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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter utilizing Kalman-Schmidt and Rach-Tung-Striebel smoothers is developed to obtain entry vehicle atmosphere estimates. The filter/smoother blends information from pressure sensors distributed on the heatshield with measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars Science Laboratory and Mars 2020 entry, descent, and landing at Gale crater and at Jezero crater, respectively. The results show that the hybrid filter produces estimates of the freestream flight condition with lower uncertainty than either the flush or synthetic air data algorithms. The filter accomplishes this result by incorporating additional data and computing estimates of systematic error parameters in the pressure data and the aerodynamic model to further reduce the uncertainties.

Christopher D. Karlgaard↗
NASA NTRSDate not supplied

Synergy of Satellite Radiation, Precipitation, and Other Meteorological Variable Observations for Global Mean Sea Surface Turbulent Heat Flux Estimation

Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.

Bing Lin↗
NASA NTRSDate not supplied

Uncertainties in an Observation-Based Estimate of the Global Aerosol Direct Radiative Effect

Aerosols impact Earth’s radiation budget directly through interactions with radiation and indirectly via interactions with clouds. Aerosols have significant radiative impacts on Earth’s energy budget and represent the largest uncertainty in the radiative forcing of the current climate. Although the magnitude of the aerosol direct radiative effect (DRE) is estimated to be less than that of the indirect effect, uncertainties are large. While model-based estimates of aerosol radiative forcing are subject to uncertainties in modeled aerosol properties and uncertainties in simulated cloud cover and albedo, most observation-based studies of global aerosol DRE have their own difficulties with aerosol optical properties and have been limited to cloud-free skies in most cases. Estimates of the uncertainty of the aerosol DRE are themselves uncertain and have varied widely among different published studies. In this study we use the CERES-CALIPSO-CloudSat-MODIS (C3M) product to estimate the global clear-sky and all-sky aerosol DRE. C3M merges collocated data from CERES, CALIPSO, CloudSat, and MODIS with information from reanalysis and an aerosol transport model. With CALIOP observations of aerosol below optically thin clouds and above clouds, co-located with cloud albedo from MODIS, the C3M dataset allows a detailed exploration of observational uncertainties. By perturbing the aerosol properties used and comparing radiative effects in perturbed cases with the base case we characterize uncertainties in estimated aerosol DRE due to uncertainties in the aerosol properties involved. The results also provide a basis for determining measurement requirements to improve the accuracy of DRE estimates. We will describe the approach and present results.

Dave Winker↗
NASA NTRS2023

Estimating the concentration of total suspended solids in inland and coastal waters from Sentinel-2 MSI: A semi-analytical approach

Inland and coastal waters provide key ecosystem services and are closely linked to human well-being. In this study, we propose a semi-analytical method, which can be applied to Sentinel-2 MultiSpectral Instrument (MSI) images to retrieve high spatial-resolution total suspended solids (TSS) concentration in a broad spectrum of aquatic ecosystems ranging from clear to extremely turbid waters. The presented approach has four main steps. First, the remote sensing reflectance ( R rs ) at a band lacking in MSI (620 nm) is estimated through an empirical relationship from R rs at 665 nm. Second, waters are classified into four types (clear, moderately turbid, highly turbid, and extremely turbid). Third, semi-analytical algorithms are used to estimate the particulate backscattering coefficient ( b bp ) at a reference band depending on the water types. Last, TSS is estimated from bbp at the reference band. Validation and comparison of the proposed method with three existing methods are performed using a simulated dataset ( N = 1000), an in situ dataset collected from global inland and coastal waters ( N = 1265) and satellite matchups ( N = 40). Results indicate that the proposed method can improve TSS estimation and provide accurate retrievals of TSS from all three datasets, with a median absolute percentage error (MAPE) of 14.88 %, 31.50 % and 41.69 % respectively. We also present comparisons of TSS mapping between the Sentinel-3 Ocean and Land Colour Instrument (OLCI) and MSI in Lake Kasumigaura, Japan and the Tagus Estuary, Portugal. Results clearly demonstrate the advantages of using MSI for TSS monitoring in small water bodies such as rivers, river mouths and other nearshore waters. MSI can provide more detailed and realistic TSS estimates than OLCI in these water bodies. The proposed TSS estimation method was applied to MSI images to produce TSS time-series in Lake Kasumigaura, which showed good agreements with in situ and OLCI-derived TSS time-series.

Sentinel-2↗
NASA NTRSDate not supplied

Accounting for Point Estimate Uncertainty in Space Systems Reliability and Risk Analysis

Understanding and accounting for uncertainty in risk analysis is a critical step in the management and communication of risk in engineered systems. The component and system-level analysis to determine the probability of a negative outcome and its consequence is often quantified by a point estimate. Many Program and Enterprise decisions involving technical concerns and issues rely on reliability engineering activities to produce quantified risk analysis to inform the decision making process. At NASA, it is common to use a Probabilistic Risk Analysis (PRA) to inform the overall risk to Loss of Mission or Loss of Crew that involves integration across all spacecraft subsystem fault trees to produce an overall probability of mission failure. The point estimate is an estimate of this overall probability and is an immediate result of a fault tree model. It is the result of a model where the probability of each event is taken to be equal to its mean. The value provides an approximation of the overall mean without running any uncertainty calculations (e.g., no sampling). Using only the point estimate can lead to a false sense of precision and the point estimate may not match the resulting mean when uncertainty is taken into consideration. This paper will explore five conditions that can cause the PRA model mean to diverge from the point estimate and will provide engineers and managers insight into the importance of understanding uncertainty in the elements of PRA models.

Paul J Collier↗
DOE OSTI2011

Meta-Analysis of Estimates of Life Cycle Greenhouse Gas Emissions from Concentrating Solar Power: Preprint

In reviewing life cycle assessment (LCA) literature of utility-scale CSP systems, this analysis focuses on clarifying central tendency and reducing variability in estimates of life cycle greenhouse gas (GHG) emissions through a meta-analytical process called harmonization. From 125 references reviewed, 10 produced 36 independent GHG emission estimates passing screens for quality and relevance: 19for parabolic trough technology and 17 for power tower technology. The interquartile range (IQR) of published GHG emission estimates was 83 and 20 g CO2eq/kWh for trough and tower, respectively, with medians of 26 and 38 g CO2eq/kWh. Two levels of harmonization were applied. Light harmonization reduced variability in published estimates by using consistent values for key parameters pertaining toplant design and performance. Compared to the published estimates, IQR was reduced by 69% and median increased by 76% for troughs. IQR was reduced by 26% for towers, and median was reduced by 34%. A second level of harmonization was applied to five well-documented trough LC GHG emission estimates, harmonizing to consistent values for GHG emissions embodied in materials and from constructionactivities. As a result, their median was further reduced by 5%, while the range increased by 6%. In sum, harmonization clarified previous results.

14 SOLAR ENERGY↗
DOE OSTI2012

AN OVERVIEW OF TOOL FOR RESPONSE ACTION COST ESTIMATING (TRACE)

Tools and techniques that provide improved performance and reduced costs are important to government programs, particularly in current times. An opportunity for improvement was identified for preparation of cost estimates used to support the evaluation of response action alternatives. As a result, CH2M HILL Plateau Remediation Company has developed Tool for Response Action Cost Estimating (TRACE). TRACE is a multi-page Microsoft Excel{reg_sign} workbook developed to introduce efficiencies into the timely and consistent production of cost estimates for response action alternatives. This tool combines costs derived from extensive site-specific runs of commercially available remediation cost models with site-specific and estimator-researched and derived costs, providing the best estimating sources available. TRACE also provides for common quantity and key parameter links across multiple alternatives, maximizing ease of updating estimates and performing sensitivity analyses, and ensuring consistency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

sparse-msrf:A package for sparse modeling and estimation of fossil-fuel CO2 emission fields

The software is used to fit models of emission fields (e.g., fossil-fuel CO2 emissions) to sparse measurements of gaseous concentrations. Its primary aim is to provide an implementation and a demonstration for the algorithms and models developed in J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders and S. A. McKenna, "A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions", accepted, Geoscientific Model Development, 2014. The software can be used to estimate emissions of non-reactive gases such as fossil-fuel CO2, methane etc. The software uses a proxy of the emission field being estimated (e.g., for fossil-fuel CO2, a population density map is a good proxy) to construct a wavelet model for the emission field. It then uses a shrinkage regression algorithm called Stagewise Orthogonal Matching Pursuit (StOMP) to fit the wavelet model to concentration measurements, using an atmospheric transport model to relate emission and concentration fields. Algorithmic novelties described in the paper above (1) ensure that the estimated emission fields are non-negative, (2) allow the use of guesses for emission fields to accelerate the estimation processes and (3) ensure that under/overestimates in the guesses do not skew the estimation.

Source record↗
DOE OSTI2018

Crop Stem Width Estimation in Highly Cluttered Field Environment

We present two methods for estimation of crop stem width on small mobile robots. Stem width is an important phenotype needed by breeders and plant-biologists to measure plant growth, however, its manual measurement is cumbersome, in-accurate, and inefficient. The presented methods use a common image processing core that is designed to extract the foreground in the presence of significant leaf and stem clutter, view of other rows, and varying lighting, from a side-facing USB camera mounted on a small mobile robot. Using the extracted foreground, one approach uses estimates of robot velocity from wheel encoders and dense optical flow to estimate depth, while the other employs filtering of the LIDAR 2-D point cloud to estimate the depth. Both methods have been exhaustively validated against available hand-measurements on biomass sorghum (Sorghum bicolor) in real experimental fields. Experiments indicate that both methods are also applicable to other crops with cylindrical stems without significant modifications. The width estimation match on sorghum is 92.5% (using vision) and 98.2% (using vision and LIDAR) when compared against manual measurements by trained agronomists. Thus, our results clearly establish the feasibility of using small robots for stem-width estimation in realistic field settings. Furthermore, the techniques presented here can be utilized for automating other phenotypic measurements.

Choudhuri, Anwesa↗
DOE OSTI2021

Introducing the GeoRePORT Resource Size Tool: Reporting on Geothermal Resource Size Estimations Using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT): Preprint

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) was developed with funding from the U.S. Department of Energy Geothermal Technologies Office to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. The assessment protocols used in GeoRePORT allow for comparison of project attributes across locations and geological settings to understand the feasibility of geothermal development. This work introduces the Resource Size Tool, a new feature within the GeoRePORT package that compiles two independent methods for estimating geothermal resource size in terms of energy capacity in MW. Energy production potential for twenty-three case studies was estimated with the Resource Size Tool in order to 1) generate a reasonable range of resource size estimates for a particular geothermal field; 2) illustrate the advantages and limitations of each methodology (such as data input requirements, estimate accuracy and precision, and the appropriate circumstances of use); and 3) test the ability of the resource size tool to provide useful and accurate information for geothermal stakeholders. The tool employs two methods widely used in the geothermal industry: (1) USGS Volumetric and (2) Power Density. Results from our case studies show general overlap between these two methods in terms of resource size estimates; however, they also reveal key differences between the two approaches that should be considered when using such estimates to drive development. First, the two methods rely on different input parameters and therefore one method may be more appropriate and/or accurate for a given project than the other. Second, the Power Density method was found to generate wider ranges of resource size predictions, more consistently aligning with actual power production of the field but with larger scales of error; whereas the USGS Volumetric method predicts narrower ranges but tends to overestimate when compared to current MW production. Future work will refine variables used in the methods with input data from other sections of GeoRePORT and modify uncertainty levels based on the particular datasets used for a given project.

geological↗
DOE OSTI2022

Spatial Transferability of Machine Learning Based Volume Estimation Models

High-quality traffic volume data is essential for efficient transportation planning and operations. However, such high-quality data is expensive to collect, owing primarily to the high capital cost of installing and maintaining continuous counting stations (CCSs). Recent availability of probe-based vehicle data offers a cost-effective solution for increasing the observability of traffic volumes. However, having ample ground truth traffic data is a prerequisite for developing robust volume estimation models. Though this might not be a big issue in many states, states with scarce CCS data might be able to benefit from robust volume estimation models developed in (adjacent) data-rich states. While there is a reasonable amount of spatial transferability research in the transportation domain, there is a dearth of knowledge on the spatial transferability of probe-based volume estimation models. To address this gap, this paper explores spatial transferability of volume estimation models developed from data in three states (Colorado, North Carolina, and Pennsylvania). Results indicate that it is extremely important to maintain temporal consistency when attempting spatial transferability of volume estimation models. It was also found that models trained on regions with lower peak traffic volumes will limit the performance of models transferred to states with higher peak hourly traffic volumes. Corroborating findings from existing spatial transferability research on other topics, it was found that a meta-model (developed using data from multiple states) performs better than volume estimation models developed within any one of the states.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

The Future of EPA's Waste Estimation Support Tool - 17227

The Environmental Protection Agency's (EPA's) Waste Estimation Support Tool (WEST) is a GIS-based decision support tool for estimating the characteristics, amount, and residual radioactivity of waste generated from remediation and cleanup activities after a radiological incident, including those involving radiological dispersal devices, improvised nuclear devices, and nuclear power plants. WEST has been released to the public and has been used in numerous national level exercises and planning scenarios; however, it continues to be improved and refined to add additional functionality and performance. Since its inception, WEST has undergone a myriad of updates, routinely ensuring compatibility with ESRI's ArcGIS and FEMA's Hazus, a tool for estimating potential losses from earthquakes, wind, and flood events. Furthermore, recent enhancements have added reporting and mapping features and multi-state support. Over time, this progress has strained WEST's Microsoft{sup C} Excel based platform. The inherent limitations of Excel have limited the capacity of WEST and narrowed the scope of potential enhancements. Recent collaborative efforts between the Department of Homeland Security's (DHS's) Science and Technology Directorate (S and T) and EPA will see the introduction of a new software platform for easing memory limitations and new and innovative features for improving the accuracy of waste estimates. The planned enhancements include: 1) Systems approach: measure or predict the outcome of decisions associated with disaster response (e.g., decontamination efficacy vs. waste) and to a greater extent, the overall resource demand (e.g., cost, time, etc.); 2) Custom infrastructure data and international support: accommodate non-US building information where available and also add new data and information on recently used decontamination technologies as applied in a real-world incident; 3) Additional waste factors: addition of waste factors that are unique to wide area scenarios such as vehicles and trees as they will likely contribute in a significant manner to the overall waste stream;4) Site analysis and logistics: apply spatial information and analysis technologies to locate and prioritize potential waste staging or storage sites; and use GIS-based logistics planning to better organize, route, and estimate the cost, time, and logistical requirements (i.e., resource demand) associated with transporting large volumes of waste from a disaster-stricken area to waste staging or storage sites; 5) Decontamination technologies: introduce new decontamination technologies, better understand the feasibility and efficacy of new and preexisting decontamination technologies when applied to a wide area incident, and use historical incidents to ground truth waste results; and 6) Resource demand: ability to estimate resource demand information associated with decontamination technologies, waste staging and storage, and logistical information for transporting waste. This paper will describe the next version of WEST (WEST 4.0), and how the aforementioned enhancements will contribute to improving the planning and response capabilities of the tool. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Cylindrical Kernel Density Estimators For Monte Carlo Neutron Transport Reactor Physics Problems

Kernel Density Estimators (KDEs) have been investigated as an alternative to histogram tallies in Monte Carlo radiation transport simulations for capturing spatially-resolved quantities such as scalar flux and reaction rate densities. KDEs are non-parametric estimators that show potential for producing smooth estimates of quantities of interest with reduced variance compared to traditional histogram tallies. Furthermore, KDEs obtain estimates of the underlying distribution at user-defined points without requiring an underlying mesh, thus making KDEs an attractive potential alternative to histogram tallies. Recent work has introduced the Mean Free Path based KDE (MFP KDE) in order to capture distributions with large curvature at material interfaces, e.g. absorption reaction rates in UO{sub 2} fuel in light water reactors. However, the multivariate MFP KDE produces inaccuracies in the form of localized spikes in problems with material cross sections that contain large resonances. Since the MFP KDE works well in one dimension, it is hypothesized that a different MFP KDE formulation where the normalization coefficient only contains one factor of the cross section would be able to capture these distributions with large curvature without producing spikes in the estimate. This can be accomplished by using a cylindrical KDE whose 2-D support area is wedge-shaped and applying the MFP KDE to the radial component of the cylindrical KDE. These cylindrical KDEs use 2-D (r,θ) cylindrical coordinates with no dependence in axial dimension z. This paper derives the cylindrical KDE and the cylindrical MFP KDE and tests them on a reactor physics pin-cell benchmark problem, producing accurate estimates of flux and reaction rate densities with differences less than 0.5% when compared to a reference histogram. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Updating Nuclear Energy Cost Estimates for Net Zero World Initiative

Energy modeling of decarbonized scenarios in integrated energy systems requires nuclear energy parameters that are critical for forecasting, modeling and cost structure analysis. Using updated real-world data has always been a challenge to estimate current nuclear reactors costs and deployment scenarios. Given this, an updated set of parameters for overnight capital costs and operation and maintenance costs are estimated for the Net Zero World initiative using recent reports that provided a vast set of open sources data inputs. This paper follows the methodology developed in the Net Zero World report and applies the new ranges estimated in the Gateway for Accelerated Innovation in Nuclear report that address many of the current challenges in obtaining accurate cost data for advanced nuclear concepts. The final goal is to provide new estimates of the overnight capital costs and operational costs for different countries. The present paper improves the earlier capital cost estimations, building on recent literature that aims to obtain accurate data for modeling and simulation to enhance energy system evaluations and support decision-making in areas like de-carbonization and capacity expansion. Finally, the paper compares the new cost estimates with the old cost results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Ensuring Solution Uniqueness in Three-Phase Power System State Estimation

This paper is concerned with the issue of potential non-unique solutions in three-phase state estimation. Theory of observability analysis for positive sequence power system state estimation is based on certain assumptions that avoid possibility of multiple solutions. Also, it is shown that observability of a positive sequence network remains independent of the network parameters or the operating state. When extending single-phase observability analysis directly to the three-phase case, this paper considers the possibility of converging to multiple solutions, i.e. solution non-uniqueness, even for cases where state estimator successfully converges. The study illustrates via numerical examples the likelihood of converging to entirely different solutions for certain network parameters. It also examines how the operating state, particularly under unbalanced loading, leads to solution non-uniqueness. The paper then describes an alternative approach to ensure a unique solution in three-phase state estimation. This method aims to accurately and uniquely estimate the state of any unbalanced three-phase system, irrespective of load imbalance, network configuration, existence of synchronous generators or transformers.

Power System State Estimation, Three-Phase, Distri↗
DOE OSTI2020

Resilient Distributed Field Estimation

We study resilient distributed field estimation under measurement attacks. A network of agents or devices measures a large, spatially distributed physical field parameter. An adversary arbitrarily manipulates the measurements of some of the agents. Each agent's goal is to process its measurements and information received from its neighbors to estimate only a few specific components of the field. Here, we present SAFE, the saturating adaptive field estimator, a consensus + innovations distributed field estimator that is resilient to measurement attacks. Under sufficient conditions on the compromised measurement streams, the physical coupling between the field and the agents' measurements, and the connectivity of the cyber communication network, SAFE guarantees that each agent's estimate converges almost surely to the true value of the components of the parameter in which the agent is interested. Finally, we illustrate the performance of SAFE through numerical examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

First-Principles Cost Estimation of a Sodium Fast Reactor Nuclear Plant

A multi-tiered cost analysis is performed to estimate full costs of a nuclear power plant (NPP) based on sodium-cooled fast reactor (SFR) technology. To address the lack of fully transparent cost estimations from past undertakings for NPPs, we have developed a detailed and first-principles-based cost estimate for a generalized SFR NPP. Our intent is to achieve a high degree of transparency with our cost assumptions and develop a cost model that is flexible and easily extendable to variations in NPP design and other nuclear reactor types. Furthermore, we strive to achieve a clear organization of costs and complete identification of key cost drivers based on first principles. To this end, the cost results of our analysis as given in Table 24 and Table 25 are organized and categorized into a code of accounts (COA) under development at Idaho National Laboratory (INL). Varying degrees of first-principles methods are employed, such as design for manufacture and assembly® (DFMA® ), to elucidate costs in all process levels of the plant equipment, buildings and site structures, personnel, and other miscellaneous but significant cost elements. These approaches have been successfully applied in past cost analysis projects and are designed to enable rapid and flexible cost estimation. Application of these techniques for evaluating NPP costs is similar in concept to the full, detailed estimation of construction and fabrication costs determined in a later stage of NPP development. Note that our approach tries to avoid use of other past analysis results and data such as those from the legacy Energy Economic Data Base (EEDB) Program, as these resources are based on historical NPP costs and thus may not be indicative of new reactor technologies or construction and fabrication/manufacturing techniques. However, we provide a comparison of our SFR NPP cost results in Table 90 against those included in the EEDB for a representative pressurized water reactor (PWR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Estimating the State of Charge in Lithium Primary Batteries: Recent Advances and Critical Insights

Lithium primary batteries (LPBs) remain essential in critical applications such as military, aerospace, medical and emergency devices, and portable electronics. Their superior energy density over lithium-ion batteries offers a significant advantage for long-duration use. Therefore, accurate estimation of the state of charge (SoC) is essential for ensuring the reliable and safe operation of these batteries. While extensive research has been conducted on SoC estimation techniques for lithium-ion secondary batteries, LPBs present unique challenges that complicate accurate SoC estimation. Moreover, research on nondestructive testing techniques for SoC estimation in LPBs is significantly lacking. In this review article, it is aimed to provide a comprehensive overview of recent advancements in SoC estimation for LPBs and generates new insights and directions for future research. Herein, existing methods are discussed and their effectiveness and mechanisms are identified, and areas for further optimization are outlined. More theoretical/experimental efforts to advance SoC detection in LPBs is recommended due to challenges identified with existing techniques.

25 ENERGY STORAGE↗