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
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
Despite great progress in lithium-sulfur(Li-S) batteries, the electrochemical reactions in the cell are not yet fully understood. Electrode processes, complex interfaces and internal resistance may be characterized by...Despite great progress in lithium-sulfur(Li-S) batteries, the electrochemical reactions in the cell are not yet fully understood. Electrode processes, complex interfaces and internal resistance may be characterized by electrochemical impedance spectroscopy(EIS). EIS is a non-destructive technique and easy to apply, though there are challenges in ensuring the reproducibility of measurements and the interpretation of impedance data. Here, we present the impedance behavior of a 3.4 Ah Li-S pouch cell characterized by EIS. The impedance changes were analyzed over the entire depth-of-discharge, depth-of-charge,and at various temperatures. Based on the formation of intermediates during(dis)charging, the changes of resistances are observed. Overall, the increase in temperature causes a decrease in electrolyte viscosity,lowering the surface energy which can improve the penetration of the electrolyte into the electrode pores. Moreover, the effect of superimposed AC current during EIS measurement was analyzed, and the results show the dependence of the charge transfer resistance on superimposed AC current which was lower compared to steady-state conditions and consents with theory.展开更多
Plasma electrolytic oxidation （PEO） coatings are prepared on aluminium with graphite powders added into the electrolyte. The scanning electron microscopy （SEM） coupled with an energy dispersive x-ray analysis syst...Plasma electrolytic oxidation （PEO） coatings are prepared on aluminium with graphite powders added into the electrolyte. The scanning electron microscopy （SEM） coupled with an energy dispersive x-ray analysis system （EDX） is used to characterize the surface and the cross-section morphologies of the coatings. The electrochemical impedance spectroscopy （EIS） is used not only to evaluate the corrosion resistance but also to analyse the structure of the coating. Results show that graphite powders are embedded in the PEO coating. The corrosion resistances of both the inner barrier and the outer porous layer are greatly improved, and the EIS could give some valuable detailed information about the coating structure.展开更多
All-solid-state lithium batteries(ASSLBs)are strongly considered as the next-generation energy storage devices for their high energy density and intrinsic safety.The solid-solid contact between lithium metal and solid...All-solid-state lithium batteries(ASSLBs)are strongly considered as the next-generation energy storage devices for their high energy density and intrinsic safety.The solid-solid contact between lithium metal and solid electrolyte plays a vital role in the performance of working ASSLBs,which is challenging to investigate quantitatively by experimental approach.This work proposed a quantitative model based on the finite element method for electrochemical impedance spectroscopy simulation of different solid-solid contact states in ASSLBs.With the assistance of an equivalent circuit model and distribution of relaxation times,it is discovered that as the number of voids and the sharpness of cracks increase,the contact resistance Rcgrows and ultimately dominates the battery impedance.Through accurate fitting,inverse proportional relations between contact resistance Rcand(1-porosity)as well as crack angle was disclosed.This contribution affords a fresh insight into clarifying solid-solid contact states in ASSLBs.展开更多
Accurate prediction of performance degradation in complex systems such as solid oxide fuel cells is crucial for expediting technological advancements.However,significant challenges still persist due to limited compreh...Accurate prediction of performance degradation in complex systems such as solid oxide fuel cells is crucial for expediting technological advancements.However,significant challenges still persist due to limited comprehension of degradation mechanisms and difficulties in acquiring in-situ features.In this study,we propose an effective approach that integrates long short-term memory(LSTM) neural network and dynamic electrochemical impedance spectroscopy(DEIS).This integrated approach enables precise prediction of future evolutions in both current-voltage and EIS features using historical testing data,without prior knowledge of degradation mechanisms.For short-term predictions spanning hundreds of hours,our approach achieves a prediction accuracy exceeding 0.99,showcasing promising prospects for diagnostic applications.Additionally,for long-term predictions spanning thousands of hours,we quantitatively determine the significance of each degradation mechanism,which is crucial for enhancing cell durability.Moreover,our proposed approach demonstrates satisfactory predictive ability in both time and frequency domains,offering the potential to reduce EIS testing time by more than half.展开更多
Photocatalytic splitting of water over p-type semiconductors is a promising strategy for production of hydrogen.However,the determination of rate law is rarely reported.To this purpose,copper oxide(CuO)is selected as ...Photocatalytic splitting of water over p-type semiconductors is a promising strategy for production of hydrogen.However,the determination of rate law is rarely reported.To this purpose,copper oxide(CuO)is selected as a model photocathode in this study,and the photogenerated surface charge density,interfacial charge transfer rate constant and their relation to the water reduction rate(in terms of photocurrent)were investigated by a combination of(photo)electrochemical techniques.The results showed that the charge transfer rate constant is exponential-dependent on the surface charge density,and that the photocurrent equals to the product of the charge transfer rate constant and surface charge density.The reaction is first-order in terms of surface charge density.Such an unconventional rate law contrasts with the reports in literature.The charge density-dependent rate constant results from the Fermi level pinning(i.e.,Galvani potential is the main driving force for the reaction)due to accumulation of charge in the surface states and/or Frumkin behavior(i.e.,chemical potential is the main driving force).This study,therefore,may be helpful for further investigation on the mechanism of hydrogen evolution over a CuO photocathode and for designing more efficient CuO-based photocatalysts.展开更多
Several acid compounds have been employed as additives of the V(V) electrolyte for vanadium redox flow battery(VRB) to improve its stability and electrochemical activity. Stability of the V(V) electrolyte with and wit...Several acid compounds have been employed as additives of the V(V) electrolyte for vanadium redox flow battery(VRB) to improve its stability and electrochemical activity. Stability of the V(V) electrolyte with and without additives was investigated with ex-situ heating/cooling treatment at a wide temperature range of-5 ?C to 60 ?C. It was observed that methanesulfonic acid, boric acid, hydrochloric acid, trifluoroacetic acid,polyacrylic acid, oxalic acid, methacrylic acid and phosphotungstic acid could improve the stability of the V(V) electrolyte at a certain range of temperature. Their electrochemical behaviors in the V(V) electrolyte were further studied by cyclic voltammetry(CV), steady state polarization and electrochemical impedance spectroscopy(EIS). The results showed that the electrochemical activity, including the reversibility of electrode reaction, the diffusivity of V(V) species, the polarization resistance and the flexibility of charge transfer for the V(V) electrolyte with these additives were all improved compared with the pristine solution.展开更多
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
This work investigated the degradation of tin – based gas-diffusion electrodes (GDE) and also a promising Bi2O3 GDE in electrochemical CO_(2) reduction in highly alkaline media which has not been studied before. The ...This work investigated the degradation of tin – based gas-diffusion electrodes (GDE) and also a promising Bi2O3 GDE in electrochemical CO_(2) reduction in highly alkaline media which has not been studied before. The contributions of the electrode wetting (or flooding, if excessively) and catalyst leaching on the degradation were analyzed. Therefore, electrochemical impedance spectroscopy was used to monitor the wetted surface area of the GDE in combination with post-mortem analysis of the penetration depth by visualizing the electrolyte’s cation in the GDE cross-section. Furthermore, to reveal a possible degradation of the electrocatalyst, its distribution was mapped in the GDEs cross-section after operation while the catholyte was additionally analyzed via ICP-MS. The results clearly demonstrate that the SnO_(2) catalyst dissolves in the reaction zone inside the GDE and might be partially redeposited near the GDEs surface. Since the redeposition process occurs only partially a steady loss of catalyst was observed impeding a clear distinction of the two degradation phenomena. Nevertheless, the deterioration of the electrode performance measured as faraday efficiency (FE) of the parasitic hydrogen evolution reaction (HER) qualitatively correlates with the differential double layer capacitance (Cdl). A significant difference of the rate of increase for the hydrogen FE and Cdl can be ascribed to the superposition of both above-mentioned degradation mechanisms. The demonstrated instability of SnO_(2) contrasts with the behavior of Bi2O3 GDE which is stabilized during CO_(2) conversion by redeposition of the diluted dissolved species as metallic Bi which is active for the CO_(2) reduction reaction.展开更多
Degradation behavior is the main technical problem in the field of commercial application of lithiumion batteries. According to the characteristics of voltage, discharge capacity and inner resistance during the charge...Degradation behavior is the main technical problem in the field of commercial application of lithiumion batteries. According to the characteristics of voltage, discharge capacity and inner resistance during the charge/discharge process of commercial lithium-ion batteries of mobile telephone, degradation analysis and related mechanisms are put forward and discussed in the paper. The impedance spectra of prismatic commercial lithium-ion batteries are measured at various state of charge after different charge/discharge cycles. The incastared impedance spectra are discussed with a proposed equivalent circuit. Results indicated that the structure change of electrode materials or swell and shrink of crystal lattice, decompose of electrolyte, dissolution of active materials and solid electrolyte interphase film formation are the main reasons leading to the capacity degradation.展开更多
Nickel hydroxide was used as the positive electrode material in rechargeable alkaline batteries, which plays a significant role in the field of electric energy storage devices. β-nickel hydroxide（β-Ni（OH）2 ） was...Nickel hydroxide was used as the positive electrode material in rechargeable alkaline batteries, which plays a significant role in the field of electric energy storage devices. β-nickel hydroxide（β-Ni（OH）2 ） was prepared from nickel sulphate solution using potassium hydroxide as a precipitating agent. Pure β-phase of nickel hydroxide was confirmed from XRD and FT-IR studies. The effects of TiO2 additive on the β-Ni（OH）2 electrode performance are examined. The structure and property of the TiO2 added β-Ni（OH）2 were characterized by XRD, TG-DTA and SEM analysis. A pasted–type electrode is prepared using nickel hydroxide powder as the main active material on a nickel sheet as a current collector. Cyclic voltammetry and electrochemical impedance spectroscopy studies were performed to evaluate the electrochemical performance of the β-Ni（OH）2 and TiO2 added β-Ni（OH）2 electrodes in 6 M KOH electrolyte. Anodic（Epa） and cathodic（Epc）peak potentials are found to decrease after the addition of TiO 2 into β-Ni（OH）2 electrode material. Further,addition of TiO2 is found to enhance the reversibility of the electrode reaction and also increase the separation of the oxidation current peak of the active material from the oxygen evolution current. Compared with pure β-Ni（OH）2 lectrode,TiO2 added β-Ni（OH）2 electrode is found to exhibit higher proton diffusion coefficient（D） and lower charge transfer resistance. These findings suggest that the TiO2 added β-Ni（OH）2 electrode possess improved electrochemical properties and thus can be recognized as a promising candidate for the battery electrode applications.展开更多
In the development of Li-ion batteries(LIBs)with high energy/power density,long cycle-life,fast charging,and high safety,an insight into charge transfer reactions is required.Although electrochemical impedance spectro...In the development of Li-ion batteries(LIBs)with high energy/power density,long cycle-life,fast charging,and high safety,an insight into charge transfer reactions is required.Although electrochemical impedance spectroscopy(EIS)is regarded as a powerful diagnosis tool,it is not a direct but an indirect measurement.With respect to this,some critical questions need to be answered:(i)why EIS can reflect the kinetics of charge transfer reactions;(ii)what the inherent logical relationship between impedance models under different physical scenes is;(iii)how charge transfer reactions compete with each other at multiple scales.This work aims at answering these questions via developing a theory framework so as to mitigate the blindness and uncertainty in unveiling charge transfer reactions in LIBs.To systematically answer the above questions,this article is organized into a three-in-one(review,tutorial,and research)type and the following contributions are made:(i)a brief review is given for impedance model development of the LIBs over the past half century;(ii)an open source code toolbox is developed based on the unified impedance model;(iii)the competive mechanisms of charge transfer reactions are unveiled based on the developed EIS-Toolbox@LIB.This work not only clarifies theoretical fundamentals,but also provides an easy-to-use open source code for EIS-Toolbox@LIB to optimize fast charge/discharge,mitigate cycle aging,and improve energy/power density.展开更多
PEO-based all-solid-state electrolytes are extensively utilized and researched owing to their exceptional safety,low-mass-density,and cost-effectiveness.However,the low oxidation potential of PEO makes the interface p...PEO-based all-solid-state electrolytes are extensively utilized and researched owing to their exceptional safety,low-mass-density,and cost-effectiveness.However,the low oxidation potential of PEO makes the interface problem with the high-voltage cathode extremely severe.In this work,the impedance of PEO-based all-solid-state batteries with high-voltage cathode(NCM811)was studied at different potentials.The Nyquist plots displayed a gyrate arc at low-frequencies for NCM811/PEO interface.Based on the kinetic modeling,it was deduced that there is a decomposition reaction of PEO-matrix in addition to de-embedded reaction of NCM811,and the PEO intermediate product(dehydra-PEO)adsorbed on the electrode surface leading to low-frequency inductive arcs.Furthermore,the distribution of relaxation time shows the dehydra-PEO results in the kinetic tardiness of the charge transfer process in the temporal dimension.Hence,an artificial interface layer(CEI_(x))was modified on the surface of NCM811 to regulate the potential of cathode/electrolyte interface to prevent the high-voltage deterioration of PEO.NCM/CEI_(x)/PEO batteries exhibit capacity retentions of 96.0%,84.6%,and 76.8%after undergoing 100 cycles at cut-off voltages of 4.1,4.2,and 4.3 V,respectively.Therefore,here the failure mechanism of high-voltage PEO electrolyte is investigated by EIS and a proposed solving strategy is presented.展开更多
Battery health evaluation and management are vital for the long-term reliability and optimal performance of lithium-ion batteries in electric vehicles.Electrochemical impedance spectroscopy(EIS)offers valuable insight...Battery health evaluation and management are vital for the long-term reliability and optimal performance of lithium-ion batteries in electric vehicles.Electrochemical impedance spectroscopy(EIS)offers valuable insights into battery degradation analysis and modeling.However,previous studies have not adequately addressed the impedance uncertainties,particularly during battery operating conditions,which can substantially impact the robustness and accuracy of state of health(SOH)estimation.Motivated by this,this paper proposes a comprehensive feature optimization scheme that integrates impedance validity assessment with correlation analysis.By utilizing metrics such as impedance residuals and correlation coefficients,the proposed method effectively filters out invalid and insignificant impedance data,thereby enhancing the reliability of the input features.Subsequently,the extreme gradient boosting(XGBoost)modeling framework is constructed for estimating the battery degradation trajectories.The XGBoost model incorporates a diverse range of hyperparameters,optimized by a genetic algorithm to improve its adaptability and generalization performance.Experimental validation confirms the effectiveness of the proposed feature optimization scheme,demonstrating the superior estimation performance of the proposed method in comparison with four baseline techniques.展开更多
Rate capability,peak power,and energy density are of vital importance for the capacitive energy storage(CES)of electrochemical energy devices.The frequency response analysis(FRA)is regarded as an efficient tool in stu...Rate capability,peak power,and energy density are of vital importance for the capacitive energy storage(CES)of electrochemical energy devices.The frequency response analysis(FRA)is regarded as an efficient tool in studying the CES.In the present work,a bi-scale impedance transmission line model(TLM)is firstly developed for a single pore to a porous electrode.Not only the TLM of the single pore is reparameterized but also the particle packing compactness is defined in the bi-scale.Subsequently,the CES properties are identified by FRA,focused on rate capability vs.characteristic frequency,peak power vs.equivalent series resistance,and energy density vs.low frequency limiting capacitance for a single pore to a porous electrode.Based on these relationships,the CES properties are numerically simulated and theoretically predicted for a single pore to a porous electrode in terms of intra-particle pore length,intra-particle pore diameter,inter-particle pore diameter,electrolyte conductivity,interfacial capacitance&exponent factor,electrode thickness,electrode apparent surface area,and particle packing compactness.Finally,the experimental diagnosis of four supercapacitors(SCs)with different electrode thicknesses is conducted for validating the bi-scale TLM and gaining an insight into the CES properties for a porous electrode to a single pore.The calculating results suggest,to some extent,the inter-particle pore plays a more critical role than the intra-particle pore in the CES properties such as the rate capability and the peak power density for a single pore to a porous electrode.Hence,in order to design a better porous electrode,more attention should be given to the inter-particle pore.展开更多
Structural and morphological changes as well as corrosion behavior of N+implanted Al in 0.6 M NaCl solution as function of N+fluence are investigated.The x-ray diffraction results confirmed AlN formation.The atomic fo...Structural and morphological changes as well as corrosion behavior of N+implanted Al in 0.6 M NaCl solution as function of N+fluence are investigated.The x-ray diffraction results confirmed AlN formation.The atomic force microscope(AFM)images showed larger grains on the surface of Al with increasing N+fluence.This can be due to the increased number of impacts of N+with Al atoms and energy conversion to heat,which increases the diffusion rate of the incident ions in the target.Hence,the number of the grain boundaries is reduced,resulting in corrosion resistance enhancement.Electrochemical impedance spectroscopy(EIS)and polarization results showed the increase of corrosion resistance of Al with increasing N+fluence.EIS data was used to simulate equivalent electric circuits(EC)for the samples.Strong dependence of the surface morphology on the EC elements was observed.The scanning electron microscope(SEM)analysis of the samples after corrosion test also showed that the surfaces of the implanted Al samples remain more intact relative to the untreated Al sample,consistent with the EIS and polarization results.展开更多
Mixed ionic electronic conductors(MIECs)have attracted increasing attention as anode materials for solid oxide fuel cells(SOFCs)and they hold great promise for lowering the operation temperature of SOFCs.However,there...Mixed ionic electronic conductors(MIECs)have attracted increasing attention as anode materials for solid oxide fuel cells(SOFCs)and they hold great promise for lowering the operation temperature of SOFCs.However,there has been a lack of understanding of the performance-limiting factors and guidelines for rational design of composite metal-MIEC electrodes.Using a newly-developed approach based on 3 D-tomography and electrochemical impedance spectroscopy,here for the first time we quantify the contribution of the dual-phase boundary(DPB)relative to the three-phase boundary(TPB)reaction pathway on real MIEC electrodes.A new design strategy is developed for Ni/gadolinium doped ceria(CGO)electrodes(a typical MIEC electrode)based on the quantitative analyses and a novel Ni/CGO fiber-matrix structure is proposed and fabricated by combining electrospinning and tape-casting methods using commercial powders.With only 11.5 vol%nickel,the designer Ni/CGO fiber-matrix electrode shows 32%and 67%lower polarization resistance than a nano-Ni impregnated CGO scaffold electrode and conventional cermet electrode respectively.The results in this paper demonstrate quantitatively using real electrode structures that enhancing DPB and hydrogen kinetics are more efficient strategies to enhance electrode performance than simply increasing TPB.展开更多
基金supported by the Chinese Scholarship Council(Nos.202208320055 and 202108320111)the support from the energy department of Aalborg University was acknowledged.
文摘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.
基金supported by the National Key R&D Program of China(2021YFB2402002)the National Natural Science Foundation of China(51922006 and 51877009)+1 种基金the China Postdoctoral Science Foundation(BX2021035 and 2022M710379)the Beijing Natural Science Foundation(Grant No.L223013)。
文摘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.
基金supported by the Ministry of Education,Science,Research and Sport of the Slovak Republic under project No.313011V334,Innovative Solutions for Propulsion,Power and Safety Components of Transport Vehicles。
文摘Despite great progress in lithium-sulfur(Li-S) batteries, the electrochemical reactions in the cell are not yet fully understood. Electrode processes, complex interfaces and internal resistance may be characterized by electrochemical impedance spectroscopy(EIS). EIS is a non-destructive technique and easy to apply, though there are challenges in ensuring the reproducibility of measurements and the interpretation of impedance data. Here, we present the impedance behavior of a 3.4 Ah Li-S pouch cell characterized by EIS. The impedance changes were analyzed over the entire depth-of-discharge, depth-of-charge,and at various temperatures. Based on the formation of intermediates during(dis)charging, the changes of resistances are observed. Overall, the increase in temperature causes a decrease in electrolyte viscosity,lowering the surface energy which can improve the penetration of the electrolyte into the electrode pores. Moreover, the effect of superimposed AC current during EIS measurement was analyzed, and the results show the dependence of the charge transfer resistance on superimposed AC current which was lower compared to steady-state conditions and consents with theory.
基金Project supported by the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No.10811140326)the State Key Program of the National Natural Science Foundation of China(Grant No.10735090)
文摘Plasma electrolytic oxidation （PEO） coatings are prepared on aluminium with graphite powders added into the electrolyte. The scanning electron microscopy （SEM） coupled with an energy dispersive x-ray analysis system （EDX） is used to characterize the surface and the cross-section morphologies of the coatings. The electrochemical impedance spectroscopy （EIS） is used not only to evaluate the corrosion resistance but also to analyse the structure of the coating. Results show that graphite powders are embedded in the PEO coating. The corrosion resistances of both the inner barrier and the outer porous layer are greatly improved, and the EIS could give some valuable detailed information about the coating structure.
基金supported by the Beijing Natural Science Foundation(Z200011,L233004)the National Key Research and Development Program(2021YFB2500300)+3 种基金the National Natural Science Foundation of China(52394170,52394171,22109011,22393900,and 22108151)the Tsinghua-Jiangyin Innovation Special Fund(TJISF)(2022JYTH0101)the S&T Program of Hebei(22344402D)the Tsinghua University Initiative Scientific Research Program.
文摘All-solid-state lithium batteries(ASSLBs)are strongly considered as the next-generation energy storage devices for their high energy density and intrinsic safety.The solid-solid contact between lithium metal and solid electrolyte plays a vital role in the performance of working ASSLBs,which is challenging to investigate quantitatively by experimental approach.This work proposed a quantitative model based on the finite element method for electrochemical impedance spectroscopy simulation of different solid-solid contact states in ASSLBs.With the assistance of an equivalent circuit model and distribution of relaxation times,it is discovered that as the number of voids and the sharpness of cracks increase,the contact resistance Rcgrows and ultimately dominates the battery impedance.Through accurate fitting,inverse proportional relations between contact resistance Rcand(1-porosity)as well as crack angle was disclosed.This contribution affords a fresh insight into clarifying solid-solid contact states in ASSLBs.
基金partly supported by Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellowships for Research in Japan (P22370)by Key Project of Jiangsu Province (BE2022029) in China。
文摘Accurate prediction of performance degradation in complex systems such as solid oxide fuel cells is crucial for expediting technological advancements.However,significant challenges still persist due to limited comprehension of degradation mechanisms and difficulties in acquiring in-situ features.In this study,we propose an effective approach that integrates long short-term memory(LSTM) neural network and dynamic electrochemical impedance spectroscopy(DEIS).This integrated approach enables precise prediction of future evolutions in both current-voltage and EIS features using historical testing data,without prior knowledge of degradation mechanisms.For short-term predictions spanning hundreds of hours,our approach achieves a prediction accuracy exceeding 0.99,showcasing promising prospects for diagnostic applications.Additionally,for long-term predictions spanning thousands of hours,we quantitatively determine the significance of each degradation mechanism,which is crucial for enhancing cell durability.Moreover,our proposed approach demonstrates satisfactory predictive ability in both time and frequency domains,offering the potential to reduce EIS testing time by more than half.
基金the National Basic Research Development of China(2011CB936003)the National Natural Science Foundation of China(50971116)。
文摘Photocatalytic splitting of water over p-type semiconductors is a promising strategy for production of hydrogen.However,the determination of rate law is rarely reported.To this purpose,copper oxide(CuO)is selected as a model photocathode in this study,and the photogenerated surface charge density,interfacial charge transfer rate constant and their relation to the water reduction rate(in terms of photocurrent)were investigated by a combination of(photo)electrochemical techniques.The results showed that the charge transfer rate constant is exponential-dependent on the surface charge density,and that the photocurrent equals to the product of the charge transfer rate constant and surface charge density.The reaction is first-order in terms of surface charge density.Such an unconventional rate law contrasts with the reports in literature.The charge density-dependent rate constant results from the Fermi level pinning(i.e.,Galvani potential is the main driving force for the reaction)due to accumulation of charge in the surface states and/or Frumkin behavior(i.e.,chemical potential is the main driving force).This study,therefore,may be helpful for further investigation on the mechanism of hydrogen evolution over a CuO photocathode and for designing more efficient CuO-based photocatalysts.
基金supported by the Doctoral Program of Higher Education(No.20110181110003)the Collaborative innovation fund by China Academyof Engineering Physics and Sichuan University(No.XTCX2011001)the Sichuan Provincial Department of Science and Technology R&D Program(No.2013FZ0034)
文摘Several acid compounds have been employed as additives of the V(V) electrolyte for vanadium redox flow battery(VRB) to improve its stability and electrochemical activity. Stability of the V(V) electrolyte with and without additives was investigated with ex-situ heating/cooling treatment at a wide temperature range of-5 ?C to 60 ?C. It was observed that methanesulfonic acid, boric acid, hydrochloric acid, trifluoroacetic acid,polyacrylic acid, oxalic acid, methacrylic acid and phosphotungstic acid could improve the stability of the V(V) electrolyte at a certain range of temperature. Their electrochemical behaviors in the V(V) electrolyte were further studied by cyclic voltammetry(CV), steady state polarization and electrochemical impedance spectroscopy(EIS). The results showed that the electrochemical activity, including the reversibility of electrode reaction, the diffusivity of V(V) species, the polarization resistance and the flexibility of charge transfer for the V(V) electrolyte with these additives were all improved compared with the pristine solution.
基金funding from the National Natural Science Foundation of China,China(12172104,52102226)the Shenzhen Science and Technology Innovation Commission,China(JCYJ20200109113439837)the Stable Supporting Fund of Shenzhen,China(GXWD2020123015542700320200728114835006)。
文摘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.
基金Parts of this work were funded by the German Federation of Industrial Research Associations(EWN03176/18).
文摘This work investigated the degradation of tin – based gas-diffusion electrodes (GDE) and also a promising Bi2O3 GDE in electrochemical CO_(2) reduction in highly alkaline media which has not been studied before. The contributions of the electrode wetting (or flooding, if excessively) and catalyst leaching on the degradation were analyzed. Therefore, electrochemical impedance spectroscopy was used to monitor the wetted surface area of the GDE in combination with post-mortem analysis of the penetration depth by visualizing the electrolyte’s cation in the GDE cross-section. Furthermore, to reveal a possible degradation of the electrocatalyst, its distribution was mapped in the GDEs cross-section after operation while the catholyte was additionally analyzed via ICP-MS. The results clearly demonstrate that the SnO_(2) catalyst dissolves in the reaction zone inside the GDE and might be partially redeposited near the GDEs surface. Since the redeposition process occurs only partially a steady loss of catalyst was observed impeding a clear distinction of the two degradation phenomena. Nevertheless, the deterioration of the electrode performance measured as faraday efficiency (FE) of the parasitic hydrogen evolution reaction (HER) qualitatively correlates with the differential double layer capacitance (Cdl). A significant difference of the rate of increase for the hydrogen FE and Cdl can be ascribed to the superposition of both above-mentioned degradation mechanisms. The demonstrated instability of SnO_(2) contrasts with the behavior of Bi2O3 GDE which is stabilized during CO_(2) conversion by redeposition of the diluted dissolved species as metallic Bi which is active for the CO_(2) reduction reaction.
基金"973"Project (2002CB211800)Teaching and Research Fund of Beijing Institute of Technology(20070542008)
文摘Degradation behavior is the main technical problem in the field of commercial application of lithiumion batteries. According to the characteristics of voltage, discharge capacity and inner resistance during the charge/discharge process of commercial lithium-ion batteries of mobile telephone, degradation analysis and related mechanisms are put forward and discussed in the paper. The impedance spectra of prismatic commercial lithium-ion batteries are measured at various state of charge after different charge/discharge cycles. The incastared impedance spectra are discussed with a proposed equivalent circuit. Results indicated that the structure change of electrode materials or swell and shrink of crystal lattice, decompose of electrolyte, dissolution of active materials and solid electrolyte interphase film formation are the main reasons leading to the capacity degradation.
文摘Nickel hydroxide was used as the positive electrode material in rechargeable alkaline batteries, which plays a significant role in the field of electric energy storage devices. β-nickel hydroxide（β-Ni（OH）2 ） was prepared from nickel sulphate solution using potassium hydroxide as a precipitating agent. Pure β-phase of nickel hydroxide was confirmed from XRD and FT-IR studies. The effects of TiO2 additive on the β-Ni（OH）2 electrode performance are examined. The structure and property of the TiO2 added β-Ni（OH）2 were characterized by XRD, TG-DTA and SEM analysis. A pasted–type electrode is prepared using nickel hydroxide powder as the main active material on a nickel sheet as a current collector. Cyclic voltammetry and electrochemical impedance spectroscopy studies were performed to evaluate the electrochemical performance of the β-Ni（OH）2 and TiO2 added β-Ni（OH）2 electrodes in 6 M KOH electrolyte. Anodic（Epa） and cathodic（Epc）peak potentials are found to decrease after the addition of TiO 2 into β-Ni（OH）2 electrode material. Further,addition of TiO2 is found to enhance the reversibility of the electrode reaction and also increase the separation of the oxidation current peak of the active material from the oxygen evolution current. Compared with pure β-Ni（OH）2 lectrode,TiO2 added β-Ni（OH）2 electrode is found to exhibit higher proton diffusion coefficient（D） and lower charge transfer resistance. These findings suggest that the TiO2 added β-Ni（OH）2 electrode possess improved electrochemical properties and thus can be recognized as a promising candidate for the battery electrode applications.
基金the financial support from the National Science Foundation of China(22078190)the National Key R&D Plan of China(2020YFB1505802)。
文摘In the development of Li-ion batteries(LIBs)with high energy/power density,long cycle-life,fast charging,and high safety,an insight into charge transfer reactions is required.Although electrochemical impedance spectroscopy(EIS)is regarded as a powerful diagnosis tool,it is not a direct but an indirect measurement.With respect to this,some critical questions need to be answered:(i)why EIS can reflect the kinetics of charge transfer reactions;(ii)what the inherent logical relationship between impedance models under different physical scenes is;(iii)how charge transfer reactions compete with each other at multiple scales.This work aims at answering these questions via developing a theory framework so as to mitigate the blindness and uncertainty in unveiling charge transfer reactions in LIBs.To systematically answer the above questions,this article is organized into a three-in-one(review,tutorial,and research)type and the following contributions are made:(i)a brief review is given for impedance model development of the LIBs over the past half century;(ii)an open source code toolbox is developed based on the unified impedance model;(iii)the competive mechanisms of charge transfer reactions are unveiled based on the developed EIS-Toolbox@LIB.This work not only clarifies theoretical fundamentals,but also provides an easy-to-use open source code for EIS-Toolbox@LIB to optimize fast charge/discharge,mitigate cycle aging,and improve energy/power density.
基金financially supported by the National Natural Science Foundation of China (Nos. 51972023, 11210304)
文摘PEO-based all-solid-state electrolytes are extensively utilized and researched owing to their exceptional safety,low-mass-density,and cost-effectiveness.However,the low oxidation potential of PEO makes the interface problem with the high-voltage cathode extremely severe.In this work,the impedance of PEO-based all-solid-state batteries with high-voltage cathode(NCM811)was studied at different potentials.The Nyquist plots displayed a gyrate arc at low-frequencies for NCM811/PEO interface.Based on the kinetic modeling,it was deduced that there is a decomposition reaction of PEO-matrix in addition to de-embedded reaction of NCM811,and the PEO intermediate product(dehydra-PEO)adsorbed on the electrode surface leading to low-frequency inductive arcs.Furthermore,the distribution of relaxation time shows the dehydra-PEO results in the kinetic tardiness of the charge transfer process in the temporal dimension.Hence,an artificial interface layer(CEI_(x))was modified on the surface of NCM811 to regulate the potential of cathode/electrolyte interface to prevent the high-voltage deterioration of PEO.NCM/CEI_(x)/PEO batteries exhibit capacity retentions of 96.0%,84.6%,and 76.8%after undergoing 100 cycles at cut-off voltages of 4.1,4.2,and 4.3 V,respectively.Therefore,here the failure mechanism of high-voltage PEO electrolyte is investigated by EIS and a proposed solving strategy is presented.
文摘Battery health evaluation and management are vital for the long-term reliability and optimal performance of lithium-ion batteries in electric vehicles.Electrochemical impedance spectroscopy(EIS)offers valuable insights into battery degradation analysis and modeling.However,previous studies have not adequately addressed the impedance uncertainties,particularly during battery operating conditions,which can substantially impact the robustness and accuracy of state of health(SOH)estimation.Motivated by this,this paper proposes a comprehensive feature optimization scheme that integrates impedance validity assessment with correlation analysis.By utilizing metrics such as impedance residuals and correlation coefficients,the proposed method effectively filters out invalid and insignificant impedance data,thereby enhancing the reliability of the input features.Subsequently,the extreme gradient boosting(XGBoost)modeling framework is constructed for estimating the battery degradation trajectories.The XGBoost model incorporates a diverse range of hyperparameters,optimized by a genetic algorithm to improve its adaptability and generalization performance.Experimental validation confirms the effectiveness of the proposed feature optimization scheme,demonstrating the superior estimation performance of the proposed method in comparison with four baseline techniques.
基金financial support from the National Science Foundation of China(22078190)the National Key R&D Plan of China(2020YFB1505802)。
文摘Rate capability,peak power,and energy density are of vital importance for the capacitive energy storage(CES)of electrochemical energy devices.The frequency response analysis(FRA)is regarded as an efficient tool in studying the CES.In the present work,a bi-scale impedance transmission line model(TLM)is firstly developed for a single pore to a porous electrode.Not only the TLM of the single pore is reparameterized but also the particle packing compactness is defined in the bi-scale.Subsequently,the CES properties are identified by FRA,focused on rate capability vs.characteristic frequency,peak power vs.equivalent series resistance,and energy density vs.low frequency limiting capacitance for a single pore to a porous electrode.Based on these relationships,the CES properties are numerically simulated and theoretically predicted for a single pore to a porous electrode in terms of intra-particle pore length,intra-particle pore diameter,inter-particle pore diameter,electrolyte conductivity,interfacial capacitance&exponent factor,electrode thickness,electrode apparent surface area,and particle packing compactness.Finally,the experimental diagnosis of four supercapacitors(SCs)with different electrode thicknesses is conducted for validating the bi-scale TLM and gaining an insight into the CES properties for a porous electrode to a single pore.The calculating results suggest,to some extent,the inter-particle pore plays a more critical role than the intra-particle pore in the CES properties such as the rate capability and the peak power density for a single pore to a porous electrode.Hence,in order to design a better porous electrode,more attention should be given to the inter-particle pore.
文摘Structural and morphological changes as well as corrosion behavior of N+implanted Al in 0.6 M NaCl solution as function of N+fluence are investigated.The x-ray diffraction results confirmed AlN formation.The atomic force microscope(AFM)images showed larger grains on the surface of Al with increasing N+fluence.This can be due to the increased number of impacts of N+with Al atoms and energy conversion to heat,which increases the diffusion rate of the incident ions in the target.Hence,the number of the grain boundaries is reduced,resulting in corrosion resistance enhancement.Electrochemical impedance spectroscopy(EIS)and polarization results showed the increase of corrosion resistance of Al with increasing N+fluence.EIS data was used to simulate equivalent electric circuits(EC)for the samples.Strong dependence of the surface morphology on the EC elements was observed.The scanning electron microscope(SEM)analysis of the samples after corrosion test also showed that the surfaces of the implanted Al samples remain more intact relative to the untreated Al sample,consistent with the EIS and polarization results.
基金sponsored by the National Basic Research Program of China(973 Program)under grant no.2015CB351905the National Natural Science Foundation of China(no.61504019)+3 种基金China Postdoctoral Science Foundation(no.2015M580783)Scientific Research Start-up Foundation of University of Electronic Science and Technology of China(Y02002010301082)the Technology Innovative Research Team of Sichuan Province of China(no.2015TD0005)the Fundamental Research Funds for the Central Universities of China(no.ZYGX2015J140)
基金the financial support from EPSRC(EP/P024807/1,EP/M014045/1,EP/S000933/1 and EP/N009924/1)by the EPSRC energy storage for low carbon grids project(EP/K002252/1)+3 种基金the EPSRC Joint UK-India Clean Energy center(JUICE)(EP/P003605/1)the Integrated Development of Low-Carbon Energy Systems(IDLES)project(EP/R045518/1)the Innovate UK BAFTA project,the Innovate UK for Advanced Battery Lifetime Extension(ABLE)project for funding underthe China Scholarship Council。
文摘Mixed ionic electronic conductors(MIECs)have attracted increasing attention as anode materials for solid oxide fuel cells(SOFCs)and they hold great promise for lowering the operation temperature of SOFCs.However,there has been a lack of understanding of the performance-limiting factors and guidelines for rational design of composite metal-MIEC electrodes.Using a newly-developed approach based on 3 D-tomography and electrochemical impedance spectroscopy,here for the first time we quantify the contribution of the dual-phase boundary(DPB)relative to the three-phase boundary(TPB)reaction pathway on real MIEC electrodes.A new design strategy is developed for Ni/gadolinium doped ceria(CGO)electrodes(a typical MIEC electrode)based on the quantitative analyses and a novel Ni/CGO fiber-matrix structure is proposed and fabricated by combining electrospinning and tape-casting methods using commercial powders.With only 11.5 vol%nickel,the designer Ni/CGO fiber-matrix electrode shows 32%and 67%lower polarization resistance than a nano-Ni impregnated CGO scaffold electrode and conventional cermet electrode respectively.The results in this paper demonstrate quantitatively using real electrode structures that enhancing DPB and hydrogen kinetics are more efficient strategies to enhance electrode performance than simply increasing TPB.
