Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

三维重建脾脏体积客观评估ICG

背景:肝切除是治疗肝癌的关键手段。术前评估肝功能储备则是肝切除的必经之路。吲哚菁绿(ICG)清除率试验是肝切除术前评估肝脏储备功能的主要方法,但由于部分患者有不良反应,给临床工作带来了避免不了的麻烦;脾脏体积与肝硬化病人的肝切除有着密切关系,那么,脾脏体积与ICG是否也有着某种联系?方法:我们回顾性分析300例肝硬化行肝切除的患者,探讨影响肝储备功能的危险因素,通过SPSS逻辑回归建立模型,并用ROC检验其模型准确性。结果:通过脾脏体积、白蛋白、总胆红素、年龄构建出逻辑回归模型,得出脾脏体积是ICG的独立危险因素,并进一步通过ROC得出模型的AUC为0.877,敏感度为84%,特异度为80%。结论:通过三维重建脾脏体积求得ICG 15分钟滞留率(ICG-R15),更好地服务于临床医生,从而评估术前肝储备功能,进而决定是否可行手术治疗。

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Novel method for identifying the stages of discharge underwater based on impedance change characteristic

It is difficult to determine the discharge stages in a fixed time of repetitive discharge underwater due to the arc formation process being susceptible to external environmental influences. This paper proposes a novel underwater discharge stage identification method based on the Strong Tracking Filter(STF) and impedance change characteristics. The time-varying equivalent circuit model of the discharge underwater is established based on the plasma theory analysis of the impedance change characteristics and mechanism of the discharge process. The STF is used to reduce the randomness of the impedance of repeated discharges underwater, and then the universal identification resistance data is obtained. Based on the resistance variation characteristics of the discriminating resistance of the pre-breakdown, main, and oscillatory discharge stages, the threshold values for determining the discharge stage are obtained. These include the threshold values for the resistance variation rate(K) and the moment(t).Experimental and error analysis results demonstrate the efficacy of this innovative method in discharge stage determination, with a maximum mean square deviation of Scrless than 1.761.

Mean nocturnal baseline impedance in gastro-esophageal reflux disease diagnosis:Should we strictly follow the Lyon 2 Consensus?

Clinical practice guidelines drive clinical practice and clinicians rely to them when trying to answer their most common questions.One of the most important position papers in the field of gastro-esophageal reflux disease(GERD)is the one produced by the Lyon Consensus.Recently an updated second version has been released.Mean nocturnal baseline impedance(MNBI)was proposed by the first Consensus to act as supportive evidence for GERD diagnosis.Originally a cut-off of 2292 Ohms was proposed,a value revised in the second edition.The updated Consensus recommended that an MNBI<1500 Ohms strongly suggests GERD while a value>2500 Ohms can be used to refute GERD.The proposed cut-offs move in the correct direction by diminishing the original cut-off,nevertheless they arise from a study of normal subjects where cut-offs were provided by measuring the mean value±2SD and not in symptomatic patients.However,data exist that even symptomatic patients with inconclusive disease or reflux hypersensitivity(RH)show lower MNBI values in comparison to normal subjects or patients with functional heartburn(FH).Moreover,according to the data,MNBI,even among symptomatic patients,is affected by age and body mass index.Also,various studies have proposed different cut-offs by using receiver operating characteristic curve analysis even lower than the one proposed.Finally,no information is given for patients submitted to on-proton pump inhibitors pH-impedance studies even if new and extremely important data now exist.Therefore,even if MNBI is an extremely important tool when trying to approach patients with reflux symptoms and could distinguish conclusive GERD from RH or FH,its values should be interpreted with caution.

Solid-state impedance spectroscopy studies of dielectric properties and relaxation processes in Na_(2)O–V_(2)O_(5)–Nb_(2)O_(5)–P_(2)O_(5) glass

Solid-state impedance spectroscopy(SS-IS)was used to investigate the influence of structural modifications resulting from the addition of Nb2O5 on the dielectric properties and relaxation processes in the quaternary mixed glass former(MGF)system 35Na_(2)O–10V_(2)O_(5)–(55-x)P_(2)O_(5)–xNb_(2)O_(5)(x=0–40,mol%).The dielectric parameters,including the dielectric strength and dielectric loss,are determined from the frequency and temperature-dependent complex permittivity data,revealing a significant dependence on the Nb2O5 content.The transition from a predominantly phosphate glass network(x<10,region I)to a mixed niobate–phosphate glass net-work(10≤x≤20,region II)leads to an increase in the dielectric parameters,which correlates with the observed trend in the direct-cur-rent(DC)conductivity.In the predominantly niobate network(x≥25,region III),the highly polarizable nature of Nb5+ions leads to a fur-ther increase in the dielectric permittivity and dielectric strength.This is particularly evident in Nb-40 glass-ceramic,which contains Na_(13)Nb_(35)O_(94) crystalline phase with a tungsten bronze structure and exhibits the highest dielectric permittivity of 61.81 and the lowest loss factor of 0.032 at 303 K and 10 kHz.The relaxation studies,analyzed through modulus formalism and complex impedance data,show that DC conductivity and relaxation processes are governed by the same mechanism,attributed to ionic conductivity.In contrast to glasses with a single peak in frequency dependence of imaginary part of electrical modulus,M″(ω),Nb-40 glass-ceramic exhibits two distinct contributions with similar relaxation times.The high-frequency peak indicates bulk ionic conductivity,while the additional low-fre-quency peak is associated with the grain boundary effect,confirmed by the electrical equivalent circuit(EEC)modelling.The scaling characteristics of permittivity and conductivity spectra,along with the electrical modulus,validate time-temperature superposition and demonstrate a strong correlation with composition and modification of the glass structure upon Nb_(2)O_(5) incorporation.

Statistical Inversion Based on Nonlinear Weighted Anisotropic Total Variational Model and Its Application in Electrical Impedance Tomography

Electrical impedance tomography (EIT) aims to reconstruct the conductivity distribution using the boundary measured voltage potential. Traditional regularization based method would suffer from error propagation due to the iteration process. The statistical inverse problem method uses statistical inference to estimate unknown parameters. In this article, we develop a nonlinear weighted anisotropic total variation (NWATV) prior density function based on the recently proposed NWATV regularization method. We calculate the corresponding posterior density function, i.e., the solution of the EIT inverse problem in the statistical sense, via a modified Markov chain Monte Carlo (MCMC) sampling. We do numerical experiment to validate the proposed approach.

ICG荧光显像+亚甲蓝染色法对乳腺癌前哨淋巴结检出率的影响

目的:观察乳腺癌前哨淋巴结检查中,用吲哚菁绿(ICG)荧光显像+亚甲蓝染色法对检出率产生的影响。方法:随机入选我院收治于2019年8月10日—2020年12月30日102例乳腺癌患者为观察对象,51例行ICG荧光显像、亚甲蓝染色法检测,51例行亚甲蓝染色法检测,以手术病理结果为“金标准”,观察不同方法乳腺癌前哨淋巴结检出率、诊断乳腺癌前哨淋巴结效能。结果:(1)乳腺癌前哨淋巴结检出率:“金标准”显示102例患者中存在前哨淋巴结患者38例,共计淋巴结96处。ICG荧光显像+亚甲蓝染色法联合检出率高于亚甲蓝染色法单一检出率,差异有统计学意义(P<0.05)。(2)乳腺癌前哨淋巴结诊断效能:ICG荧光显像+亚甲蓝染色法联合方法特异度、阳性预测值、诊断符合率明显高于单一方法,且误诊率低于单一方法,差异有统计学意义(P<0.05);联合方法与单一方法在灵敏度、阴性预测值、漏诊率上无统计学差异(P>0.05)。ICG荧光显像+亚甲蓝染色法联合方法Youden指数高于单一方法。结论:ICG荧光显像+亚甲蓝染色法对乳腺癌前哨淋巴结检出率较高,采用联合方法诊断乳腺癌前哨淋巴准确性高,可推广应用。

Semi-supervised estimation of capacity degradation for lithium ion batteries with electrochemical impedance spectroscopy

Machine learning-based methods have emerged as a promising solution to accurate battery capacity estimation for battery management systems.However,they are generally developed in a supervised manner which requires a considerable number of input features and corresponding capacities,leading to prohibitive costs and efforts for data collection.In response to this issue,this study proposes a convolutional neural network(CNN)based method to perform end-to-end capacity estimation by taking only raw impedance spectra as input.More importantly,an input reconstruction module is devised to effectively exploit impedance spectra without corresponding capacities in the training process,thereby significantly alleviating the cost of collecting training data.Two large battery degradation datasets encompassing over 4700 impedance spectra are developed to validate the proposed method.The results show that accurate capacity estimation can be achieved when substantial training samples with measured capacities are given.However,the estimation performance of supervised machine learning algorithms sharply deteriorates when fewer samples with measured capacities are available.In this case,the proposed method outperforms supervised benchmarks and can reduce the root mean square error by up to 50.66%.A further validation under different current rates and states of charge confirms the effectiveness of the proposed method.Our method provides a flexible approach to take advantage of unlabelled samples for developing data-driven models and is promising to be generalised to other battery management tasks.

Vertical impedance functions of pile groups under low-to-high loading amplitudes:numerical simulations and experimental validation

Piles in a group experience additional displacements in soil due to pile-to-pile interactions apart from those resulting from the external loading.The effect of these interactions determined assuming soil as an elastic and/or viscoelastic material on pile head impedance functions of the pile group is studied by relating the group stiffness to the static stiffness of a single pile.However,the prevailing elastic solutions may misestimate the resulting pile group response due to the lack of consideration for either soil(material)and/or soil-pile interface nonlinearities.It is well established that soil behaves nonlinearly under moderate-to-high loading amplitudes,and besides,the soil-pile interface nonlinearity can exist even at small loading amplitudes.This study addresses the effects of these nonlinearities on the vertical impedance functions of a 3×3-pile group using numerical methods by direct analyses and superposition using pile-to-pile interaction factors.The numerical results are validated using scaled model tests under 1 g conditions.The results highlight the overestimation of pile-to-pile interactions in the pile group when assuming elastic soil conditions.The cases either by direct analyses or superposition approach involving soil and soil-pile interface nonlinearities agree well with the experimental pile group responses under close-to-elastic and nonlinear conditions.

Stress wave analysis of high-voltage pulse discharge rock fragmentation based on plasma channel impedance model

High-voltage pulse discharge(HVPD)rock fragmentation controls a plasma channel forming inside the rock by adjusting the electrical parameters,electrode type,etc.In this work,an HVPD rock fragmentation test platform was built and the test waveforms were measured.Considering the effects of temperature,channel expansion and electromagnetic radiation,the impedance model of the plasma channel in the rock was established.The parameters and initial values of the model were determined by an iterative computational process.The model calculation results can reasonably characterize the development of the plasma channel in the rock and estimate the shock wave characteristics.Based on the plasma channel impedance model,the temporal and spatial distribution characteristics of the radial stress and tangential stress in the rock were calculated,and the rock fragmentation effect of the HVPD was analyzed.

High impedance fault detection in distribution network based on S-transform and average singular entropy

When a high impedance fault(HIF)occurs in a distribution network,the detection efficiency of traditional protection devices is strongly limited by the weak fault information.In this study,a method based on S-transform(ST)and average singular entropy(ASE)is proposed to identify HIFs.First,a wavelet packet transform(WPT)was applied to extract the feature frequency band.Thereafter,the ST was investigated in each half cycle.Afterwards,the obtained time-frequency matrix was denoised by singular value decomposition(SVD),followed by the calculation of the ASE index.Finally,an appropriate threshold was selected to detect the HIFs.The advantages of this method are the ability of fine band division,adaptive time-frequency transformation,and quantitative expression of signal complexity.The performance of the proposed method was verified by simulated and field data,and further analysis revealed that it could still achieve good results under different conditions.

基于CEEMDAN的ICG信号预处理与特征识别方法研究

提出一种基于自适应噪声完备集合经验模态分解(CEEMDAN)结合差分、阈值迭代处理和信号分段对心阻抗血流图(ICG)信号进行预处理和多个特征点的识别方法。首先对ICG信号做CEEMDAN分解,获取多个模态函数分量(IMF),根据ICG存在的高频与低频噪声频率,利用相关系数法去除干扰噪声,再对去除噪声后的ICG信号进行差分与分段,寻找特征点B、C、X,并对通过临床采集的20名志愿者的信号进行以上处理,对该算法准确性进行评估。最终结果表明该方法对特征点的定位准确率达到95.8%,特征定位效果较好。

Human-Robot Collaboration Framework Based on Impedance Control in Robotic Assembly

Human–robot(HR)collaboration(HRC)is an emerging research field because of the complementary advantages of humans and robots.An HRC framework for robotic assembly based on impedance control is proposed in this paper.In the HRC framework,the human is the decision maker,the robot acts as the executor,while the assembly environment provides constraints.The robot is the main executor to perform the assembly action,which has the position control,drag and drop,positive impedance control,and negative impedance control modes.To reveal the characteristics of the HRC framework,the switch condition map of different control modes and the stability analysis of the HR coupled system are discussed.In the end,HRC assembly experiments are conducted,where the HRC assembly task can be accomplished when the assembling tolerance is 0.08 mm or with the interference fit.Experiments show that the HRC assembly has the complementary advantages of humans and robots and is efficient in finishing complex assembly tasks.

Early Debonding Detection of Rebar-Concrete Interface due to External Loading Utilizing AC Impedance Spectroscopy

A novel method for detecting early damage at the steel-concrete interface due to external loading based on AC impedance spectroscopy technology was proposed.Firstly,alkali pretreatment was introduced to ensure the accuracy and repeatability of the AC impedance test.Secondly,the AC impedance spectroscopy between the steel bar and concrete surface of different bonding positions was tested,and then the physical quantities reflecting the bonding damage condition were obtained by equivalent circuit fitting.Theoretical debonding position calculation and AC conductive structure analysis indicate that the change of interface resistance and interface capacitance can seize the development of bonding damage during the loading process.As the interface damage develops,obvious changes in interface resistance and interface capacitance are observed,and they cannot be recovered after unloading.

Battery impedance spectrum prediction from partial charging voltage curve by machine learning

Electrochemical impedance spectroscopy(EIS) is an effective technique for Lithium-ion battery state of health diagnosis, and the impedance spectrum prediction by battery charging curve is expected to enable battery impedance testing during vehicle operation. However, the mechanistic relationship between charging curves and impedance spectrum remains unclear, which hinders the development as well as optimization of EIS-based prediction techniques. In this paper, we predicted the impedance spectrum by the battery charging voltage curve and optimized the input based on electrochemical mechanistic analysis and machine learning. The internal electrochemical relationships between the charging curve,incremental capacity curve, and the impedance spectrum are explored, which improves the physical interpretability for this prediction and helps define the proper partial voltage range for the input for machine learning models. Different machine learning algorithms have been adopted for the verification of the proposed framework based on the sequence-to-sequence predictions. In addition, the predictions with different partial voltage ranges, at different state of charge, and with different training data ratio are evaluated to prove the proposed method have high generalization and robustness. The experimental results show that the proper partial voltage range has high accuracy and converges to the findings of the electrochemical analysis. The predicted errors for impedance spectrum are less than 1.9 mΩ with the proper partial voltage range selected by the corelative analysis of the electrochemical reactions inside the batteries. Even with the voltage range reduced to 3.65–3.75 V, the predictions are still reliable with most RMSEs less than 4 mO.

Understanding Lithium-ion Transport in Sulfolane- and Tetraglyme-Based Electrolytes Using Very Low-Frequency Impedance Spectroscopy

With the increasing interest in highly concentrated electrolyte systems,correct determination of the cation transference number is important.Pulsed-field gradient NMR technique,which measures self-diffusion coefficients,is often applied on liquid electrolytes because of the wide accessibility and simple sample preparation.However,since the assumptions of this technique,that is,complete salt dissociation,all ions participating in motion,and all of them moving independently,no longer hold true in concentrated solutions,the transference numbers,thus obtained are often over-estimated.In the present work,impedance spectroscopy at a frequency range of 1 MHz to 0.1 mHz was used to examine the concentration effect on lithium-ion transference number under anion-blocking conditions T abc Liþfor two electrolytes:lithium bis(fluorosulfonyl)imide(LiFSI)in sulfolane(SL)and lithium bis(trifluorosulfonyl)imide(LiTFSI)in tetraglyme(G4).The T abc Liþof the former was almost an order of magnitude higher than that of the latter.It also appeared to increase with increasing concentration while the latter followed an opposite trend.The faster Li^(+)transport in the SL system is attributed to the formation of a liquid structure consisting of extended chains/bridges of SL molecules and the anions,which facilitate a cation-hopping/ligand-exchanged-typed diffusion mechanism by partially decoupling the cations from the anions and solvent molecules.The G4 system,in contrast,is dominated by the formation of long-lived,stable[Li(G4)]+solvation cages that results in a sluggish Li+transport.The difference between the two transport mechanisms is discussed via comparison of the bulk ionic conductivity,viscosity,ion self-diffusion coefficients,and the Onsager transport coefficients.

Study of the axial density/impedance gradient composite long rod hypervelocity penetration into a four-layer Q345 target

Based on the dynamic shock response of the material and structure,the hypervelocity impact processes and mechanisms of long composite rods with axial density/impedance gradients penetration into fourlayer targets were studied through experiments and numerical simulation methods.The propagation law of the shock waves,together with the structural responses of the projectiles and targets,the formation and evolution of the fragment groups formed during the processes and their distributions were described.The damage of each target plate was quantitatively analysed by comparing the results of the experiment and numerical simulation.The results showed that the axial density/impedance gradient projectiles could decrease the impact pressure to a certain extent,and the degree of damage to the target plate decreased layer by layer when the head density/impedance of the projectile was high.When the head density/impedance of the projectile was low,the degree of target damage first increased layer by layer until the projectile was completely eroded and then it decreased.The results can provide a reference for the design and application of long rods with axial composite structure for velocities ranging from 6 to 10 Ma or greater.

Impedance spectroscopy for quantum dot light-emitting diodes

Impedance spectroscopy has been increasingly employed in quantum dot light-emitting diodes(QLEDs)to investigate the charge dynamics and device physics.In this review,we introduce the mathematical basics of impedance spectroscopy that applied to QLEDs.In particular,we focus on the Nyquist plot,Mott-Schottky analysis,capacitance-frequency and capacitance-voltage characteristics,and the d C/d V measurement of the QLEDs.These impedance measurements can provide critical information on electrical parameters such as equivalent circuit models,characteristic time constants,charge injection and recombination points,and trap distribution of the QLEDs.However,this paper will also discuss the disadvantages and limitations of these measurements.Fundamentally,this review provides a deeper understanding of the device physics of QLEDs through the application of impedance spectroscopy,offering valuable insights into the analysis of performance loss and degradation mechanisms of QLEDs.

Model-constrained and data-driven double-supervision acoustic impedance inversion

Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geophysical inversion problem is essentially an ill-posedness problem,which means that there are many solutions corresponding to the same seismic data.Therefore,regularization schemes,which can provide stable and unique inversion results to some extent,have been introduced into the objective function as constrain terms.Among them,given a low-frequency initial impedance model is the most commonly used regularization method,which can provide a smooth and stable solution.However,this model-based inversion method relies heavily on the initial model and the inversion result is band limited to the effective frequency bandwidth of seismic data,which cannot effectively improve the seismic vertical resolution and is difficult to be applied to complex structural regions.Therefore,we propose a data-driven approach for high-resolution impedance inversion based on the bidirectional long short-term memory recurrent neural network,which regards seismic data as time-series rather than image-like patches.Compared with the model-based inversion method,the data-driven approach provides higher resolution inversion results,which demonstrates the effectiveness of the data-driven method for recovering the high-frequency components.However,judging from the inversion results for characterization the spatial distribution of thin-layer sands,the accuracy of high-frequency components is difficult to guarantee.Therefore,we add the model constraint to the objective function to overcome the shortages of relying only on the data-driven schemes.First,constructing the supervisor1 based on the bidirectional long short-term memory recurrent neural network,which provides the predicted impedance with higher resolution.Then,convolution constraint as supervisor2 is introduced into the objective function to guarantee the reliability and accuracy of the inversion results,which makes the synthetic seismic data obtained from the inversion result consistent with the input data.Finally,we test the proposed scheme based on the synthetic and field seismic data.Compared to model-based and purely data-driven impedance inversion methods,the proposed approach provides more accurate and reliable inversion results while with higher vertical resolution and better spatial continuity.The inversion results accurately characterize the spatial distribution relationship of thin sands.The model tests demonstrate that the model-constrained and data-driven impedance inversion scheme can effectively improve the thin-layer structure characterization based on the seismic data.Moreover,tests on the oil field data indicate the practicality and adaptability of the proposed method.