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Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review 被引量:1
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作者 Xinghao Du Jinhao Meng +2 位作者 Yassine Amirat Fei Gao Mohamed Benbouzid 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2024年第8期464-483,I0010,共21页
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 indis... 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. 展开更多
关键词 Lithium-ion battery impedance spectrum Temperature monitoring Failure diagnosis Health prognosis
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Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors 被引量:1
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作者 Weiheng Li Qiu-An Huang +6 位作者 Yuxuan Bai Jia Wang Linlin Wang Yuyu Liu Yufeng Zhao Xifei Li Jiujun Zhang 《Carbon Energy》 SCIE EI CAS CSCD 2024年第1期108-141,共34页
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 correlatio... 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. 展开更多
关键词 battery fuel cell supercapacitor fractional impedance spectroscopy model reduction time-frequency analysis
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Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia 被引量:1
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作者 Anjali Dixit Animesh Mandal Shib Sankar Ganguli 《Energy Geoscience》 EI 2024年第2期202-213,共12页
Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in t... Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive task.Many researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir heterogeneity.However,these attributes take seismic data as input and might not be sensitive to lateral lithology variation.To incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance inversion.Our proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as input.To evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,Australia.This study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional approach.In addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir characterization.This study also suggests a well-bounded potential reservoir facies distribution along the parallel fault lines.Thus,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage. 展开更多
关键词 Seismic texture attributes Seismic acoustic impedance Multi-directional texture attributes Reservoir heterogeneity Reservoir characterization Poseidon field
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Transverse mode-coupling instability with longitudinal impedance
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作者 Hai-Sheng Xu Chun-Tao Lin +2 位作者 Na Wang Jing-Ye Xu Yuan Zhang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2024年第6期40-53,共14页
Transverse mode-coupling instability(TMCI)is a dangerous transverse single-bunch instability that can lead to severe par-ticle loss.The mechanism of TMCI can be explained by the coupling of transverse coherent oscilla... Transverse mode-coupling instability(TMCI)is a dangerous transverse single-bunch instability that can lead to severe par-ticle loss.The mechanism of TMCI can be explained by the coupling of transverse coherent oscillation modes owing to the transverse short-range wakefield(i.e.,the transverse broadband impedance).Recent studies on future circular colliders,e.g.,FCC-ee,showed that the threshold of TMCI decreased significantly when both longitudinal and transverse impedances were included.We performed computations for the circular electron-positron collider(CEPC)and observed a similar phenom-enon.Systematic studies on the influence of longitudinal impedance on the TMCI threshold were conducted.We concluded that the imaginary part of the longitudinal impedance,which caused a reduction in the incoherent synchrotron tune,was the primary reason for the reduction in the TMCI threshold.Additionally,the real part of the longitudinal impedance assists in increasing the TMCI threshold. 展开更多
关键词 Transverse mode-coupling instability Longitudinal impedance
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Novel method for identifying the stages of discharge underwater based on impedance change characteristic
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作者 高崇 康忠健 +3 位作者 龚大建 张扬 王玉芳 孙一鸣 《Plasma Science and Technology》 SCIE EI CAS CSCD 2024年第4期133-145,共13页
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... 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. 展开更多
关键词 discharge underwater discharge stage identification impedance characteristics strong tracking filter
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3D electromagnetic simulation of the coupling characteristics and double-stub Ferrite tuners impedance matching for EAST ICRH four-strap antenna
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作者 Hua ZHOU Dan DU +4 位作者 Zhongshi YANG KSAITO Qingxi YANG Wei ZHANG Guojian NIU 《Plasma Science and Technology》 SCIE EI CAS CSCD 2024年第11期32-44,共13页
A program developed with COMSOL software integrates EAST four-strap antenna coupling with the double-stub Ferrite tuners(FT)impedance matching,obtaining physical quantities crucial for predicting the overall performan... A program developed with COMSOL software integrates EAST four-strap antenna coupling with the double-stub Ferrite tuners(FT)impedance matching,obtaining physical quantities crucial for predicting the overall performance of the ion cyclotron resonance heating(ICRH)antenna and matching system.These quantities encompass S-matrix,port complex impedance,reflection coefficients,electric field and voltage distribution,and optimal matching settings.In this study,we explore the relationship between S-matrix,reflection coefficients,port complex impedance,and frequency.Then,we analyze the impact of Faraday screens placement position and transparency,the distance from the Faraday screen(FS)to the current straps(CS),the relative distance between ports,and the characteristic impedance of the transmission line on the coupling characteristic impedance of the EAST ICRH system.Finally,we simulate the electric field distribution and voltage distribution of the EAST ICRH system for plasma heating with double-stub FT impedance matching.Using optimized parameters,the coupling power of the ICRH system can be approximately doubled.The results present herein may offer guidance for the design of high-power,long-pulse operation ICRH antenna systems. 展开更多
关键词 ion cyclotron resonance heating antenna impedance matching system coupling power S-MATRIX EAST
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Predicting dynamic compressive strength of frozen-thawed rocks by characteristic impedance and data-driven methods
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作者 Shengtao Zhou Zong-Xian Zhang +3 位作者 Xuedong Luo Yifan Huang Zhi Yu Xiaowei Yang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第7期2591-2606,共16页
In cold regions,the dynamic compressive strength(DCS)of rock damaged by freeze-thaw weathering significantly influences the stability of rock engineering.Nevertheless,testing the dynamic strength under freeze-thaw wea... In cold regions,the dynamic compressive strength(DCS)of rock damaged by freeze-thaw weathering significantly influences the stability of rock engineering.Nevertheless,testing the dynamic strength under freeze-thaw weathering conditions is often both time-consuming and expensive.Therefore,this study considers the effect of characteristic impedance on DCS and aims to quickly determine the DCS of frozen-thawed rocks through the application of machine-learning techniques.Initially,a database of DCS for frozen-thawed rocks,comprising 216 rock specimens,was compiled.Three external load parameters(freeze-thaw cycle number,confining pressure,and impact pressure)and two rock parameters(characteristic impedance and porosity)were selected as input variables,with DCS as the predicted target.This research optimized the kernel scale,penalty factor,and insensitive loss coefficient of the support vector regression(SVR)model using five swarm intelligent optimization algorithms,leading to the development of five hybrid models.In addition,a statistical DCS prediction equation using multiple linear regression techniques was developed.The performance of the prediction models was comprehensively evaluated using two error indexes and two trend indexes.A sensitivity analysis based on the cosine amplitude method has also been conducted.The results demonstrate that the proposed hybrid SVR-based models consistently provided accurate DCS predictions.Among these models,the SVR model optimized with the chameleon swarm algorithm exhibited the best performance,with metrics indicating its effectiveness,including root mean square error(RMSE)﹦3.9675,mean absolute error(MAE)﹦2.9673,coefficient of determination(R^(2))﹦0.98631,and variance accounted for(VAF)﹦98.634.This suggests that the chameleon swarm algorithm yielded the most optimal results for enhancing SVR models.Notably,impact pressure and characteristic impedance emerged as the two most influential parameters in DCS prediction.This research is anticipated to serve as a reliable reference for estimating the DCS of rocks subjected to freeze-thaw weathering. 展开更多
关键词 Freeze-thaw cycle Characteristic impedance Dynamic compressive strength Machine learning Support vector regression
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Data-driven diagnosis of high temperature PEM fuel cells based on the electrochemical impedance spectroscopy: Robustness improvement and evaluation
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作者 Dan Yu Xingjun Li +2 位作者 Samuel Simon Araya Simon Lennart Sahlin Vincenzo Liso 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2024年第9期544-558,共15页
Utilizing machine learning techniques for data-driven diagnosis of high temperature PEM fuel cells is beneficial and meaningful to the system durability. Nevertheless, ensuring the robustness of diagnosis remains a cr... Utilizing machine learning techniques for data-driven diagnosis of high temperature PEM fuel cells is beneficial and meaningful to the system durability. Nevertheless, ensuring the robustness of diagnosis remains a critical and challenging task in real application. To enhance the robustness of diagnosis and achieve a more thorough evaluation of diagnostic performance, a robust diagnostic procedure based on electrochemical impedance spectroscopy (EIS) and a new method for evaluation of the diagnosis robustness was proposed and investigated in this work. To improve the diagnosis robustness: (1) the degradation mechanism of different faults in the high temperature PEM fuel cell was first analyzed via the distribution of relaxation time of EIS to determine the equivalent circuit model (ECM) with better interpretability, simplicity and accuracy;(2) the feature extraction was implemented on the identified parameters of the ECM and extra attention was paid to distinguishing between the long-term normal degradation and other faults;(3) a Siamese Network was adopted to get features with higher robustness in a new embedding. The diagnosis was conducted using 6 classic classification algorithms—support vector machine (SVM), K-nearest neighbor (KNN), logistic regression (LR), decision tree (DT), random forest (RF), and Naive Bayes employing a dataset comprising a total of 1935 collected EIS. To evaluate the robustness of trained models: (1) different levels of errors were added to the features for performance evaluation;(2) a robustness coefficient (Roubust_C) was defined for a quantified and explicit evaluation of the diagnosis robustness. The diagnostic models employing the proposed feature extraction method can not only achieve the higher performance of around 100% but also higher robustness for diagnosis models. Despite the initial performance being similar, the KNN demonstrated a superior robustness after feature selection and re-embedding by triplet-loss method, which suggests the necessity of robustness evaluation for the machine learning models and the effectiveness of the defined robustness coefficient. This work hopes to give new insights to the robust diagnosis of high temperature PEM fuel cells and more comprehensive performance evaluation of the data-driven method for diagnostic application. 展开更多
关键词 PEM fuel cell Data-driven diagnosis Robustness improvement and evaluation Electrochemical impedance spectroscopy
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Mean nocturnal baseline impedance in gastro-esophageal reflux disease diagnosis:Should we strictly follow the Lyon 2 Consensus?
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作者 Theodoros A Voulgaris Georgios P Karamanolis 《World Journal of Gastroenterology》 SCIE CAS 2024年第26期3253-3256,共4页
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 dis... 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. 展开更多
关键词 Mean nocturnal baseline impedance Gastro-esophageal reflux disease Lyon 2 Consensus pH-impedance DIAGNOSIS
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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
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作者 Sara Marijan Luka Pavic 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CSCD 2024年第1期186-196,共11页
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 m... 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. 展开更多
关键词 phosphate glasses GLASS-CERAMICS impedance spectroscopy dielectric properties relaxation processes permittivity scaling conductivity scaling modulus formalism
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Improved reservoir characterization by means of supervised machine learning and model-based seismic impedance inversion in the Penobscot field,Scotian Basin
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作者 Satya Narayan Soumyashree Debasis Sahoo +2 位作者 Soumitra Kar Sanjit Kumar Pal Subhra Kangsabanik 《Energy Geoscience》 EI 2024年第2期183-201,共19页
The present research work attempted to delineate and characterize the reservoir facies from the Dawson Canyon Formation in the Penobscot field,Scotian Basin.An integrated study of instantaneous frequency,P-impedance,v... The present research work attempted to delineate and characterize the reservoir facies from the Dawson Canyon Formation in the Penobscot field,Scotian Basin.An integrated study of instantaneous frequency,P-impedance,volume of clay and neutron-porosity attributes,and structural framework was done to unravel the Late Cretaceous depositional system and reservoir facies distribution patterns within the study area.Fault strikes were found in the EW and NEE-SWW directions indicating the dominant course of tectonic activities during the Late Cretaceous period in the region.P-impedance was estimated using model-based seismic inversion.Petrophysical properties such as the neutron porosity(NPHI)and volume of clay(VCL)were estimated using the multilayer perceptron neural network with high accuracy.Comparatively,a combination of low instantaneous frequency(15-30 Hz),moderate to high impedance(7000-9500 gm/cc*m/s),low neutron porosity(27%-40%)and low volume of clay(40%-60%),suggests fair-to-good sandstone development in the Dawson Canyon Formation.After calibration with the welllog data,it is found that further lowering in these attribute responses signifies the clean sandstone facies possibly containing hydrocarbons.The present study suggests that the shale lithofacies dominates the Late Cretaceous deposition(Dawson Canyon Formation)in the Penobscot field,Scotian Basin.Major faults and overlying shale facies provide structural and stratigraphic seals and act as a suitable hydrocarbon entrapment mechanism in the Dawson Canyon Formation's reservoirs.The present research advocates the integrated analysis of multi-attributes estimated using different methods to minimize the risk involved in hydrocarbon exploration. 展开更多
关键词 Reservoir characterization Model-based inversion Multilayer perceptron(MLP) impedance Petrophysical properties Scotian Basin
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Statistical Inversion Based on Nonlinear Weighted Anisotropic Total Variational Model and Its Application in Electrical Impedance Tomography
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作者 Pengfei Qi 《Engineering(科研)》 2024年第1期1-7,共7页
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... 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. 展开更多
关键词 Statistical Inverse Problem Electrical impedance Tomography NWATV Prior Markov Chain Monte Carlo Sampling
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Investigation into Impedance Measurements for Rapid Capacity Estimation of Lithium-ion Batteries in Electric Vehicles
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作者 Xiaoyu Zhao Zuolu Wang +1 位作者 Eric Li Haiyan Miao 《Journal of Dynamics, Monitoring and Diagnostics》 2024年第1期21-31,共11页
With the dramatic increase in electric vehicles(EVs)globally,the demand for lithium-ion batteries has grown dramatically,resulting in many batteries being retired in the future.Developing a rapid and robust capacity e... With the dramatic increase in electric vehicles(EVs)globally,the demand for lithium-ion batteries has grown dramatically,resulting in many batteries being retired in the future.Developing a rapid and robust capacity estimation method is a challenging work to recognize the battery aging level on service and provide regroup strategy of the retied batteries in secondary use.There are still limitations on the current rapid battery capacity estimation methods,such as direct current internal resistance(DCIR)and electrochemical impedance spectroscopy(EIS),in terms of efficiency and robustness.To address the challenges,this paper proposes an improved version of DCIR,named pulse impedance technique(PIT),for rapid battery capacity estimation with more robustness.First,PIT is carried out based on the transient current excitation and dynamic voltage measurement using the high sampling frequency,in which the coherence analysis is used to guide the selection of a reliable frequency band.The battery impedance can be extracted in a wide range of frequency bands compared to the traditional DCIR method,which obtains more information on the battery capacity evaluation.Second,various statistical variables are used to extract aging features,and Pearson correlation analysis is applied to determine the highly correlated features.Then a linear regression model is developed to map the relationship between extracted features and battery capacity.To validate the performance of the proposed method,the experimental system is designed to conduct comparative studies between PIT and EIS based on the two 18650 batteries connected in series.The results reveal that the proposed PIT can provide comparative indicators to EIS,which contributes higher estimation accuracy of the proposed PIT method than EIS technology with lower time and cost. 展开更多
关键词 electric vehicles electrochemical impedance spectroscopy lithium-ion battery pulse impedance technique rapid capacity estimation
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Semi-supervised estimation of capacity degradation for lithium ion batteries with electrochemical impedance spectroscopy 被引量:5
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作者 Rui Xiong Jinpeng Tian +2 位作者 Weixiang Shen Jiahuan Lu Fengchun Sun 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2023年第1期404-413,I0010,共11页
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 c... 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. 展开更多
关键词 Lithium-ion battery Capacity degradation Electrochemical impedance spectroscopy Deep learning
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Battery impedance spectrum prediction from partial charging voltage curve by machine learning 被引量:3
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作者 Jia Guo Yunhong Che +1 位作者 Kjeld Pedersen Daniel-Ioan Stroe 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2023年第4期211-221,共11页
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 im... 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. 展开更多
关键词 impedance spectrum prediction Lithium-ion battery Machine learning EIS Graphite anode
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Human-Robot Collaboration Framework Based on Impedance Control in Robotic Assembly 被引量:1
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作者 Xingwei Zhao Yiming Chen +2 位作者 Lu Qian Bo Tao Han Ding 《Engineering》 SCIE EI CAS CSCD 2023年第11期83-92,共10页
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.I... 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. 展开更多
关键词 Human-robot collaboration impedance control Robotic assembly
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Vertical impedance functions of pile groups under low-to-high loading amplitudes:numerical simulations and experimental validation 被引量:1
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作者 Usama Zafar Chandra Shekhar Goit +1 位作者 Masato Saitoh Riku Fukuda 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2023年第3期647-666,共20页
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 elasti... 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. 展开更多
关键词 impedance functions numerical simulations model-scale experiment superposition approach soil-pile interface nonlinearity
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Stress wave analysis of high-voltage pulse discharge rock fragmentation based on plasma channel impedance model 被引量:1
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作者 黄仕杰 刘毅 +5 位作者 赵勇 徐尤来 林福昌 李化 张钦 李柳霞 《Plasma Science and Technology》 SCIE EI CAS CSCD 2023年第6期52-64,共13页
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 wa... 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. 展开更多
关键词 stress wave shock wave plasma channel impedance model rock fragmentation high-voltage pulse discharge
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High impedance fault detection in distribution network based on S-transform and average singular entropy 被引量:2
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作者 Xiaofeng Zeng Wei Gao Gengjie Yang 《Global Energy Interconnection》 EI CAS CSCD 2023年第1期64-80,共17页
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... 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. 展开更多
关键词 High impedance fault(HIF) Wavelet packet transform(WPT) S-transform(ST) Singular entropy(SE)
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Prediction of impedance responses of protonic ceramic cells using artificial neural network tuned with the distribution of relaxation times 被引量:1
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作者 Xuhao Liu Zilin Yan +6 位作者 Junwei Wu Jake Huang Yifeng Zheng Neal PSullivan Ryan O'Hayre Zheng Zhong Zehua Pan 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2023年第3期582-588,I0016,共8页
A deep-learning-based framework is proposed to predict the impedance response and underlying electrochemical behavior of the reversible protonic ceramic cell(PCC) across a wide variety of different operating condition... A deep-learning-based framework is proposed to predict the impedance response and underlying electrochemical behavior of the reversible protonic ceramic cell(PCC) across a wide variety of different operating conditions.Electrochemical impedance spectra(EIS) of PCCs were first acquired under a variety of opera ting conditions to provide a dataset containing 36 sets of EIS spectra for the model.An artificial neural network(ANN) was then trained to model the relationship between the cell operating condition and EIS response.Finally,ANN model-predicted EIS spectra were analyzed by the distribution of relaxation times(DRT) and compared to DRT spectra obtained from the experimental EIS data,enabling an assessment of the accumulative errors from the predicted EIS data vs the predicted DRT.We show that in certain cases,although the R^(2)of the predicted EIS curve may be> 0.98,the R^(2)of the predicted DRT may be as low as~0.3.This can lead to an inaccurate ANN prediction of the underlying time-resolved electrochemical response,although the apparent accuracy as evaluated from the EIS prediction may seem acceptable.After adjustment of the parameters of the ANN framework,the average R^(2)of the DRTs derived from the predicted EIS can be improved to 0.9667.Thus,we demonstrate that a properly tuned ANN model can be used as an effective tool to predict not only the EIS,but also the DRT of complex electrochemical systems. 展开更多
关键词 Protonic ceramic fuel cell/electrolysis cell Electrochemical impedance spectroscopy Distribution of relaxation times Artificial neural network
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