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DOE OSTI2021

Polycrystalline SnSe with a thermoelectric figure of merit greater than the single crystal

Abstract Thermoelectric materials generate electric energy from waste heat, with conversion efficiency governed by the dimensionless figure of merit, ZT. Single-crystal tin selenide (SnSe) was discovered to exhibit a high ZT of roughly 2.2–2.6 at 913 K, but more practical and deployable polycrystal versions of the same compound suffer from much poorer overall ZT, thereby thwarting prospects for cost-effective lead-free thermoelectrics. The poor polycrystal bulk performance is attributed to traces of tin oxides covering the surface of SnSe powders, which increases thermal conductivity, reduces electrical conductivity and thereby reduces ZT. Here, we report that hole-doped SnSe polycrystalline samples with reagents carefully purified and tin oxides removed exhibit an ZT of roughly 3.1 at 783 K. Its lattice thermal conductivity is ultralow at roughly 0.07 W m –1 K –1 at 783 K, lower than the single crystals. The path to ultrahigh thermoelectric performance in polycrystalline samples is the proper removal of the deleterious thermally conductive oxides from the surface of SnSe grains. These results could open an era of high-performance practical thermoelectrics from this high-performance material.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Energy dataset of Frontier supercomputer for waste heat recovery

The Hewlett Packard Enterprise–Cray EX Frontier is the world’s first and fastest exascale supercomputer, hosted at the Oak Ridge Leadership Computing Facility in Tennessee, United States. Frontier is a significant electricity consumer, drawing 8–30 MW; this massive energy demand produces significant waste heat, requiring extensive cooling measures. Although harnessing this waste heat for campus heating is a sustainability goal at Oak Ridge National Laboratory (ORNL), the 30 °C–38 °C waste heat temperature poses compatibility issues with standard HVAC systems. Heat pump systems, prevalent in residential settings and some industries, can efficiently upgrade low-quality heat to usable energy for buildings. Thus, heat pump technology powered by renewable electricity offers an efficient, cost-effective solution for substantial waste heat recovery. However, a major challenge is the absence of benchmark data on high-performance computing (HPC) heat generation and waste heat profiles. This paper reports power demand and waste heat measurements from an ORNL HPC data centre, aiming to guide future research on optimizing waste heat recovery in large-scale data centres, especially those of HPC calibre.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A Framework for Optimal Placement of Rooftop Photovoltaic: Maximizing Solar Production and Operational Cost Savings in Residential Communities

Optimizing the placement of photovoltaic (PV) panels on residential buildings has the potential to significantly increase energy efficiency benefits to both homeowners and communities. Strategic PV placement can lower electricity costs by reducing the electricity fed from the grid during on-peak hours, while maintaining PV panel efficiency in terms of the amount of solar radiation received. In this article, we present a framework that identifies the ideal location of PV panels on residential rooftops. Our framework combines energy and environmental simulation, parametric modeling, and optimization to inform PV placement as it relates to and affects the entire community (in terms of both energy use and financial cost), as well as individual buildings. Ensuring that our framework accounts for shading from nearby buildings, different utility rate structures, and different buildings’ energy demand profiles means that existing communities and future housing developments can be optimized for energy savings and PV efficiency. The framework comprises two workflows, each contributing to optimal PV placement with a unique target: (a) maximizing PV panel efficiency (i.e., solar generation) and (b) minimizing operational energy cost considering utility rate structures for operational energy. We apply our framework to a residential community in Fort Collins, Colorado, to demonstrate the optimal PV placement, considering the two workflow targets. Here, we present our results and illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost.

14 SOLAR ENERGY↗

DOE OSTI2022

Split HPWHs as an Efficient Solution for Multifamily Buildings with In-Unit Water Heaters

A quarter of all housing units in the United States are found in multifamily buildings, but few efficiency innovations have been made to improve electric water heating systems in this building type. Domestic hot water in multifamily buildings can either be provided by a large central water heater or smaller in-unit water heaters. Integrated heat pump water heaters that are installed in single-family homes are often a poor fit for individual multifamily units because the water heaters are often located in small internal closets. This confined space can limit the airflow to the heat pump, and the cold exhaust air can cause discomfort and reduced efficiency. Split CO2 HPWHs separate the tank from the heat pump, which allows for installation location flexibility. Further, CO2 heat pumps can operate under colder ambient conditions, making them a better fit for multifamily units across a wide range of climate regions. As part of a larger project to characterize split HPWH performance, we evaluated the feasibility of installing an additional, parallel tank that could provide hot water to a second housing unit using a single CO2 heat pump. This approach would reduce the first costs of these more expensive units. Based on the high draw volume that we imposed on both tanks, the same heat pump may be able to support more tanks, depending on hot water usage. This paper will describe the split CO2 HPWH technology, how the two-tank system was controlled, and results from our laboratory evaluation.

CO2 HPWH↗

DOE OSTI2022

Split HPWHs as an Efficient Solution for Multifamily Buildings with In-Unit Water Heaters: Preprint

A quarter of all housing units in the country are found in multifamily buildings but few efficiency innovations have been made to improve electric water heating systems in this building type. Domestic hot water in multifamily buildings can either be provided by a large central water heater or smaller in-unit water heaters. Integrated heat pump water heaters that are installed in single family homes are often a poor fit for individual multifamily units since the water heaters are often located in small internal closets. This confined space can limit the air flow to the heat pump and the cold exhaust air can cause discomfort and reduced efficiency. Split CO2 HPWHs separate the tank from the heat pump, which allows for installation location flexibility. Further, CO2 heat pumps can operate under colder ambient conditions, making them a better fit for multifamily units across a wide range of climate regions. As part of a larger project to characterize split HPWH performance, we evaluated the feasibility of installing an additional, parallel tank that could provide hot water to a second housing unit using a single CO2 heat pump. This approach would reduce the first costs of these more expensive units. Based on the high draw volume that we imposed on both tanks, the same heat pump may be able to support more tanks, depending on hot water usage. This paper will describe the split CO2 HPWH technology, how the two-tank system was controlled, and results from our laboratory evaluation.

CO2 HPWH↗

DOE OSTI2021

Comprehensive Performance Calibration Guidance for Perovskites and Other Emerging Solar Cells

Emerging photovoltaic (PV) technologies (e.g., organic, perovskite, and solution processed quantum dot) have attracted remarkable attention with the rapid growth of their efficiencies, and their transition toward commercialization. Accurate and reliable efficiency measurements of these PV technologies are crucial, yet much more complicated than for conventional PV technologies due to the former's pronounced dynamic responses to changes in measurement conditions (e.g., current–voltage (I–V) scan rate and preconditioning) and their susceptibility to degradation. Adjustments to the measurement procedures are therefore necessary so that a reproducible “steady state” is reached during measurement. Furthermore, given the small size of many emerging cells, inappropriate device area definition and solar simulator setup can lead to measurement errors. Here, comprehensive efficiency calibration guidance is offered for emerging solar cells, including area measurement; spectral irradiance translation to standard test conditions; and steady-state electrical performance. The necessity of reporting steady-state efficiency is justified with a statistical performance comparison between conventional and steady-state I–V scans over hundreds of cells the group has received globally for efficiency certifications. The procedures described here do not require specialized measurement instrumentation; what matters most are changes to the measurement protocols. These described changes aim to enable better comparisons between reported efficiencies.

14 SOLAR ENERGY↗

DOE OSTI2022

Customer outcomes in Pay-As-You-Save programs

We review the energy and financial outcomes of households participating in several programs based on successive versions of the Pay As You Save¯ (PAYS¯) system. PAYS¯ programs offer non-debt financing for energy efficiency (and sometimes other technologies) in residential buildings through a tariff attached to the home’s utility meter, designed to be offset by project savings. We find that the five programs we study generally serve customers living in zip codes with levels of income and education below the national average and unemployment rates above the national average, demonstrating their potential to improve equity in energy efficiency adoption. Using weather-normalized analysis of energy consumption data, we show that most customers of Midwest Energy’s program reduce annual electricity and gas consumption, averaging 15% and 26% reductions respectively. Changes in energy consumption calculated using this method represent a combination of project effects and changes in occupant behavior. These results are similar to existing analyses of PAYS¯ programs in North Carolina, Arkansas, and Tennessee. About half of participating Midwest households generate sufficient energy cost savings to cover their monthly tariff. Various factors, including changes in occupant behavior, program error, causes independent of the customer or program, or some combination thereof may explain lower-than-expected cost reductions in some projects. Given the inherent variability in annual household electricity consumption, we feel these programs are enabling energy efficiency improvements and their attendant co-benefits, including occupant health and comfort and reduced carbon emissions, while reasonably balancing energy savings and tariff costs. Pairing PAYS¯ with additional financial assistance, as well as promoting cost-effective measures such as air and duct sealing, could further broaden program participation by enabling additional projects to meet PAYS¯ program eligibility rules.

Deason, Jeff↗

DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Heat Pump Rooftop Units With Exhaust Air Energy Recovery

This technical report documents the Advanced Rooftop Unit Control End Use Savings Shapes (EUSS) measure, including providing a description of the technology, modeling methods, and the energy savings calculated from applying the measure to applicable across the US commercial building stock using ComStock to quantify its potential. This measure replaces gas furnace and electric resistance rooftop units with high-efficiency variable speed heat pump rooftop units (HP-RTU) that include exhaust air heat or energy recovery. The measure uses the same assumptions and technology as the variable speed HP-RTU measure from EUSS 2023 release 1 but adds energy recovery to precondition outdoor ventilation air to reduce HVAC loads. The HP-RTU compressor lockout temperature is modeled as 0 degrees Fahrenheit; below this temperature, the heat pump is set to shut off. The unit is sized based on the design cooling loads, with backup electric resistance heating addressing any remaining loads including heating hours below the compressor lockout temperature when there is no heat pump heating.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Tracking the PACE of household energy usage: Energy usage impacts of projects financed through Property Assessed Clean Energy programs in California

This report examines the household-level energy impacts of residential property assessed clean energy (R-PACE) projects using normalized metered energy consumption methods. Our analysis covers projects that occurred through an R-PACE program between 2009 and 2017 and includes more than 25,000 electricity meters and 15,000 gas meters. We employ a comparison group, drawn from other R-PACE households with similar locational and usage characteristics whose projects were implemented at different times, to control for some non-project and non-weather factors that may impact energy use. We find that projects consisting of energy efficiency technologies save, on average, about 3% of household electricity usage and 3.5% of household gas usage. R-PACE financing, however, can be used to install central heating or air conditioning equipment for the first time. These projects would be expected to increase energy consumption. Since our data do not directly indicate which projects are new installations, we develop a simple algorithm for identifying them. Removing these inferred installation projects yields average savings of about 5% for electricity and 6% for gas for those households that remain in the sample. Given the mild California climate and the results of another study of similar California projects using similar methods, these results are in line with expectations. Solar PV projects yield large reductions in grid electricity use, averaging 69% of household consumption. We estimate that, collectively, all R-PACE projects installed in California through 2019 would generate annual reductions in grid-tied electricity consumption of 506 GWh (mostly due to solar PV) and gas consumption reductions of 2 million therms in a normal weather year. These impacts are equivalent to the electricity consumption of about 74,000 California households (including both efficiency and PV generation) and the gas consumption of about 4700 California households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL) proved to be effective in optimizing the management of integrated energy systems in buildings, reducing energy costs and improving indoor comfort conditions when compared to traditional reactive controllers. However, the scalability and implementation of DRL controllers are still limited since they require a considerable amount of time before converging to a near-optimal solution. This issue is currently addressed in literature through the offline pre-training of the DRL agent. However this solution results in two main critical issues: (1) the need to develop a building surrogate model to perform the training task, and (2) the need to perform a fine-tuning process over several training episodes to obtain a near-optimal control policy. In this context, this paper introduces an Online Transfer Learning (OTL) strategy that exploits two knowledge-sharing techniques, weight-initialization and imitation learning, to transfer a DRL control policy from a source office building to various target buildings in a simulation environment coupling EnergyPlus and Python. A DRL controller based on discrete Soft Actor–Critic (SAC) is trained on the source building to manage the operation of a cooling system consisting of a chiller and a thermal storage. Several target buildings are defined to benchmark the performance of the OTL strategy with that of a Rule-Based Controller (RBC) and two DRL-based control strategies, deployed in offline and online fashion. The strategy adopted for OTL emulates the real world implementation with a simulation process by implementing the transferred DRL agent for a single episode in the target buildings. Target buildings have the same geometrical features and are served by the same energy system as the source building, but differ in terms of weather conditions, electricity price schedules, occupancy patterns, and building envelope efficiency levels. The results show that the OTL strategy can reduce the cumulated sum of temperature violations on average by 50% and 80% respectively when compared to RBC and online DRL while enhancing the energy system operation with electricity cost savings ranging between 20% and 40%. Furthermore, the OTL agent performs slightly worse than the offline DRL controller but it does not require any modeling effort and can be implemented directly on target buildings emulating a real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

We report ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility's distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood's load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes' energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community's demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

Building electrical load profiles can improve understanding of building energy efficiency, demand flexibility, and building-grid interactions. Current approaches to generating load profiles are time-consuming and not capable of reflecting the dynamic and stochastic behaviors of real buildings; some approaches also trigger data privacy concerns. In this study, we proposed a novel approach for generating realistic electrical load profiles of buildings through the Generative Adversarial Network (GAN), a machine learning technique that is capable of revealing an unknown probability distribution purely from data. The proposed approach has three main steps: (1) normalizing the daily 24-hour load profiles, (2) clustering the daily load profiles with the k-means algorithm, and (3) using GAN to generate daily load profiles for each cluster. The approach was tested with an open-source database – the Building Data Genome Project. We validated the proposed method by comparing the mean, standard deviation, and distribution of key parameters of the generated load profiles with those of the real ones. The KL divergence of the generated and real load profiles are within 0.3 for majority of parameters and clusters. Additionally, results showed the load profiles generated by GAN can capture not only the general trend but also the random variations of the actual electrical loads in buildings. We report the proposed GAN approach can be used to generate building electrical load profiles, verify other load profile generation models, detect changes to load profiles, and more importantly, anonymize smart meter data for sharing, to support research and applications of grid-interactive efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

2D microspatial distribution uniformity of photon detection efficiency and crosstalk probability of multi-pixel photon counters

Two-dimensional (2D) microspatial distribution uniformity of photon detection efficiency (PDE) and optical crosstalk probability P{sub ct} of multi-pixel photon counters (MPPCs) is studied. The experimental results show that the 2D spatial distribution of P{sub ct} is obviously uneven, i.e. P{sub ct} is larger at the corners and edges of a single pixel in MPPCs, which suggest a higher electrical field in the depletion region of the pixel at the corners and edges. The nonuniformity of the 2D spatial distribution of PDE also become evident when the size of the pixels of MPPCs is small, which signifies higher nonuniformity of the electric field distribution in MPPCs with small pixel size. A method is proposed for characterization of the 2D electrical field spatial distribution uniformity in a single pixel of MPPCs, which can be used for guiding the optimisation of the fabrication process of MPPCs and their properties. This promising method can naturally be extended to any Geiger avalanche photodiodes (G-APDs) and their arrays. (laser applications and other topics in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Electrically enhanced thermochemical cycles for hydrogen generation

In two-step metal-oxide (MO) solar thermochemical cycles, high temperature solar thermal energy is first converted to chemical energy in the form of a reduced MO. The reduced MO is then reoxidized in a second step with steam (or carbon dioxide) to produce hydrogen (or carbon monoxide) at a lower temperature. Solar thermochemical cycles of this type circumvent heat-to-electrical conversion required for electrochemical water splitting and promise high efficiencies. However, significant challenges remain to implementation. Ultra-high temperatures and efficiency-sapping low per-cycle conversion stand out as particularly difficult hurdles. Hybrid approaches utilizing both thermal and electrical energy provide some of the advantages of each, and can facilitate lower temperature operation and offer better per-pass utilization than thermochemical alone. However, early concepts for implementing the thermo-electrochemical approach introduced substantial new challenges including difficult separations, corrosive environments, and energy losses from large temperature swings and phase changes. We are currently investigating two different options for implementation. In the first, a MO that reduces at lower temperature is selected. As the reduced MO lacks the full thermodynamic driving force to effectively split water, the reaction is driven forward by an electrically-assisted proton-conducting membrane that separates and recovers hydrogen as it is produced. This approach produces a pure hydrogen stream, is mechanically simple, and has unique thermodynamic advantages. The second option seeks to more directly couple the electrical boost to the solid MO to drive either the reduction or oxidation step, or both, through the utilization of layered MO materials and advanced reactors. This approach could be applied to both water and carbon dioxide splitting. The results of process modeling and optimization will be presented, and progress towards demonstrating the concepts at the laboratory scale will be discussed.

08 HYDROGEN↗

DOE OSTI2024

Dissolution of Mg-enriched defects in implanted GaN and increased p-type dopant activation

Annealing Mg-implanted homoepitaxial GaN at temperatures above 1400 °C eliminates the formation of inversion domains and leads to improved dopant activation efficiency. Extended defects, in the form of inversion domains, contain electrically inactive Mg after post-implantation annealing at temperatures as high as 1300 °C (one GPa N 2 overpressure), which results in a low dopant activation efficiency. Triple-axis x-ray data reveal that implant-induced strain is fully relieved after annealing at 1300 °C for 10 min, indicating that strain-inducing point defects formed during implantation have reconfigured and inversion domains are formed. However, annealing at temperatures of 1400–1500 °C (one GPa N 2 overpressure) eliminates the presence of the inversion domains. While residual defects, such as dislocation loops, still exist after annealing at and above 1400 °C, chemical analysis at multiple dislocation loops shows no sign of Mg segregation. Meanwhile, an overall decreasing trend in the dislocation loop density is observed after annealing at the higher temperatures and longer times. Additionally, once inversion domains are formed and the samples are cooled to room temperature, they are shown to dissolve with subsequent annealing above 1400 °C. While such defects have been observed before, the important finding that such defects can be dissolved with a short, higher temperature step is key. Earlier work [Breckenridge et al., J. Appl. Phys. Lett. 118, 022101 (2021)] addressing electrical measurements of these types of samples showed that annealing at 1400 °C leads to a dopant activation efficiency that is an order of magnitude higher than that observed at 1300 °C. In conclusion, this work complements earlier work by identifying the inversion domains, which incorporate Mg, and points to the benefits, in terms of defect density and p-type dopant activation, of using higher temperature (>1400 °C) annealing cycles to activate Mg in GaN, even if the Mg-containing inversion domains had been formed during lower temperature annealing.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Analyzing School Bus Electrification in Richmond, Virginia

School buses are an essential component of the transportation infrastructure, serving as a lifeline for students across the globe. However, the widespread use of diesel school buses has raised concerns about the health impact on millions of students exposed to harmful emissions daily. Recognizing this issue, school districts worldwide are urgently seeking cleaner energy alternatives. Electric school buses emerge as an environmentally friendly and sustainable option, fostering a healthier environment for both students and communities. However, school bus electrification faces the challenges of high upfront cost, cumbersome charging management, and constraints from power grids. To help school bus operators address those challenges, this study presents a data-driven analysis for school bus electrification. This study considered a real-world school bus system in Richmond, VA, and developed a mathematical programming model to analyze the system design, charging strategies, and charging load profiles for the electrification scenario. The study evaluated different charging strategies based on model outcomes, aiming to optimize efficiency and effectiveness. Ultimately, this research generated electric school bus charging demand profiles under various scenarios, shedding light on the feasibility and implications of transitioning to electric-powered school buses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Neuromorphic spintronics

Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial neurons and synapses are, however, currently limited by the energy and area requirements of these components. Spintronic nanodevices, which exploit both the magnetic and electrical properties of electrons, can increase the energy efficiency and decrease the area of these circuits, and magnetic tunnel junctions are of particular interest as neuromorphic computing elements because they are compatible with standard integrated circuits and can support multiple functionalities. Here, we review the development of spintronic devices for neuromorphic computing. We examine how magnetic tunnel junctions can serve as synapses and neurons, and how magnetic textures, such as domain walls and skyrmions, can function as neurons. We also explore spintronics-based implementations of neuromorphic computing tasks, such as pattern recognition in an associative memory, and discuss the challenges that exist in scaling up these systems.

42 ENGINEERING↗

DOE OSTI2023

Condition monitoring of permanent magnet AC machines for all-electric transportation systems: State of the art

The current state of the art on emerging and efficient techniques for condition monitoring of permanent magnet (PM) alternating-current (AC) machines deployed in electric vehicle (EV) applications is presented. The discussion includes the most common and specific types of faults in PM motors, such as rotor demagnetisation and stator inter-turn faults, respectively. Fault indicators, such as voltage (v s ) and current (i s ) signals and machine signatures based on motor back electromotive force (EMF) (E B ) and magnetic flux (φ), are taken into account as a measuring quantity in diagnosing motor faults. Other signatures, including thermal analysis, acoustic noise, and vibrations, are also illustrated as some of the emerging techniques in estimating the performance of EV motors while under operations. In addition, various fault modelling methods, condition monitoring techniques, and comprehensive approaches applied in diagnosing the effect of machine faults during its incipient stages are illustrated. Since most of the fault diagnostic techniques discussed here include only machine-based quantities as fault indices/indicators, the provided solutions are therefore found to be more reliable and accurate for diagnosing the motor faults. This comprehensive review study is inclusive of the existing fault diagnostic techniques, which are currently employed in industrial and commercial practices, in addition to the new methodologies proposed by the authors. All the given condition monitoring schemes therefore seem significantly vital in estimating the state of health of PM AC machines while under operation in all-electric transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗