal architecture for high-fidelity detailed design and evaluation. Compared to existing methods, the ML-ACCEPT project investigated innovative technologies to make the design of power converters more cost-effective and time-efficient by i) integrating recent breakthroughs in ML, power electronics, simulation software, and optimization to research, develop, and developed a suite of ML-enhanced hypothesis generation tools for power converter design; and ii) facilitating the integration of the proposed software tools into existing power-converter design work-flows. Some existing tools for power-converter design have a certain level of intelligence to aid the design process, but to our knowledge none of them has ML-enhanced capability of automating the electrical circuit design process by selecting, configuring, and tailoring the individual components that enable available resources (e.g., high-voltage DC power) to be converted to the desired output (e.g., lower-voltage DC power with a desired voltage ripple), subject to application-specific (e.g., plasma generation and automotive applications) thermal and packaging considerations. The state-of-the-art circuit design of power converters is still heavily reliant on human experts to select the optimal topology and search for design parameters with human’s experience and intuitions, which can be very time-consuming, inefficient, and labor intensive. The team is composed of University of Michigan-Dearborn (UM-Dearborn), Lawrence Livermore National Laboratory (LLNL), Oak Ridge National Laboratory (ORNL), Modelon Inc., and lighthouse customers.

42 ENGINEERING↗

A 25-kW Series-Resonant Power Converter

Prototype exhibited efficiency of 93.9 percent. 25-kW resonant dc/dc power converter designed, developed, fabricated, and tested, using Westinghouse D7ST transistors as high-power switches. D7ST transistor characterized for use as switch in series-resonant converters, and refined base-drive circuit developed. Technical base includes advanced switching magnetic, and filter components, mathematical circuit models, control philosophies, and switch-drive strategies. Power-system benefits such as lower losses when used for high-voltage distribution, and reduced magnetics and filter mass realized.

Frye, R. J.↗

A new approach to the minimum weight/loss design of switching power converters

A new technique using the mathematical nonlinear programming ALAG is proposed to facilitate design optimizations of switching power converters. This computer-aided approach provides a minimum weight (or loss) design down to the details of component level and concurrently satisfies all related power-circuit performance requirements. It also provides such design insights as tradeoffs between power loss and system weight as the switching frequency is increased.

Lee, F. C.↗

Modeling and Feedback Compensator Design for Power-Hardware-in-the-Loop System for Medium-Voltage Grid-Connected Power Converters

Hardware-in-the-loop (HIL) evaluation is a method in which the test subject is split into a physical part and a simulated part, and these parts are connected with interfaces to form a combined physical-numerical system. Power-hardware-in-the-loop (PHIL) systems, where actual hardware is connected to a real-time model, can exhibit issues of instability, inaccuracy and errors when operating in a closed-loop. The challenges of generating a PHIL setup are that, first, because of the limited dynamic response of the different parts of the system, the test results might be inaccurate, and, second, because of the high frequency noise introduced by the sensors to the closed-loop system, it can be difficult to design a compensator for the real-time emulator response, while stabilizing the closed-loop system at the same time. In this paper, different parts of a PHIL system are characterized, and the feedback compensator system design is proposed for the stable operation of the closed-loop PHIL system. The issues as observed in a PHIL system without any compensator are demonstrated using experimental results, and the effectiveness of a first order phase lead compensator is validated.

compensator design↗

Low Temperature Operation of a Switching Power Converter

The low temperature operation of a 48 W, 50 kHz, 36/12 V pulse width modulated (PWM) buck de-de power converter designed with standard commercially available components and devices is reported. The efficiency of the converter increased from 85.6% at room temperature (300 K) to 92.0% at liquid nitrogen temperature (77 K). The variation of power MOSFET, diode rectifier, and output filter inductor loss with temperature is discussed. Relevant current, voltage. and power waveforms are also included.

Anglada-Sanchez, Carlos R.↗

Development of a dual-field heteropoplar power converter

The design and testing of a 400 watt, dual phase, dual rotor, field modulated inductor alternator is described. The system is designed for use as a flywheel to ac utility line or flywheel to dc bus (electric vehicle) power converter. The machine is unique in that it uses dual rotors and separately controlled fields to produce output current and voltage which are in phase with each other. Having the voltage and current in phase allows the power electronics to be made of simple low cost components. Based on analytical predictions and experimental results, development of a complete 22 kilowatt (30 Hp) power conversion system is recommended. This system would include power electronics and controls and would replace the inductor alternator with an improved electromagnetic conversion system.

Eisenhaure, D. B.↗

Power System for Venus Surface Exploration

A radioisotope power and cooling system is designed to provide electrical power for a probe operating on the surface of Venus. Most foreseeable electronics devices and sensors cannot operate at the 450 C ambient surface temperature of Venus. Because the mission duration is substantially long and the use of thermal mass to maintain an operable temperature range is likely impractical, some type of active refrigeration may be required to keep electronic components at a temperature below ambient. The fundamental cooling parameters are the cold sink temperature, the hot sink temperature, and the amount of heat to be removed. In this instance, it is anticipated that electronics would have a nominal operating temperature of 300 C. Due to the highly thermal convective nature of the high-density (90 bar CO2) atmosphere, the hot sink temperature was assumed to be 50 C, which provided a 500 C temperature of the cooler's heat rejecter to the ambient atmosphere. The majority of the heat load on the cooler is from the high temperature ambient surface environment on Venus, with a small contribution of heat generation from electronics and sensors. Both thermoelectric (RTG) and dynamic power conversion systems were analyzed, based on use of a standard isotope (General-purpose heat source, or GPHS) brick. For the radioisotope Stirling power converter configuration designed, the Sage model predicts a thermodynamic power output capacity of 478.1 watts, which slightly exceeds the required 469.1 watts. The hot sink temperature is 1200 C, and the cold sink temperature is 500 C. The required heat input is 1740 watts. This gives a thermodynamic efficiency of 27.48 %. It is estimated that the mechanical efficiency of the power converter design is on the order of 85 %, based on experimental measurements taken from 500-watt power class, laboratory-tested Stirling engines. The overall efficiency is calculated to be 23.36 %. The mass of the power converter is estimated at approximately 21.6 kg. Additional information is included in the original extended abstract.

Landis, Geoffrey A.↗

Venus Surface Power and Cooling System Design

A radioisotope power and cooling system is designed to provide electrical power for the a probe operating on the surface of Venus. Most foreseeable electronics devices and sensors simply cannot operate at the 450 C ambient surface temperature of Venus. Because the mission duration is substantially long and the use of thermal mass to maintain an operable temperature range is likely impractical, some type of active refrigeration may be required to keep certain components at a temperature below ambient. The fundamental cooling requirements are comprised of the cold sink temperature, the hot sink temperature, and the amount of heat to be removed. In this instance, it is anticipated that electronics would have a nominal operating temperature of 300 C. Due to the highly thermal convective nature of the high-density atmosphere, the hot sink temperature was assumed to be 50 C, which provided a 500 C temperature of the cooler's heat rejecter to the ambient atmosphere. The majority of the heat load on the cooler is from the high temperature ambient surface environment on Venus. Assuming 5 cm radial thickness of ceramic blanket insulation, the ambient heat load was estimated at approximately 77 watts. With an estimated quantity of 10 watts of heat generation from electronics and sensors, and to accommodate some level of uncertainty, the total heat load requirement was rounded up to an even 100 watts. For the radioisotope Stirling power converter configuration designed, the Sage model predicts a thermodynamic power output capacity of 478.1 watts, which slightly exceeds the required 469.1 watts. The hot sink temperature is 1200 C, and the cold sink temperature is 500 C. The required heat input is 1740 watts. This gives a thermodynamic efficiency of 27.48 %. The maximum theoretically obtainable efficiency is 47.52 %. It is estimated that the mechanical efficiency of the power converter design is on the order of 85 %, based on experimental measurements taken from 500 watt power class, laboratory-tested Stirling engines at GRC. The overall efficiency is calculated to be 23.36 %. The mass of the power converter is estimated at approximately 21.6 kg.

Landis, Geoffrey A.↗