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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

NO 2 -mediated voloxidation for iodine separation from cesium iodide surrogates

Heterogeneous NO 2 -mediated oxidation of uranium, also known as advanced voloxidation, is a proposed head-end reprocessing method for used nuclear fuel. An advantage of advanced voloxidation is the removal of volatile fission products, which complicate downstream separation and containment challenges leading to increased processing economics. Iodine, one of the volatile species of interest, has exhibited varied results in this process. Using CsI as a surrogate material, this work mimics the effect of NO 2 -based voloxidation on iodine and sheds light on the factors that influence the solid–gas phase reaction. Solid-state analysis using Fourier transform infrared attenuated total reflectance spectroscopy and scanning electron microscopy with energy-dispersive X-ray spectroscopy confirmed the conversion of CsI to CsNO 3 . Iodine separation ranged from 46% to 100% across multiple tests. Iodine separation was most effective when multiple recharges of NO 2 were administered. In conclusion, at the bench scale, liberating iodine from CsI appears to occur within 1 h, but the presence of surface H 2 O and the composition of the NO x reagent mixtures greatly influence its success.

advanced voloxidation↗
DOE OSTI2024

A novel diamond-like carbon based photocathode for PICOSEC Micromegas detectors

The PICOSEC Micromegas (MM) detector is a precise timinggaseous detector based on a MM detector operating in a two-stageamplification mode and a Cherenkov radiator. Prototypes equippedwith cesium iodide (CsI) photocathodes have shown promising timeresolutions as precise as 24 picoseconds (ps) for Minimum IonizingParticles. However, due to the high hygroscopicity andsusceptibility to ion bombardment of the CsI photocathodes,alternative photocathode materials are needed to improve therobustness of PICOSEC MM. Diamond-like Carbon (DLC) film have beenintroduced as a novel robust photocathode material, which have shownpromising results. A batch of DLC photocathodes with differentthicknesses were produced and evaluated using ultraviolet light. Thequantum efficiency measurements indicate that the optimizedthickness of the DLC photocathode is approximately3 nm. Furthermore, DLC photocathodes show good resistance to ionbombardment in aging test compared to the CsI photocathode. Finally,a PICOSEC MM prototype equipped with DLC photocathodes was tested inmuon beams. A time resolution of around 42 ps with a detectionefficiency of 97% for 150 GeV/c muons were obtained. These resultsindicate the great potential of DLC as a photocathode for thePICOSEC MM detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Silicon Photomultipliers Coupled to Scintillators With the Emission Maximum at 550 nm

A majority of the silicon photomultipliers (SiPMs) are sensitive to blue and near-ultraviolet (NUV) photons that are not optimized for scintillators with the emission maximum at wavelengths longer than 500 nm. The red–green–blue (RGB) SiPM is developed for the maximum photon detection efficiency (PDE) at 550 nm, which is a good match for some high-light-yield scintillators, such as CsI:Tl (CsI) and Gd 1.5 Y 1.5 Ga 2 Al 3 O 12 :Ce (GYGAG). Comparisons are made for the performance of these scintillators coupled to the RGB SiPM and a blue-sensitive SiPM. Because it takes tens of nanoseconds for the microcells to recharge after registering a photon hit, the linearity of these scintillation detectors was studied for high-energy gammas where numerous scintillation photons are generated. In addition, the energy resolution of the 662-keV gamma emitted by 137 Cs was measured for temperatures between –20 °C and 50 °C. The nonlinearity was observed above 1 MeV for all measurements, and however, it can be corrected by energy calibration using a third-degree polynomial. For CsI, the energy resolution is better with the blue-sensitive SiPM because of the lower dark count rate (DCR). In contrast, GYGAG coupled to the RGB SiPM has a better energy resolution for temperatures below 30 °C because of the well-matched emission spectrum and PDE distribution. Nevertheless, the advantage disappears for temperatures above 30 °C due to the higher DCR. It would be useful to further develop the RGB SiPM with a lower DCR and higher operating temperatures.

42 ENGINEERING↗
DOE OSTI2023

Design of a Cryogenic Scintillation Neutrino Detector at the Spallation Neutron Source

We successfully verified in the following three aspects the feasibility of using a cryogenic scintillating crystal-based neutrino detector at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory, for the detection of low-mass dark matter particles and non-standard neutrino interactions (NSIs), as part of the detector R&D effort of the COHERENT experiment. First, we demonstrated the possibility of using silicon photomultipliers (SiPMs) at cryogenic temperatures to replace traditional photomultiplier tubes (PMTs) as light sensors. Second, we verified that the high light yield of undoped CsI crystals measured above 13 keVee at 77 K still holds down to 5.9 keVee. Third, we successfully measured nuclear quenching factor of undoped cryogenic CsI at the Triangle Universities Nuclear Laboratory with the help from our Duke collaborators. The first achievement resulted in a publication in European Physics Journal C. The second resulted in an arXiv pre-print, which is under journal review. The last one indicates that the performance of the proposed detector may be better than what was assumed in the literature. The analysis is in the final stage and will result in another journal publication. In addition, two graduate students involved in this project graduated with master’s degrees during the project period. Both decided to continue their research as PhD students. One open-source data analysis code package was created and is publicly available on GitHub. A set of tutorials about Monte Carlo simulation of radiation interacting with detectors were created on YouTube, receiving more than 100,000 views.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Mechanisms of mechanochemical synthesis of cesium lead halides: pathways toward stabilization of α-CsPbI 3

Cesium lead iodide with cubic perovskite structure (α-CsPbI 3 ) is gaining significant interest in photovoltaic applications due to its excellent absorbance of the visible solar light and other attractive optoelectronic properties. However, the synthesis of stable α-CsPbI 3 poses a significant challenge. Mechanochemical synthesis is emerging as a suitable method for the preparation of cesium lead halides. This work investigates the ball milling-induced synthesis of cesium lead halides perovskite phase using halide mixing or doping approaches. The synthesis in the CsI + PbI 2 , CsBr + PbBr 2 , CsBr + PbI 2 , and CsI + PbI 2 + NdI 3 mixtures and halide exchange reactions in the CsPbBr 3 + 3KI and CsBr + PbBr 2 + 3KI systems are investigated to elucidate the mechanism of this process. Then, CsPb(I 1–x Br x ) 3 and CsPb( 1–y )Nd y I 3 materials with different x and y ratios are prepared, and their stability is probed in the air using light absorption spectroscopy. These results suggest that Nd doping is more efficient in the stabilization of the perovskite structure than partial replacement of iodine with bromine. Microstructure observations reveal the existence of two different product formation mechanisms depending on the mechanical properties of reactants. The results reveal that the milling temperature has a significant impact on the reaction kinetics. Here, the produced particles nucleate and grow at the reactant interface and retard the synthesis reaction by creating a diffusion barrier. Extended milling reduces the product particle size and creates fresh contact between reactants, thus facilitating reaction completion.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Towards robust PICOSEC Micromegas precise timing detectors

The PICOSEC Micromegas (MM) detector is a precise timing gaseous detector consisting of a Cherenkov radiator combined with a photocathode and a MM amplifying structure. A 100-channel PICOSEC MM prototype with 10 × 10 cm 2 active area equipped with a Cesium Iodide (CsI) photocathode demonstrated a time resolution below σ = 18 ps. The objective of this work is to improve the PICOSEC MM detector robustness aspects, i.e. integration of resistive MM and carbon-based photocathodes, while maintaining good time resolution. The PICOSEC MM prototypes have been tested in laboratory conditions and successfully characterised with 150 GeV/c muon beams at the CERN SPS H4 beam line. The excellent timing performance below σ = 20 ps for an individual pad obtained with the 10 × 10 cm 2 area resistive PICOSEC MM of 20 MΩ/$\square$ showed no significant time resolution degradation as a result of adding a resistive layer. A single-pad prototype equipped with a 12 nm thick Boron Carbide (B 4 C) photocathode presented a time resolution below σ = 35 ps, opening up new possibilities for detectors with robust photocathodes. The results made the concept more suitable for the experiments in need of robust detectors with good time resolution.

RETHGEM↗
DOE OSTI2025

Direct dark matter searches with metal halide perovskites

Polar materials with optical phonons in the meV range are excellent candidates for both dark matter direct detection via dark photon-mediated scattering and light dark matter absorption. In this study, we propose, for the first time, the metal halide perovskites MAPbI 3 , MAPbCl 3 , and CsPbI 3 for these purposes. Our findings reveal that CsPbI 3 is the best material, significantly improving exclusion limits compared to other polar materials. For scattering, CsPbI 3 can probe dark matter masses down to the keV range. For absorption, it enhances sensitivity to detect dark photon masses below ∼10 meV. The only material that has so far been investigated and that could provide competitive bounds is CsI, which, however, demonstrates lower stability as device platform compared to CsPbI 3 . Moreover, CsI is isotropic while the anisotropic structure of CsPbI 3 enables daily modulation analysis, showing that a significant percentage of daily modulation exceeding 1% is achievable for dark matter masses below 40 keV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Covariance Shaping Over Riemannian Manifolds for Massive MIMO Communication

Acquiring accurate instantaneous channel state information (CSI) is a challenging aspect of massive multi-input multi-output (MIMO) communication. Utilizing statistical information, such as channel covariance matrix, to design statistical beamforming vectors is robust when compared to instantaneous CSI. In this paper, we propose a novel MIMO covariance shaping scheme over Riemannian manifolds. It serves as an effective statistical beamforming solution to a number of close proximity user equipment (UE) that are undergoing substantial channel correlation. Proposed algorithm exploits the Hermitian positive definite nature of covariance matrices lying over Riemannian manifold. We introduce Wasserstein distance function as a Riemannian metric to measure distances between channel covariance matrices. Furthermore, K-means clustering technique is utilized to effectively identify the optimal shape of effective optimal covariance matrices. Our findings suggest that maximizing the geodesic distance between covariance matrices ultimately leads to a corresponding increase in the network throughput, as determined by the beamforming vector used to shape the covariance matrices. Simulation results validate that the proposed solution converges faster than Euclidean-based state-of-the-art, while maintaining the same computational complexity. Finally, the sum rate performance asymptotically achieves full capacity for two-UE case and more than 96% of the upper bound exhaustive search benchmark for multi-UE scenario.

42 ENGINEERING↗
DOE OSTI2022

A High-Accuracy Power Loss Model of SiC MOSFETs in Current Source Inverter Considering Current Commutation and Parasitic Parameters

Power loss estimation of power electronic devices is important to the efficiency optimization of motor drives used in many applications. However, most existing simplified power loss models of silicon carbide (SiC) MOSFETs are not sufficiently accurate due to their neglect of parasitic parameters in the current commutation loop. In addition, the loss model of the voltage source inverter (VSI) cannot be directly applied to the current source inverter (CSI) because of differences between their commutation loops. First, the commutation processes for VSIs and CSIs are compared. The voltage and current trajectories of SiC MOSFETs in the switching transition of a CSI-based motor drive system are analyzed in detail. Based on these results, the conduction and switching losses of SiC MOSFETs in CSIs are modeled considering the current commutation details. In addition, the proposed analytical model includes parasitic inductances and capacitances in the current commutation loop. Experimental results have verified that the proposed power loss model delivers higher accuracy loss predictions than the conventional loss model.

current commutation, current source inverter, powe↗
DOE OSTI2022

Thermal Stress Reduction in Power Switching Devices Using Distributed Loss PWM Concept for Current Source Inverters

A new modulation scheme is proposed for current source inverters (CSIs) that reduces the variation and peak junction temperature in the CSIs' power devices. The distributed loss pulse-width modulation (DLM) concept is introduced and applied to traditional space vector modulation methods to develop modified modulation schemes that reduce the thermal stress on power devices. The device junction temperatures resulting from conventional and DLM schemes are compared. Simulation and experimental results confirm that the proposed DLM concept reduces thermal stress on the devices while maintaining the same high output current waveform quality compared to traditional CSI modulation schemes. The CSI power device lifetime (i.e., the number of cycles to failure) are estimated using the simulation and experimental results. The proposed DLM significantly increases the device lifetime (by 5 to 6 times) by reducing the junction temperature variation compared to the conventional modulations.

42 ENGINEERING↗
DOE OSTI2024

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improved Diagnosis of Precipitation Type with LightGBM Machine Learning

Abstract Existing precipitation-type algorithms have difficulty discerning the occurrence of freezing rain and ice pellets. These inherent biases are not only problematic in operational forecasting but also complicate the development of model-based precipitation-type climatologies. To address these issues, this paper introduces a novel light gradient-boosting machine (LightGBM)-based machine learning precipitation-type algorithm that utilizes reanalysis and surface observations. By comparing it with the Bourgouin precipitation-type algorithm as a baseline, we demonstrate that our algorithm improves the critical success index (CSI) for all examined precipitation types. Moreover, when compared with the precipitation-type diagnosis in reanalysis, our algorithm exhibits increased F1 scores for snow, freezing rain, and ice pellets. Subsequently, we utilize the algorithm to compute a freezing-rain climatology over the eastern United States. The resulting climatology pattern aligns well with observations; however, a significant mean bias is observed. We interpret this bias to be influenced by both the algorithm itself and assumptions regarding precipitation processes, which include biases associated with freezing drizzle, precipitation occurrence, and regional synoptic weather patterns. To mitigate the overall bias, we propose increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 , as it better reflects the precision of precipitation observations. This adjustment yields a substantial reduction in the overall bias. Finally, given the strong performance of LightGBM in predicting mixed precipitation episodes, we anticipate that the algorithm can be effectively utilized in operational settings and for diagnosing precipitation types in climate model outputs. Significance Statement Freezing rain can have significant impacts on transportation and infrastructure, making accurate prediction of precipitation types crucial. In this study, we use a machine learning method known as LightGBM to predict precipitation types. We show that the new algorithm performs better than the existing methods for all precipitation types examined. Additionally, we compute a freezing-rain climatology over the eastern United States. Although the resulting climatology pattern corresponds well to observations, the algorithm overpredicts freezing-rain occurrence. We argue that this bias can be substantially reduced by increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 . Overall, this work highlights the potential of the LightGBM algorithm for both weather forecasting and diagnosing precipitation types in climate models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

The Beam Dump eXperiment

Hadronic matter makes about 14% of the known universe. The remaining 86% is Dark Matter (DM). Since it does not interact with the ordinary matter via electromagnetic force, DM is not visible and, to date, it escaped detection. The search for Dark Matter (DM) is one of the hottest topic in modern physics. Despite the increasing number of astrophysical and cosmological observations proving the existence, so far no particle physics experiment has detected DM yet. Up to now, most of the experimental efforts have been focused on the so called WIMP (Weakly Interacting Massive Particle) paradigm, which predicts heavy DM (10 GeV-10 TeV mass range) interacting with Standard Model (SM) particles via the weak force mediators (W or Z bosons). More recently, due to the lack of clear evidence of WIMPs, other models of DM gained the interest of the physics community. These models consider Light DM particles (LDM), in MeV-GeV mass range. Among LDM theories, the Dark Photon theory predicts the existence of a Dark Sector interacting with SM particles via a new massive vector boson (Dark Photon, Heavy Photon or A0), mediator of a new force. This scenario, despite being theoretically well motivated, is remarkably experimentally unexplored. The Beam Dump eXperiment (BDX), is an approved experiment at Jefferson Lab (JLab), aiming to discover the DM predicted witihn the Dark Photon theory. The experiment uses the CEBAF (Continuous Electron Beam Accelerator Facility) 11 GeV electron beam, impinging on the JLab Hall-A beam-dump, to produce a beam of DM particles, detected by a ~ 1 m3 detector made of thallium doped cesium iodide (CsI(Tl)) crystals located ~ 20 m downstream. In order to achieve excellent background rejection, the experimental setup includes active vetos and passive shielding surrounding CsI(Tl) crystals. Given the weakness of the DM-SM interaction, the scattering of a DM particle in the BDX detector is a rare event. Therefore, the characterization of the expected background is a critical aspect of the experiment. Both cosmogenic and penetrating SM particles produced by the beam interaction in the dump contribute to the background of the experiment. While the cosmogenic contribution can be measured during the experiment when the beam is off, beam-related background can only be estimated via Monte Carlo (MC) simulations. Therefore, a careful assessment of possible systematics introduced by the MC is needed. The beam-correlated background characterization was made by measuring the muon flux produced by the interaction of the CEBAF beam with Hall-A dump in a dedicated experimental campaign in spring 2018 [1]. The comparison to the ?ux predicted by MC allowed us to validate the BDX simulation framework. The reach of BDX, i.e. the region that the experiment can probe in the LDM theory parameter space, depends critically on the background rejection capability and signal detection effciency. For this reason, the detector setup was fine-tuned through a dedicated study. The response to LDM and background events was evaluated for different setups and selection cuts. As a result of this procedure, the configuration resulting in the best sensitivity was selected [2]. The reach calculation was performed taking into account the different LDM production mechanisms, including the contribution of secondary particles produced in the beam-dump. In particular, the effect of the secondary positrons annihilation was found to be extremely significant. In the majority of the sensitivity studies, this contribution is neglected, but recent results [3] [4] demonstrated that this process significantly enhances the sensitivity of lepton beam-dump experiments. Currently, the BDX collaboration is focused on the deployment and operation of a small detector, called BDX-MINI, built to perform a preliminary physics measurement searching for LDM at JLab. This test will pave the way to the realization of the full BDX experiment. The measurement is currently ongoing but results are expected by the end of this year. During my PhD I was involved in all aspects of the BDX experiment: design, simulation, prototyping and data analysis. The main results of my work are reported in this thesis. This manuscript is organized as follows: the first Chapter provides an introduction to the theory of LDM, with particular attention to the Dark Photon paradigm; the second Chapter illustrates the BDX experimental setup, the LDM production and detection mechanisms and the expected backgrounds; Chapter 3 and 4 describe, respectively, the BDX-HODO measurement, with a detailed description of the simulations, and the BDX experimental setup and analysis cuts optimization. Chapter 5 reports about BDXMINI detector characterization, calibration and sensitivity estimate. Finally, Chapter 6 describes in detail the calculation of the secondary positron annihilation contribution to the sensitivity of BDX and other electron-beam thick-target experiment.

Marsicano, Luca↗
DOE OSTI2024

The Design, Fabrication, and Test Program for NREL's Wave-Powered Desalination System: Preprint

Starting in 2018, the U.S. Department of Energy's Water Power Technologies Office (WPTO), initiated the development of a prize competition as a foundational investment of Powering the Blue Economy, The prize encouraged the development of small, modular, cost-competitive wave-powered desalination systems. The National Renewable Energy Laboratory (NREL) was tasked with managing the prize, known as the Waves to Water Prize (W2W), and providing technical input based on prior desalination research performed at the lab. NREL partnered with the Coastal Studies Institute (CSI) and Jennette's Pier in North Carolina for their expertise in deploying research articles at the Jennette's Pier research facility. The prize consisted of five stages that included high-level concept proposals, numerical modelling, site- specific design, subsystem prototyping, and a final ocean demonstration. Due to the logistical risks of installing numerous prototypes in the ocean at the same time, NREL was tasked with designing and building a test article to de- risk the final event. The test article design needed to represent the technologies expected in the final stage of the prize. This meant that the design was expected to follow the same rules as the competitors, providing CSI with an opportunity to practice installations and develop a final logistics plan prior to the final event. After concluding the W2W event in April 2022, the NREL test article was redeployed in August 2022 to better understand the challenges of anchoring wave energy converters (WECs) in shallow water conditions with breaking waves. For the Spanish version of this report, see NREL/CP-5700-88482 (https://www.nrel.gov/docs/fy24osti/88482.pdf).

deployment↗
DOE OSTI2024

The Design, Fabrication, and Test Program for NREL's Wave-Powered Desalination System

Starting in 2018, the U.S. Department of Energy's Water Power Technologies Office (WPTO), initiated the development of a prize competition as a foundational investment of Powering the Blue Economy, the prize encouraged the development of small, modular, cost-competitive wave-powered desalination systems. The National Renewable Energy Laboratory (NREL) was tasked with managing the prize, known as the Waves to Water Prize (W2W), and providing technical input based on prior desalination research performed at the lab. NREL partnered with the Coastal Studies Institute (CSI) and Jennette's Pier in North Carolina for their expertise in deploying research articles at the Jennette's Pier research facility. The prize consisted of five stages that included high-level concept proposals, numerical modelling, site-specific design, subsystem prototyping, and a final ocean demonstration. Due to the logistical risks of installing numerous prototypes in the ocean at the same time, NREL was tasked with designing and building a test article to de-risk the final event. The test article design needed to represent the technologies expected in the final stage of the prize. This meant that the design was expected to follow the same rules as the competitors, providing CSI with an opportunity to practice installations and develop a final logistics plan prior to the final event. After concluding the W2W event in April 2022, the NREL test article was redeployed in August 2022 to better understand the challenges of anchoring wave energy converters (WECs) in shallow water conditions with breaking waves.

desalination↗
DOE OSTI2024

Simple and Robust Carrier-Based PWM Technique for Single-Stage Three-phase Rectifier Indirect Matrix Converter

Indirect matrix converters (IMC) can offer high efficiency, high power density, and bidirectional power flow capability with a single-stage three-to single-phase AC-AC power conversion integrating a conventional three-phase active rectifier with a primary side full-bridge inverter of a dual active bridge converter. However, the IMCs generally require space vector modulation techniques, leading to complex sectors and dwell times calculations. A practical implementation of the modulation methods with a commonly used digital signal processor becomes even more challenging when considering power factor correction, harmonics reduction, and deadtime between sector transitions. This paper proposes a simple and robust carrier-based pulse width modulation (PWM) technique determined through a voltage-source inverter (VSI) to current-source inverter (CSI) to IMC conversion. This translation enables the adoption of all conventional VSI control methods with active and reactive power control in the IMCs through simple carrier and reference waveform comparison. The VSI vectors are first one-on-one matched with CSI vectors and translated to IMC modulation signals without calculating sectors and dwell times. Nine different carrier waveforms are proposed, and the converter performance is analyzed. Grid current THD and efficiency are estimated for each modulation method. The symmetric A and B methods had the lowest THD of the grid current, 2.80%, and the efficiency remained at approximately 98.3%, making it the most suitable carrier-based method proposed in this paper. The space vector PWM (SVPWM) modulation method was implemented to the DSP and generated the expected twelve gate signals.

Benson, Mikayla↗
DOE OSTI2021

Design of High Power Density 100 kW Surface Permanent Magnet Machine with No Heavy Rare Earth Material Using Current Source Inverter for Traction Application

Surface permanent magnet (SPM) machines are appealing candidates for traction applications because of high power density and high efficiency. Rare-earth magnets deliver high performance but raise concerns about material supply dependability, particularly if they use heavy rare-earth materials. This paper presents the design of a high-performance SPM machine without any heavy rare-earth material that is optimized specifically for a current-source inverter (CSI) traction drive. This machine is designed for a constant-power speed ratio (CPSR) of 3. A genetic algorithm has been performed to achieve a target of 50 kW/L active power density at speeds up to 20,000 rpm. Operation at a peak line-to-line voltage of 800 V can be achieved using 1200 V power devices with a safety margin. The predicted electromagnetic and rotor structural performance characteristics are presented using both analytical and finite element analysis (FEA) results.

(CPSR)↗