Insights and reviews on battery lifetime prediction from research to practice

The rising demand for energy storage solutions,especially in the electric vehicle and renewable energy sectors,highlights the importance of accurately predicting battery health to enhance their longevity and reliability.This article comprehensively examines various methods used to forecast battery health,including physics-based models,empirical models,and equivalent circuit models,among others.It delves into the promise of data-driven prognostics,utilizing both conventional machine learning and cuttingedge deep neural network techniques.The advantages and limitations of hybrid models are thoroughly analyzed,with a focus on the benefits of integrating diverse data sources to improve prognostic precision.Through practical case studies,the article showcases the effectiveness and flexibility of these approaches.It also critically addresses the challenges encountered in applying battery health prognostics in realworld scenarios,such as issues of scalability,complexity,and data anomalies.Despite these challenges,the article underscores the emerging opportunities brought about by recent technological,academic,and research advancements.These include the development of digital twin models for batteries,the use of data-centric AI and standardized benchmarking,the potential integration of blockchain technology for enhanced data security and transparency,and the synergy between edge and cloud computing to boost data analysis and processing.The primary goal of this article is to enrich the understanding of current battery health prognostic techniques and to inspire further research aimed at overcoming existing hurdles and tapping into new opportunities.It concludes with a visionary perspective on future research directions and potential developments in this evolving field,encouraging both researchers and practitioners to explore innovative solutions.

Omni-Channel Retailing and Firm Performance from a Customer Lifetime Value Perspective

In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.

Gross Alpha and Beta Activities and Related Lifetime Risks Assessment Due to Ingestion of Drinking Water from Different Sources in the District of Abidjan, Cote d’Ivoire

Drinking good quality water is essential for better health. It is therefore essential to assess the radiological quality of all water consumed in the District of Abidjan in order to prevent related hazards. Thus, the objective of this study was to assess the risk of cancer due to the ingestion of alpha and beta emitting radionuclides in the different types of water consumed in the region. A total of 63 water samples with 43 tap water samples, 5 bottled mineral water and 15 sachet water samples was collected and taken to GAEC laboratory for analysis. The low background Gas-less Automatic Alpha/Beta counting system (Canberra iMaticTM) was used to determine alpha and beta activity concentrations. Activity concentrations of both gross alpha and gross beta obtained in water sample were respectively lower than the WHO recommended limits of 0.1 Bq/l and 1 Bq/l. Also, the annual effective dose and total equivalent effective dose found in mineral bottled water samples were higher than in other types of water. The assessment of radiological lifetime risk has shown values of cancer risk due to ingestion alpha and beta emitters lower than recommended limit. These results indicate that there is no health hazard associated to consumption of water in the District of Abidjan.

Topology Driven Cooperative Self Scheduling for Improved Lifetime Maximization in WSN

In Wireless Sensor Network(WSN),scheduling is one of the important issues that impacts the lifetime of entire WSN.Various scheduling schemes have been proposed earlier to increase the lifetime of the network.Still,the results from such methods are compromised in terms of achieving high lifetime.With this objective to increase the lifetime of network,an Efficient Topology driven Cooperative Self-Scheduling(TDCSS)model is recommended in this study.Instead of scheduling the network nodes in a centralized manner,a combined approach is proposed.Based on the situation,the proposed TDCSS approach performs scheduling in both the ways.By sharing the node statistics in a periodic manner,the overhead during the transmission of control packets gets reduced.This in turn impacts the lifetime of all the nodes.Further,this also reduces the number of idle conditions of each sensor node which is required for every cycle.The proposed method enables every sensor to schedule its own conditions according to duty cycle and topology constraints.Central scheduler monitors the network conditions whereas total transmissions occurs at every cycle.According to this,the source can infer the possible routes in a cycle and approximate the available routes.Further,based on the statistics of previous transmissions,the routes towards the sink are identified.Among the routes found,a single optimal route with energy efficiency is selected to perform data transmission.This cooperative approach improves the lifetime of entire network with high throughput performance.

Exciton radiative lifetime in CdSe quantum dots

Colloidal CdSe quantum dots(QDs)are promising materials for solar cells because of their simple preparation pro-cess and compatibility with flexible substrates.The QD radiative recombination lifetime has attracted enormous attention as it affects the probability of photogenerated charges leaving the QDs and being collected at the battery electrodes.However,the scaling law for the exciton radiative lifetime in CdSe QDs is still a puzzle.This article presents a novel explanation that recon-ciles this controversy.Our calculations agree with the experimental measurements of all three divergent trends in a broadened energy window.Further,we proved that the exciton radiative lifetime is a consequence of the thermal average of decays for all thermally accessible exciton states.Each of the contradictory size-dependent patterns reflects this trend in a specific size range.As the optical band gap increases,the radiative lifetime decreases in larger QDs,increases in smaller QDs,and is weakly depend-ent on size in the intermediate energy region.This study addresses the inconsistencies in the scaling law of the exciton life-time and gives a unified interpretation over a widened framework.Moreover,it provides valuable guidance for carrier separa-tion in the thin film solar cell of CdSe QDs.

Fully relativistic many-body perturbation energies,transition properties,and lifetimes of lithium-like iron Fe XXIV

Employing the advanced relativistic configuration interaction(RCI)combined with the many-body perturbation theory(RMBPT)method,we report energies and lifetime values for the lowest 35 energy levels from the(1s^(2))nl configurations(where the principal quantum number n=2–6 and the angular quantum number l=0,...,n-1)of lithium-like iron Fe XXIV,as well as complete data on the transition wavelengths,radiative rates,absorption oscillator strengths,and line strengths between the levels.Both the allowed(E1)and forbidden(magnetic dipole M1,magnetic quadrupole M2,and electric quadrupole E2)ones are reported.Through detailed comparisons with previous results,we assess the overall accuracies of present RMBPT results to be likely the most precise ones to date.Configuration interaction effects are found to be very important for the energies and radiative properties for the ion.The present RMBPT results are valuable for spectral line identification,plasma modeling,and diagnosing.

Lifetime measurement of the 3d^(9) ^(2)D_(3/2) metastable level in Mo^(15+)at an electron beam ion trap

An experimental measurement of the lifetime of 3d^(9) ^(2)D_(3/2) metastable level in Mo^(15+)is reported in this work.The Mo^(15+)ions are produced and trapped in an electron beam ion trap with a magnetic field of 0.65 T.The decay photons emitted from 3d^(9) ^(2)D_(3/2) level are subsequently recorded via a cooled photomultiplier tube.Through meticulous scrutiny of potential systematic uncertainties affecting the measurement outcomes,we have determined the lifetime of Mo^(15+)3d^(9)2D_(3/2)metastable level to be 2.83(22)ms.The experimental result provides a clear distinguishment from existing calculations based on various theoretical approaches.

Impacts of hydrogen annealing on the carrier lifetimes in p-type 4H-SiC after thermal oxidation

Thermal oxidation and hydrogen annealing were applied on a 100μm thick Al-doped p-type 4H-Si C epitaxial wafer to modulate the minority carrier lifetime,which was investigated by microwave photoconductive decay(μ-PCD).The minority carrier lifetime decreased after each thermal oxidation.On the contrary,with the hydrogen annealing time increasing to3 hours,the minority carrier lifetime increased from 1.1μs(as-grown)to 3.14μs and then saturated after the annealing time reached 4 hours.The increase of surface roughness from 0.236 nm to 0.316 nm may also be one of the reasons for limiting the further improvement of the minority carrier lifetimes.Moreover,the whole wafer mappings of minority carrier lifetimes before and after hydrogen annealing were measured and discussed.The average minority carrier lifetime was up to 1.94μs and non-uniformity of carrier lifetime reached 38%after 4-hour hydrogen annealing.The increasing minority carrier lifetimes could be attributed to the double mechanisms of excess carbon atoms diffusion caused by selective etching of Si atoms and passivation of deep-level defects by hydrogen atoms.

Room-Temperature Phosphorescence and Lifetime of Fossil Resins (Amber) from Dominican Republic, Mexico, Baltic Sea, Myanmar, and Fushun, China

Amber can emit room temperature phosphorescence(RTP)under the well-known 365 nm fluorescence ultraviolet light.This paper is devoted to the phosphorescence study of 20 pieces of amber materials from the Dominican Republic,Mexico,Baltic sea,Myanmar,and Fushun,China.The results show that amber from the same geographic origin has similar shape in phosphorescence spectra.However,the shape of the amber phosphorescence spectra varies depending on their different localities.Burmite(amber from Myanmar)and Fushun amber have a bright yellow phosphorescence with a long lifetime,while the Dominican and Mexican ones are weaker and last shorter.The irradiation of Baltic amber becomes faint or even inert.Phosphorescence spectral Gaussian fitting results suggest an emission maximum near 550 nm in most amber samples.Their phosphorescence lifetime,analyzed through the exponential function fitting,is up to 1 second in Burmite and Fushun samples,shorter in the Dominican and Mexican ones,about 0.230 s,and the shortest in Baltic amber,close to 0.151 s.These variations of phosphorescence lifetime and intensity are related to the relative geological ages of these amber.It indicated that the phosphorescence agent was probably formed during the long geological time.While the anomaly occurred in Baltic amber,the only one found in a sea secondary deposit form,it demonstrated that the terrestrial geological environment these amber preserved has prevented the phosphorescence agent to be deactivated.

Outdoor Air Quality Monitoring with Enhanced Lifetime-enhancing Cooperative Data Gathering and Relaying Algorithm (E-LCDGRA) Based Sensor Network

The air continues to be an extremely substantial part of survival on earth.Air pollution poses a critical risk to humans and the environment.Using sensor-based structures,we can get air pollutant data in real-time.However,the sensors rely upon limited-battery sources that are immaterial to be alternated repeatedly amid extensive broadcast costs associated with real-time applications like air quality monitoring.Consequently,air quality sensor-based monitoring structures are lifetime-constrained and prone to the untimely loss of connectivity.Effective energy administration measures must therefore be implemented to handle the outlay of power dissipation.In this study,the authors propose outdoor air quality monitoring using a sensor network with an enhanced lifetime-enhancing cooperative data gathering and relaying algorithm(E-LCDGRA).LCDGRA is a cluster-based cooperative event-driven routing scheme with dedicated relay allocation mechanisms that tackle the problems of event-driven clustered WSNs with immobile gateways.The adapted variant,named E-LCDGRA,enhances the LCDGRA algorithm by incorporating a non-beacon-aided CSMA layer-2 un-slotted protocol with a back-off mechanism.The performance of the proposed E-LCDGRA is examined with other classical gathering schemes,including IEESEP and CERP,in terms of average lifetime,energy consumption,and delay.

Applications,of fluorescence lifetime imaging in clinical medicine

Fluorescence lifetime is not only associated with the molecular structure f fuorophores,but alsostrongly depends on the environment around them,which llows fuorescence lifetime imagingmicroscopy(FLIM)to be used as a tool for precise measurement of the cell or tisue microenvironment,This review introduces the basic principle of fuorescence lifetime imagingtechnology and its application in clinical medicine,including research and diagnosis of diseases inskin,brain,eyes,mouth,bone,blood vessels and cavity organs,and drug evaluation.As anoninvasive,nontoxic and nonionizing radiation technique,FLIM demonstrates excellent per-formance with high sensitivity and specificity,which allows to determine precise position of thelesion and,thus,has good potential for application in biomedical research and clinical diagnosis.

Fluid-structure Interaction Analysis and Lifetime Estimation of a Natural Gas Pipeline Centrifugal Compressor under Near-choke and Near-surge Conditions

Up to present, there have been no studies concerning the application of fluid-structure interaction（FSI） analysis to the lifetime estimation of multi-stage centrifugal compressors under dangerous unsteady aerodynamic excitations. In this paper, computational fluid dynamics（CFD） simulations of a three-stage natural gas pipeline centrifugal compressor are performed under near-choke and near-surge conditions, and the unsteady aerodynamic pressure acting on impeller blades are obtained. Then computational structural dynamics（CSD） analysis is conducted through a one-way coupling FSI model to predict alternating stresses in impeller blades. Finally, the compressor lifetime is estimated using the nominal stress approach. The FSI results show that the impellers of latter stages suffer larger fluctuation stresses but smaller mean stresses than those at preceding stages under near-choke and near-surge conditions. The most dangerous position in the compressor is found to be located near the leading edge of the last-stage impeller blade. Compressor lifetime estimation shows that the investigated compressor can run up to 102.7 h under the near-choke condition and 200.2 h under the near-surge condition. This study is expected to provide a scientific guidance for the operation safety of natural gas pipeline centrifugal compressors.

Probabilistic Lifetime Assessment of Marine Reinforced Concrete with Steel Corrosion and Cover Cracking

In order to study the durability behavior of marine reinforced concrete structure suffering from chloride attack, the structural service life is assumed to be divided into three critical stages, which can be characterized by steel corrosion and cover cracking. For each stage, a calculated model used to predict the lifetime is developed. Based on the definition of durability limit state, a probabilistic lifetime model and its time-dependent reliability analytical method are proposed considering the random natures of influencing factors. Then, the probabilistic lifetime prediction models are applied to a bridge pier located in the Hangzhou Bay with Monte Carlo simulation. It is found that the time to corrosion initiation to follows a lognormal distribution, while that the time from corrosion initiation to cover cracking t~ and the time for crack to develop from hairline crack to a limit crack width t2 can be described by Weibull distributions. With the permitted failure probability of 5.0%, it is also observed that the structural durability lifetime mainly depends on the durability life to and that the percentage of participation of the life to to the total service life grows from 61.5% to 83.6% when the cover thickness increases from 40 mm to 80 mm. Therefore, for any part of the marine RC bridge, the lifetime predictions and maintenance efforts should also be directed toward controlling the stage of corrosion initiation induced by chloride ion.

Residual lifetime prediction model of nonlinear accelerated degradation data with measurement error

For the product degradation process with random effect (RE), measurement error (ME) and nonlinearity in step-stress accelerated degradation test (SSADT), the nonlinear Wiener based degradation model with RE and ME is built. An analytical approximation to the probability density function (PDF) of the product's lifetime is derived in a closed form. The process and data of SSADT are analyzed to obtain the relation model of the observed data under each accelerated stress. The likelihood function for the population-based observed data is constructed. The population-based model parameters and its random coefficient prior values are estimated. According to the newly observed data of the target product in SSADT, an analytical approximation to the PDF of its residual lifetime (RL) is derived in accordance with its individual degradation characteristics. The parameter updating method based on Bayesian inference is applied to obtain the posterior value of random coefficient of the RL model. A numerical example by simulation is analyzed to verify the accuracy and advantage of the proposed model.

Room-temperature continuous-wave operation of GaN-based blue-violet laser diodes with a lifetime longer than 1000h

GaN-based continuous-wave operated blue-violet laser diodes(LDs) with long lifetime are demonstrated, which are grown on a c-plane GaN substrate by metal organic chemical vapor deposition with a 10 × 600 μm^2 ridge waveguide structure.The electrical and optical characteristics of a blue-violet LD are investigated under direct-current injection at room temperature(25 °C). The stimulated emission wavelength and peak optical power of the LD are around 413 nm and over 600 mW, respectively.In addition, the threshold current density and voltage are as small as 1.46 kA/cm^2 and 4.1 V, respectively. Moreover, the lifetime is longer than 1000 hours under room-temperature continuous-wave operation.

The Application of Neural Network in Lifetime Prediction of Concrete

There are many difficulties in concrete endurance prediction, especially in accurate predicting service life of concrete engineering. It is determined by the concentration of S042-/ Mg2+ / Cl- /Ca2+ , reactionareas , the cycles of freezing and dissolving, alternatives of dry and wet state, the kind of cement, etc. . In general , because of complexity itself and cognitive limitation, endurance prediction under sulphate erosion is still illegible and uncertain, so this paper adopts neural network technology to research this problem. Through analyzing , the paper sets up a 3 - levels neural network and a 4 - levels neural network to predict the endurance undersulphate erosion. The 3 - levels neural network includes 13 inputting nodes, 7 outputting nodes and 34 hidden nodes. The 4 - levels neural network also has 13 inputting nodes and 7 outputting nodes with two hidden levels which has 1 nodes and 8 nodes separately. In the end the paper give a example with laboratorial data and discussion the result and deviation. The paper shows that deviation results from some faults of training specimens; such as few training specimens and few distinctions among training specimens. So the more specimens should be collected to reduce data redundancy and improve the reliability of network analysis conclusion.

Lifetime Prolonging Algorithms for Underwater Sensor Networks

Underwater acoustic modem technology has attained a level of maturity to support underwater acoustic sensor networks （UASNs） which are generally formed by acoustically connected sensor nodes and a surface station providing a link to an on-shore control center. While many applications require long-term monitoring of the deployment area, the batterypowered network nodes limit the lifetime of UASNs. Therefore, designing a UASN that minimizes the power consumption while maximizing lifetime becomes a very difficult task. In this paper, a method is proposed to determine the optimum number of clnstens throngh combining an application-specific protocol architecture and underwater acoustic communication model so as to reduce the energy dissipation of UASNs. Deploying more sensor nodes which work alternately is another way to prolong the lifetime of UASNs, An algorithm is presented for selecting sensor nodes and putting them into operation in each round, ensuring the monitoring to the whole given area. The present results show that the algorithm can help prolong system lifetime remarkably when it is applied to other conventional approaches for sensor networks under the condition that the sensor node density is high.

Lifetime and Aging Degradation Prognostics for Lithium-ion Battery Packs Based on a Cell to Pack Method

Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region.This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination of transferred deep learning and Gaussian process regression.General health indicators are extracted from the partial discharge process.The sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation prediction.The future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a comprehensive lifetime prognostic.Besides,only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model construction.Experimental results show that the lifetime prediction errors are less than 25 cycles for the battery pack,even with only 50 cycles for model fine-tuning,which can save about 90%time for the aging experiment.Thus,it largely reduces the time and labor for battery pack investigation.The predicted capacity trends of the battery cells connected in the battery pack accurately reflect the actual degradation of each battery cell,which can reveal the weakest cell for maintenance in advance.

Analysis of Numerical Simulation Results of LIPS-200 Lifetime Experiments

Accelerator grid structural and electron backstreaming failures are the most important factors affecting the ion thruster＇s lifetime.During the thruster＇s operation,Charge Exchange Xenon（CEX） ions are generated from collisions between plasma and neutral atoms.Those CEX ions grid＇s barrel and wall frequently,which cause the failures of the grid system.In order to validate whether the 20 cm Lanzhou Ion Propulsion System（LIPS-200） satisfies China＇s communication satellite platform＇s application requirement for North-South Station Keeping（NSSK）,this study analyzed the measured depth of the pit/groove on the accelerator grid＇s wall and aperture diameter＇s variation and estimated the operating lifetime of the ion thruster.Different from the previous method,in this paper,the experimental results after the 5500 h of accumulated operation of the LIPS-200 ion thruster are presented firstly.Then,based on these results,theoretical analysis and numerical calculations were firstly performed to predict the on-orbit lifetime of LIPS-200.The results obtained were more accurate to calculate the reliability and analyze the failure modes of the ion thruster.The results indicated that the predicted lifetime of LIPS-200＇s was about 13218.1 h which could satisfy the required lifetime requirement of 11000 h very well.

Study of the key factors affecting the triple grid lifetime of the LIPS-300 ion thruster

In order to ascertain the key factors affecting the lifetime of the triple grids in the LIPS-300 ion thruster,the thermal deformation,upstream ion density and component lifetime of the grids are simulated with finite element analysis,fluid simulation and charged-particle tracing simulation methods on the basis of a 1500 h short lifetime test.The key factor affecting the lifetime of the triple grids in the LIPS-300 ion thruster is obtained and analyzed through the test results.The results show that ion sputtering erosion of the grids in 5 kW operation mode is greater than in the case of 3 kW.In 5 kW mode,the decelerator grid shows the most serious corrosion,the accelerator grid shows moderate corrosion,and the screen grid shows the least amount of corrosion.With the serious corrosion of the grids in 5 kW operation mode,the intercept current of the acceleration and deceleration grids increases substantially.Meanwhile,the cold gap between the accelerator grid and the screen grid decreases from 1 mm to 0.7 mm,while the cold gap between the accelerator grid and the decelerator grid increases from 1 mm to 1.25 mm after 1500 h of thruster operation.At equilibrium temperature with 5 k W power,the finite element method（FEM）simulation results show that the hot gap between the screen grid and the accelerator grid reduces to 0.2 mm.Accordingly,the hot gap between the accelerator grid and the decelerator grid increases to 1.5 mm.According to the fluid method,the plasma density simulated in most regions of the discharge chamber is 1?×?10;-8?×?10;m;.The upstream plasma density of the screen grid is in the range 6?×?10;-6?×?10;m;and displays a parabolic characteristic.The charged particle tracing simulation method results show that the ion beam current without the thermal deformation of triple grids has optimal perveance status.The ion sputtering rates of the accelerator grid hole and the decelerator hole are 5.5?×?10;kg s;and 4.28?×?10;kg s;,respectively,while after the thermal deformation of the triple grids,the ion beam current has over-perveance status.The ion sputtering rates of the accelerator grid hole and the decelerator hole are 1.41?×?10;kg s;and 4.1?×?10;kg s;,respectively.The anode current is a key factor for the triple grid lifetime in situations where the structural strength of the grids does not change with temperature variation.The average sputtering rates of the accelerator grid and the decelerator grid,which were measured during the 1500 h lifetime test in5 k W operating conditions,are 2.2?×?10;kg s;and 7.3?×?10;kg s;,respectively.These results are in accordance with the simulation,and the error comes mainly from the calculation distribution of the upstream plasma density of the grids.