As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imagi...As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and extraction.Tested on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and reliability.Its robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.展开更多
Flexible Zn-based batteries have attracted increasing research interest as essential components of wearable energy storage devices.However,the advancement of flexible aqueous Zn-based batteries based on Co-Ni layered ...Flexible Zn-based batteries have attracted increasing research interest as essential components of wearable energy storage devices.However,the advancement of flexible aqueous Zn-based batteries based on Co-Ni layered double hydroxide (CoNi-LDH) as the cathode material is hampered by their poor cycling stability and the corrosiveness of alkaline electrolytes.Herein,CoNi-LDH nanosheets enriched with H vacancies (CoNi-LDH(v)) were constructed on a flexible carbon cloth (CC) substrate via electrochemical deposition and activation.The Zn-based battery comprising CoNi-LDH(v)@CC as the cathode exhibited highly reversible conversion reactions and stable operation in 3 M ZnSO4electrolyte (pH=4).The battery delivered an excellent specific capacity (225 mA h g^(-1),0.26 mA h cm^(-2)),acceptable cycling stability(53.9%,900 cycles),and high discharging voltage.The abundant H vacancies served as active sites for the reversible intercalation of Zn^(2+)and the extravasation of NO_(3)-generated channels and space for Zn^(2+)transport and storage,together enabling an excellent Zn^(2+)storage capacity.Furthermore,a sandwich-structured solid-state CoNi-LDH(v)@CC//Zn@CC battery was fabricated and was found to exhibit a noteworthy electrochemical performance and mechanical durability.As a proof of concept,the unencapsulated battery powered a digital watch under various deformation conditions and operated stably for 80 h.Additionally,the flexible battery displayed outstanding customizability,maintaining an open-circuit voltage of 1.42 V even after being cut twice.The proposed engineering strategy contributes to the realization of textiles with truly wearable energy-storage devices.展开更多
The risk of flammability is an unavoidable issue for gel polymer electrolytes(GPEs).Usually,flameretardant solvents are necessary to be used,but most of them would react with anode/cathode easily and cause serious int...The risk of flammability is an unavoidable issue for gel polymer electrolytes(GPEs).Usually,flameretardant solvents are necessary to be used,but most of them would react with anode/cathode easily and cause serious interfacial instability,which is a big challenge for design and application of nonflammable GPEs.Here,a nonflammable GPE(SGPE)is developed by in situ polymerizing trifluoroethyl methacrylate(TFMA)monomers with flame-retardant triethyl phosphate(TEP)solvents and LiTFSI–LiDFOB dual lithium salts.TEP is strongly anchored to PTFMA matrix via polarity interaction between-P=O and-CH_(2)CF_(3).It reduces free TEP molecules,which obviously mitigates interfacial reactions,and enhances flame-retardant performance of TEP surprisingly.Anchored TEP molecules are also inhibited in solvation of Li^(+),leading to anion-dominated solvation sheath,which creates inorganic-rich solid electrolyte interface/cathode electrolyte interface layers.Such coordination structure changes Li^(+)transport from sluggish vehicular to fast structural transport,raising ionic conductivity to 1.03 mS cm^(-1) and transfer number to 0.41 at 30℃.The Li|SGPE|Li cell presents highly reversible Li stripping/plating performance for over 1000 h at 0.1 mA cm^(−2),and 4.2 V LiCoO_(2)|SGPE|Li battery delivers high average specific capacity>120 mAh g^(−1) over 200 cycles.This study paves a new way to make nonflammable GPE that is compatible with Li metal anode.展开更多
Regulation the electronic density of solid-state electrolyte by donor–acceptor(D–A)system can achieve highly-selective Li^(+)transportation and conduction in solid-state Li metal batteries.This study reports a high-...Regulation the electronic density of solid-state electrolyte by donor–acceptor(D–A)system can achieve highly-selective Li^(+)transportation and conduction in solid-state Li metal batteries.This study reports a high-performance solid-state electrolyte thorough D–A-linked covalent organic frameworks(COFs)based on intramolecular charge transfer interactions.Unlike other reported COFbased solid-state electrolyte,the developed concept with D–A-linked COFs not only achieves electronic modulation to promote highly-selective Li^(+)migration and inhibit Li dendrite,but also offers a crucial opportunity to understand the role of electronic density in solid-state Li metal batteries.The introduced strong electronegativity F-based ligand in COF electrolyte results in highlyselective Li^(+)(transference number 0.83),high ionic conductivity(6.7×10^(-4)S cm^(−1)),excellent cyclic ability(1000 h)in Li metal symmetric cell and high-capacity retention in Li/LiFePO_(4)cell(90.8%for 300 cycles at 5C)than substituted C-and N-based ligands.This is ascribed to outstanding D–A interaction between donor porphyrin and acceptor F atoms,which effectively expedites electron transferring from porphyrin to F-based ligand and enhances Li^(+)kinetics.Consequently,we anticipate that this work creates insight into the strategy for accelerating Li^(+)conduction in high-performance solid-state Li metal batteries through D–A system.展开更多
The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational per...The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.展开更多
Combining water electrolysis and rechargeable battery technologies into a single system holds great promise for the co-production of hydrogen (H_(2)) and electricity.However,the design and development of such systems ...Combining water electrolysis and rechargeable battery technologies into a single system holds great promise for the co-production of hydrogen (H_(2)) and electricity.However,the design and development of such systems is still in its infancy.Herein,an integrated hydrogen-oxygen (O_(2))-electricity co-production system featuring a bipolar membrane-assisted decoupled electrolyzer and a Na-Zn ion battery was established with sodium nickelhexacyanoferrate (NaNiHCF) and Zn^(2+)/Zn as dual redox electrodes.The decoupled electrolyzer enables to produce H_(2)and O_(2)in different time and space with almost 100%Faradaic efficiency at 100 mA cm^(-2).Then,the charged NaNiHCF and Zn electrodes after the electrolysis processes formed a Na-Zn ion battery,which can generate electricity with an average cell voltage of 1.75 V at 10 m A cm^(-2).By connecting Si photovoltaics with the modular electrochemical device,a well-matched solar driven system was built to convert the intermittent solar energy into hydrogen and electric energy with a solar to hydrogen-electricity efficiency of 16.7%,demonstrating the flexible storage and conversion of renewables.展开更多
The growth of dendrites and the side reactions occurring at the Zn anode pose significant challenges to the commercialization of aqueous Zn-ion batteries(AZIBs). These challenges arise from the inherent conflict betwe...The growth of dendrites and the side reactions occurring at the Zn anode pose significant challenges to the commercialization of aqueous Zn-ion batteries(AZIBs). These challenges arise from the inherent conflict between mass transfer and electrochemical kinetics. In this study, we propose the use of a multifunctional electrolyte additive based on the xylose(Xylo) molecule to address these issues by modulating the solvation structure and electrode/electrolyte interface, thereby stabilizing the Zn anode. The introduction of the additive alters the solvation structure, creating steric hindrance that impedes charge transfer and then reduces electrochemical kinetics. Furthermore, in-situ analyses demonstrate that the reconstructed electrode/electrolyte interface facilitates stable and rapid Zn^(2+)ion migration and suppresses corrosion and hydrogen evolution reactions. As a result, symmetric cells incorporating the Xylo additive exhibit significantly enhanced reversibility during the Zn plating/stripping process, with an impressively long lifespan of up to 1986 h, compared to cells using pure ZnSO4electrolyte. When combined with a polyaniline cathode, the full cells demonstrate improved capacity and long-term cyclic stability. This work offers an effective direction for improving the stability of Zn anode via electrolyte design, as well as highperformance AZIBs.展开更多
Aqueous Ni-Zn microbatteries are safe,reliable and inexpensive but notoriously suffer from inadequate energy and power densities.Herein,we present a novel mechanism of superoxide-activated Ni substrate that realizes t...Aqueous Ni-Zn microbatteries are safe,reliable and inexpensive but notoriously suffer from inadequate energy and power densities.Herein,we present a novel mechanism of superoxide-activated Ni substrate that realizes the redox reaction featuring three-electron transfers(Ni↔Ni3+).The superoxide activates the direct redox reaction between Ni substrate and KNiO_(2)by lowering the reaction Gibbs free energy,supported by in-situ Raman and density functional theory simulations.The prepared chronopotentiostatic superoxidation-activated Ni(CPS-Ni)electrodes exhibit an ultrahigh capacity of 3.21 mAh cm^(-2)at the current density of 5 mA cm^(-2),nearly 8 times that of traditional one-electron processes electrodes.Even under the ultrahigh 200 mA cm^(-2)current density,the CPS-Ni electrodes show 86.4%capacity retention with a Columbic efficiency of 99.2%after 10,000 cycles.The CPS-Ni||Zn microbattery achieves an exceptional energy density of 6.88 mWh cm^(-2)and power density of 339.56 mW cm^(-2).Device demonstration shows that the power source can continuously operate for more than 7 days in powering the sensing and computation intensive practical application of photoplethysmographic waveform monitoring.This work paves the way to the development of multi-electron transfer mechanisms for advanced aqueous Ni-Zn batteries with high capacity and long lifetime.展开更多
Efficient and stable photocathodes with versatility are of significance in photoassisted lithium-ion batteries(PLIBs),while there is always a request on fast carrier transport in electrochemical active photocathodes.P...Efficient and stable photocathodes with versatility are of significance in photoassisted lithium-ion batteries(PLIBs),while there is always a request on fast carrier transport in electrochemical active photocathodes.Present work proposes a general approach of creating bulk heterojunction to boost the carrier mobility of photocathodes by simply laser assisted embedding of plasmonic nanocrystals.When employed in PLIBs,it was found effective for synchronously enhanced photocharge separation and transport in light charging process.Additionally,experimental photon spectroscopy,finite difference time domain method simulation and theoretical analyses demonstrate that the improved carrier dynamics are driven by the plasmonic-induced hot electron injection from metal to TiO_(2),as well as the enhanced conductivity in TiO2 matrix due to the formation of oxygen vacancies after Schottky contact.Benefiting from these merits,several benchmark values in performance of TiO2-based photocathode applied in PLIBs are set,including the capacity of 276 mAh g^(−1) at 0.2 A g^(−1) under illumination,photoconversion efficiency of 1.276%at 3 A g^(−1),less capacity and Columbic efficiency loss even through 200 cycles.These results exemplify the potential of the bulk heterojunction strategy in developing highly efficient and stable photoassisted energy storage systems.展开更多
Amidst the ever-growing interest in high-mass-loading Li battery electrodes,a persistent challenge has been the insufficient continuity of their ion/electron conduction pathways.Here,we propose cellulose elementary fi...Amidst the ever-growing interest in high-mass-loading Li battery electrodes,a persistent challenge has been the insufficient continuity of their ion/electron conduction pathways.Here,we propose cellulose elementary fibrils(CEFs)as a class of deagglomerated binder for high-mass-loading electrodes.Derived from natural wood,CEF represents the most fundamental unit of cellulose with nanoscale diameter.The preparation of the CEFs involves the modulation of intermolecular hydrogen bonding by the treatment with a proton acceptor and a hydrotropic agent.This elementary deagglomeration of the cellulose fibers increases surface area and anionic charge density,thus promoting uniform dispersion with carbon conductive additives and suppressing interfacial side reactions at electrodes.Consequently,a homogeneous redox reaction is achieved throughout the electrodes.The resulting CEF-based cathode(overlithiated layered oxide(OLO)is chosen as a benchmark electrode active material)exhibits a high areal-mass-loading(50 mg cm^(-2),equivalent to an areal capacity of 12.5 mAh cm^(-2))and a high specific energy density(445.4 Wh kg–1)of a cell,which far exceeds those of previously reported OLO cathodes.This study highlights the viability of the deagglomerated binder in enabling sustainable high-mass-loading electrodes that are difficult to achieve with conventional synthetic polymer binders.展开更多
Thermal runaway(TR)is a critical issue hindering the large-scale application of lithium-ion batteries(LIBs).Understanding the thermal safety behavior of LIBs at the cell and module level under different state of charg...Thermal runaway(TR)is a critical issue hindering the large-scale application of lithium-ion batteries(LIBs).Understanding the thermal safety behavior of LIBs at the cell and module level under different state of charges(SOCs)has significant implications for reinforcing the thermal safety design of the lithium-ion battery module.This study first investigates the thermal safety boundary(TSB)correspondence at the cells and modules level under the guidance of a newly proposed concept,safe electric quantity boundary(SEQB).A reasonable thermal runaway propagation(TRP)judgment indicator,peak heat transfer power(PHTP),is proposed to predict whether TRP occurs.Moreover,a validated 3D model is used to quantitatively clarify the TSB at different SOCs from the perspective of PHTP,TR trigger temperature,SOC,and the full cycle life.Besides,three different TRP transfer modes are discovered.The interconversion relationship of three different TRP modes is investigated from the perspective of PHTP.This paper explores the TSB of LIBs under different SOCs at both cell and module levels for the first time,which has great significance in guiding the thermal safety design of battery systems.展开更多
With the increasing attention paid to battery technology,the microscopic reaction mechanism and macroscopic heat transfer process of lithium-ion batteries have been further studied and understood from both academic an...With the increasing attention paid to battery technology,the microscopic reaction mechanism and macroscopic heat transfer process of lithium-ion batteries have been further studied and understood from both academic and industrial perspectives.Temperature,as one of the key parameters in the physical fra mework of batteries,affects the performa nce of the multi-physical fields within the battery,a nd its effective control is crucial.Since the heat generation in the battery is determined by the real-time operating conditions,the battery temperature is essentially controlled by the real-time heat dissipation conditions provided by the battery thermal management system.Conventional battery thermal management systems have basic temperature control capabilities for most conventional application scenarios.However,with the current development of la rge-scale,integrated,and intelligent battery technology,the adva ncement of battery thermal management technology will pay more attention to the effective control of battery temperature under sophisticated situations,such as high power and widely varied operating conditions.In this context,this paper presents the latest advances and representative research related to battery thermal management system.Firstly,starting from battery thermal profile,the mechanism of battery heat generation is discussed in detail.Secondly,the static characteristics of the traditional battery thermal management system are summarized.Then,considering the dynamic requirements of battery heat dissipation under complex operating conditions,the concept of adaptive battery thermal management system is proposed based on specific research cases.Finally,the main challenges for battery thermal management system in practice are identified,and potential future developments to overcome these challenges are presented and discussed.展开更多
Cell-to-cell variations(CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack's fast-charging performance remain unexplored. ...Cell-to-cell variations(CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack's fast-charging performance remain unexplored. This knowledge gap is vital for the proliferation of electric vehicles. This study underlies the relationship between CtCV and charging performance by assessing the pack's charge speed, final electric quantity, and temperature consistency. Cell variations and pack status are depicted using 2D parameter diagrams, and an m PnS configured pack model is built upon a decomposed electrode cell model.Variations in three single electric parameters, i.e., capacity(Q), electric quantity(E), and internal resistance(R), and their dual interactions, i.e., E-Q and R-Q, are analyzed carefully. The results indicate that Q variations predominantly affect the final electric quantity of the pack, while R variations impact the charge speed most. With incremental variances in cell parameters, the pack's fast-charging capability first declines linearly and then deteriorates sharply as variations intensify. This research elucidates the correlations between pack charging capabilities and cell variations, providing essential insights for optimizing cell sorting and assembly, battery management design, and charging protocol development for battery packs.展开更多
Magnesium ion batteries(MIBs)are a potential field for the energy storage of the future but are restricted by insufficient rate capability and rapid capacity degradation.Magnesium-sodium hybrid ion batteries(MSHBs)are...Magnesium ion batteries(MIBs)are a potential field for the energy storage of the future but are restricted by insufficient rate capability and rapid capacity degradation.Magnesium-sodium hybrid ion batteries(MSHBs)are an effective way to address these problems.Here,we report a new type of MSHBs that use layered sodium vanadate((Na,Mn)V_(8)O_(20)·5H_(2)O,Mn-NVO)cathodes coupled with an organic 3,4,9,10-perylenetetracarboxylic diimide(PTCDI)anode in Mg^(2+)/Na^(+)hybrid electrolytes.During electrochemical cycling,Mg^(2+)and Na^(+)co-participate in the cathode reactions,and the introduction of Na^(+)promotes the structural stability of the Mn-NVO cathode,as cleared by several ex-situ characterizations.Consequently,the Mn-NVO cathode presents great specific capacity(249.9 mA h g^(−1)at 300 mA g^(−1))and cycling(1500 cycles at 1500 mA g^(−1))in the Mg^(2+)/Na^(+)hybrid electrolytes.Besides,full battery displays long lifespan with 10,000 cycles at 1000 mA g^(−1).The rate performance and cycling stability of MSHBs have been improved by an economical and scalable method,and the mechanism for these improvements is discussed.展开更多
The development of aqueous battery with dual mechanisms is now arousing more and more interest.The dual mechanisms of Zn^(2+)(de)intercalation and I^(-)/I_(2)redox bring unexpected effects.Herein,differing from previo...The development of aqueous battery with dual mechanisms is now arousing more and more interest.The dual mechanisms of Zn^(2+)(de)intercalation and I^(-)/I_(2)redox bring unexpected effects.Herein,differing from previous studies using Zn I_(2)additive,this work designs an aqueous Bi I_(3)-Zn battery with selfsupplied I^(-).Ex situ tests reveal the conversion of Bi I_(3)into Bi(discharge)and Bi OI(charge)at the 1st cycle and the dissolved I^(-)in electrolyte.The active I^(-)species enhances the specific capacity and discharge medium voltage of electrode as well as improves the generation of Zn dendrite and by-product.Furthermore,the porous hard carbon is introduced to enhance the electronic/ionic conductivity and adsorb iodine species,proven by experimental and theoretical studies.Accordingly,the well-designed Bi I_(3)-Zn battery delivers a high reversible capacity of 182 m A h g^(-1)at 0.2 A g^(-1),an excellent rate capability with 88 m A h g^(-1)at 10 A g^(-1),and an impressive cyclability with 63%capacity retention over 20 K cycles at 10 A g^(-1).An excellent electrochemical performance is obtained even at a high mass loading of 6 mg cm^(-2).Moreover,a flexible quasi-solid-state Bi I_(3)-Zn battery exhibits satisfactory battery performances.This work provides a new idea for designing high-performance aqueous battery with dual mechanisms.展开更多
Lithium-ion battery(LIB) industry seems to have met its bottle neck in cutting down producing costs even though much efforts have been put into building a complete industrial chain. Actually, manufacturing methods can...Lithium-ion battery(LIB) industry seems to have met its bottle neck in cutting down producing costs even though much efforts have been put into building a complete industrial chain. Actually, manufacturing methods can greatly affect the cost of battery production. Up to now, lithium ion battery producers still adopt manufacturing methods with cumbersome sub-components preparing processes and costly assembling procedures, which will undoubtedly elevate the producing cost. Herein, we propose a novel approach to directly assemble battery components(cathode, anode and separator) in an integrated way using electro-spraying and electro-spinning technologies. More importantly, this novel battery manufacturing method can produce LIBs in large scale, and the products show excellent mechanical strength, flexibility, thermal stability and electrolyte wettability. Additionally, the performance of the as-prepaed Li Fe PO_(4)||graphite full cell produced by this new method is comparable or even better than that produced by conventional manufacturing approach. In brief, this work provides a new promising technology to prepare LIBs with low cost and better performance.展开更多
Lithium-ion batteries(LIBs)featuring a Ni-rich cathode exhibit increased specific capacity,but the establishment of a stable interphase through the implementation of a functional electrolyte strategy remains challengi...Lithium-ion batteries(LIBs)featuring a Ni-rich cathode exhibit increased specific capacity,but the establishment of a stable interphase through the implementation of a functional electrolyte strategy remains challenging.Especially when the battery is operated under high temperature,the trace water present in the electrolyte will accelerate the hydrolysis of the electrolyte and the resulting HF will further erode the interphase.In order to enhance the long-term cycling performance of graphite/LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)(NCM811)LIBs,herein,Tolylene-2,4-diisocyanate(TDI)additive containing lone-pair electrons is employed to formulate a novel bifunctional electrolyte aimed at eliminating H_(2)O/HF generated at elevated temperature.After 1000 cycles at 25℃,the battery incorporating the TDI-containing electrolyte exhibits an impressive capacity retention of 94%at 1 C.In contrast,the battery utilizing the blank electrolyte has a lower capacity retention of only 78%.Furthermore,after undergoing 550 cycles at 1 C under45℃,the inclusion of TDI results in a notable enhancement of capacity,increasing it from 68%to 80%.This indicates TDI has a favorable influence on the cycling performance of LIBs,especially at elevated temperatures.The analysis of the film formation mechanism suggests that the lone pair of electrons of the isocyanate group in TDI play a crucial role in inhibiting the generation of H_(2)O and HF,which leads to the formation of a thin and dense interphase.The existence of this interphase is thought to substantially enhance the cycling performance of the LIBs.This work not only improves the performance of graphite/NCM811 batteries at room temperature and high temperature by eliminating H_(2)O/HF but also presents a novel strategy for advancing functional electrolyte development.展开更多
The reliable prediction of state of charge(SOC)is one of the vital functions of advanced battery management system(BMS),which has great significance towards safe operation of electric vehicles.By far,the empirical mod...The reliable prediction of state of charge(SOC)is one of the vital functions of advanced battery management system(BMS),which has great significance towards safe operation of electric vehicles.By far,the empirical model-based and data-driven-based SOC estimation methods of lithium-ion batteries have been comprehensively discussed and reviewed in various literatures.However,few reviews involving SOC estimation focused on electrochemical mechanism,which gives physical explanations to SOC and becomes most attractive candidate for advanced BMS.For this reason,this paper comprehensively surveys on physics-based SOC algorithms applied in advanced BMS.First,the research progresses of physical SOC estimation methods for lithium-ion batteries are thoroughly discussed and corresponding evaluation criteria are carefully elaborated.Second,future perspectives of the current researches on physics-based battery SOC estimation are presented.The insights stated in this paper are expected to catalyze the development and application of the physics-based advanced BMS algorithms.展开更多
Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical ener...Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.展开更多
With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair compar...With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.展开更多
基金National Natural Science Foundation of China (Grant No. 52225705)。
文摘As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and extraction.Tested on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and reliability.Its robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.
基金National Natural Science Foundation of China (52003191,5247317, 52473275)Young Elite Scientists Sponsorship Program by CAST (2022QNRC001)+3 种基金Natural Science Foundation of Jiangsu Province (BK20221539)Postgraduate Research&Practice Innovation Program of Jiangsu Province (KYCX22_2341)Program of Introducing Talents of Jiangnan University (1065219032210150)Program of China Scholarship Council (202306790065)。
文摘Flexible Zn-based batteries have attracted increasing research interest as essential components of wearable energy storage devices.However,the advancement of flexible aqueous Zn-based batteries based on Co-Ni layered double hydroxide (CoNi-LDH) as the cathode material is hampered by their poor cycling stability and the corrosiveness of alkaline electrolytes.Herein,CoNi-LDH nanosheets enriched with H vacancies (CoNi-LDH(v)) were constructed on a flexible carbon cloth (CC) substrate via electrochemical deposition and activation.The Zn-based battery comprising CoNi-LDH(v)@CC as the cathode exhibited highly reversible conversion reactions and stable operation in 3 M ZnSO4electrolyte (pH=4).The battery delivered an excellent specific capacity (225 mA h g^(-1),0.26 mA h cm^(-2)),acceptable cycling stability(53.9%,900 cycles),and high discharging voltage.The abundant H vacancies served as active sites for the reversible intercalation of Zn^(2+)and the extravasation of NO_(3)-generated channels and space for Zn^(2+)transport and storage,together enabling an excellent Zn^(2+)storage capacity.Furthermore,a sandwich-structured solid-state CoNi-LDH(v)@CC//Zn@CC battery was fabricated and was found to exhibit a noteworthy electrochemical performance and mechanical durability.As a proof of concept,the unencapsulated battery powered a digital watch under various deformation conditions and operated stably for 80 h.Additionally,the flexible battery displayed outstanding customizability,maintaining an open-circuit voltage of 1.42 V even after being cut twice.The proposed engineering strategy contributes to the realization of textiles with truly wearable energy-storage devices.
基金supported by the National Natural Science Foundation of China(Nos.52172214,52272221,52171182)the Postdoctoral Innovation Project of Shandong Province(No.202102003)+2 种基金The Key Research and Development Program of Shandong Province(2021ZLGX01)the Qilu Young Scholar ProgramHPC Cloud Platform of Shandong University are also thanked.
文摘The risk of flammability is an unavoidable issue for gel polymer electrolytes(GPEs).Usually,flameretardant solvents are necessary to be used,but most of them would react with anode/cathode easily and cause serious interfacial instability,which is a big challenge for design and application of nonflammable GPEs.Here,a nonflammable GPE(SGPE)is developed by in situ polymerizing trifluoroethyl methacrylate(TFMA)monomers with flame-retardant triethyl phosphate(TEP)solvents and LiTFSI–LiDFOB dual lithium salts.TEP is strongly anchored to PTFMA matrix via polarity interaction between-P=O and-CH_(2)CF_(3).It reduces free TEP molecules,which obviously mitigates interfacial reactions,and enhances flame-retardant performance of TEP surprisingly.Anchored TEP molecules are also inhibited in solvation of Li^(+),leading to anion-dominated solvation sheath,which creates inorganic-rich solid electrolyte interface/cathode electrolyte interface layers.Such coordination structure changes Li^(+)transport from sluggish vehicular to fast structural transport,raising ionic conductivity to 1.03 mS cm^(-1) and transfer number to 0.41 at 30℃.The Li|SGPE|Li cell presents highly reversible Li stripping/plating performance for over 1000 h at 0.1 mA cm^(−2),and 4.2 V LiCoO_(2)|SGPE|Li battery delivers high average specific capacity>120 mAh g^(−1) over 200 cycles.This study paves a new way to make nonflammable GPE that is compatible with Li metal anode.
基金financial support provided by National Natural Science Foundation of China(52303283,52372232,52064049)the Major Science and Technology Projects of Yunnan Province(202302AB080019-3)+2 种基金National Natural Science Foundation of Yunnan Province(202301AS070040,202401AU070201)the Analysis and Measurements Center of Yunnan University for the sample testing servicethe Electron Microscope Center of Yunnan University for the support of this work.
文摘Regulation the electronic density of solid-state electrolyte by donor–acceptor(D–A)system can achieve highly-selective Li^(+)transportation and conduction in solid-state Li metal batteries.This study reports a high-performance solid-state electrolyte thorough D–A-linked covalent organic frameworks(COFs)based on intramolecular charge transfer interactions.Unlike other reported COFbased solid-state electrolyte,the developed concept with D–A-linked COFs not only achieves electronic modulation to promote highly-selective Li^(+)migration and inhibit Li dendrite,but also offers a crucial opportunity to understand the role of electronic density in solid-state Li metal batteries.The introduced strong electronegativity F-based ligand in COF electrolyte results in highlyselective Li^(+)(transference number 0.83),high ionic conductivity(6.7×10^(-4)S cm^(−1)),excellent cyclic ability(1000 h)in Li metal symmetric cell and high-capacity retention in Li/LiFePO_(4)cell(90.8%for 300 cycles at 5C)than substituted C-and N-based ligands.This is ascribed to outstanding D–A interaction between donor porphyrin and acceptor F atoms,which effectively expedites electron transferring from porphyrin to F-based ligand and enhances Li^(+)kinetics.Consequently,we anticipate that this work creates insight into the strategy for accelerating Li^(+)conduction in high-performance solid-state Li metal batteries through D–A system.
基金National Natural Science Foundation of China (52075420)Fundamental Research Funds for the Central Universities (xzy022023049)National Key Research and Development Program of China (2023YFB3408600)。
文摘The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.
基金National Natural Science Foundation of China (Nos. 52488201, 52076177, and 52476222)China National Key Research and Development Plan Project (No. 2021YFF0500503)+1 种基金Key Research and Development Program of Shaanxi (No. 2024GH-YBXM-02)China Fundamental Research Funds for the Central Universities。
文摘Combining water electrolysis and rechargeable battery technologies into a single system holds great promise for the co-production of hydrogen (H_(2)) and electricity.However,the design and development of such systems is still in its infancy.Herein,an integrated hydrogen-oxygen (O_(2))-electricity co-production system featuring a bipolar membrane-assisted decoupled electrolyzer and a Na-Zn ion battery was established with sodium nickelhexacyanoferrate (NaNiHCF) and Zn^(2+)/Zn as dual redox electrodes.The decoupled electrolyzer enables to produce H_(2)and O_(2)in different time and space with almost 100%Faradaic efficiency at 100 mA cm^(-2).Then,the charged NaNiHCF and Zn electrodes after the electrolysis processes formed a Na-Zn ion battery,which can generate electricity with an average cell voltage of 1.75 V at 10 m A cm^(-2).By connecting Si photovoltaics with the modular electrochemical device,a well-matched solar driven system was built to convert the intermittent solar energy into hydrogen and electric energy with a solar to hydrogen-electricity efficiency of 16.7%,demonstrating the flexible storage and conversion of renewables.
文摘The growth of dendrites and the side reactions occurring at the Zn anode pose significant challenges to the commercialization of aqueous Zn-ion batteries(AZIBs). These challenges arise from the inherent conflict between mass transfer and electrochemical kinetics. In this study, we propose the use of a multifunctional electrolyte additive based on the xylose(Xylo) molecule to address these issues by modulating the solvation structure and electrode/electrolyte interface, thereby stabilizing the Zn anode. The introduction of the additive alters the solvation structure, creating steric hindrance that impedes charge transfer and then reduces electrochemical kinetics. Furthermore, in-situ analyses demonstrate that the reconstructed electrode/electrolyte interface facilitates stable and rapid Zn^(2+)ion migration and suppresses corrosion and hydrogen evolution reactions. As a result, symmetric cells incorporating the Xylo additive exhibit significantly enhanced reversibility during the Zn plating/stripping process, with an impressively long lifespan of up to 1986 h, compared to cells using pure ZnSO4electrolyte. When combined with a polyaniline cathode, the full cells demonstrate improved capacity and long-term cyclic stability. This work offers an effective direction for improving the stability of Zn anode via electrolyte design, as well as highperformance AZIBs.
基金supported by InnoHK Project at Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE)City University of Hong Kong (7006108)。
文摘Aqueous Ni-Zn microbatteries are safe,reliable and inexpensive but notoriously suffer from inadequate energy and power densities.Herein,we present a novel mechanism of superoxide-activated Ni substrate that realizes the redox reaction featuring three-electron transfers(Ni↔Ni3+).The superoxide activates the direct redox reaction between Ni substrate and KNiO_(2)by lowering the reaction Gibbs free energy,supported by in-situ Raman and density functional theory simulations.The prepared chronopotentiostatic superoxidation-activated Ni(CPS-Ni)electrodes exhibit an ultrahigh capacity of 3.21 mAh cm^(-2)at the current density of 5 mA cm^(-2),nearly 8 times that of traditional one-electron processes electrodes.Even under the ultrahigh 200 mA cm^(-2)current density,the CPS-Ni electrodes show 86.4%capacity retention with a Columbic efficiency of 99.2%after 10,000 cycles.The CPS-Ni||Zn microbattery achieves an exceptional energy density of 6.88 mWh cm^(-2)and power density of 339.56 mW cm^(-2).Device demonstration shows that the power source can continuously operate for more than 7 days in powering the sensing and computation intensive practical application of photoplethysmographic waveform monitoring.This work paves the way to the development of multi-electron transfer mechanisms for advanced aqueous Ni-Zn batteries with high capacity and long lifetime.
基金supported by the project of the National Natural Science Foundation of China(52202115 and 52172101)Guangdong Basic and Applied Basic Research Foundation(2024A1515012325)+2 种基金the Natural Science Foundation of Chongqing,China(CSTB2022NSCQ-MSX1085)the Shaanxi Science and Technology Innovation Team(2023-CXTD-44)the Fundamental Research Funds for the Central Universities(G2022KY0604).
文摘Efficient and stable photocathodes with versatility are of significance in photoassisted lithium-ion batteries(PLIBs),while there is always a request on fast carrier transport in electrochemical active photocathodes.Present work proposes a general approach of creating bulk heterojunction to boost the carrier mobility of photocathodes by simply laser assisted embedding of plasmonic nanocrystals.When employed in PLIBs,it was found effective for synchronously enhanced photocharge separation and transport in light charging process.Additionally,experimental photon spectroscopy,finite difference time domain method simulation and theoretical analyses demonstrate that the improved carrier dynamics are driven by the plasmonic-induced hot electron injection from metal to TiO_(2),as well as the enhanced conductivity in TiO2 matrix due to the formation of oxygen vacancies after Schottky contact.Benefiting from these merits,several benchmark values in performance of TiO2-based photocathode applied in PLIBs are set,including the capacity of 276 mAh g^(−1) at 0.2 A g^(−1) under illumination,photoconversion efficiency of 1.276%at 3 A g^(−1),less capacity and Columbic efficiency loss even through 200 cycles.These results exemplify the potential of the bulk heterojunction strategy in developing highly efficient and stable photoassisted energy storage systems.
基金supported by the Institute of Civil Military Technology Cooperation funded by the Defense Acquisition Program Administration and Ministry of Trade,Industry and Energy of Korean government under grant No 23-CM-AI-08.
文摘Amidst the ever-growing interest in high-mass-loading Li battery electrodes,a persistent challenge has been the insufficient continuity of their ion/electron conduction pathways.Here,we propose cellulose elementary fibrils(CEFs)as a class of deagglomerated binder for high-mass-loading electrodes.Derived from natural wood,CEF represents the most fundamental unit of cellulose with nanoscale diameter.The preparation of the CEFs involves the modulation of intermolecular hydrogen bonding by the treatment with a proton acceptor and a hydrotropic agent.This elementary deagglomeration of the cellulose fibers increases surface area and anionic charge density,thus promoting uniform dispersion with carbon conductive additives and suppressing interfacial side reactions at electrodes.Consequently,a homogeneous redox reaction is achieved throughout the electrodes.The resulting CEF-based cathode(overlithiated layered oxide(OLO)is chosen as a benchmark electrode active material)exhibits a high areal-mass-loading(50 mg cm^(-2),equivalent to an areal capacity of 12.5 mAh cm^(-2))and a high specific energy density(445.4 Wh kg–1)of a cell,which far exceeds those of previously reported OLO cathodes.This study highlights the viability of the deagglomerated binder in enabling sustainable high-mass-loading electrodes that are difficult to achieve with conventional synthetic polymer binders.
基金supported by the National Natural Science Foundation of China(No.U20A20310 and No.52176199)sponsored by the Program of Shanghai Academic/Technology Research Leader(No.22XD1423800)。
文摘Thermal runaway(TR)is a critical issue hindering the large-scale application of lithium-ion batteries(LIBs).Understanding the thermal safety behavior of LIBs at the cell and module level under different state of charges(SOCs)has significant implications for reinforcing the thermal safety design of the lithium-ion battery module.This study first investigates the thermal safety boundary(TSB)correspondence at the cells and modules level under the guidance of a newly proposed concept,safe electric quantity boundary(SEQB).A reasonable thermal runaway propagation(TRP)judgment indicator,peak heat transfer power(PHTP),is proposed to predict whether TRP occurs.Moreover,a validated 3D model is used to quantitatively clarify the TSB at different SOCs from the perspective of PHTP,TR trigger temperature,SOC,and the full cycle life.Besides,three different TRP transfer modes are discovered.The interconversion relationship of three different TRP modes is investigated from the perspective of PHTP.This paper explores the TSB of LIBs under different SOCs at both cell and module levels for the first time,which has great significance in guiding the thermal safety design of battery systems.
基金supported by the National Natural Science Foundation of China (No.62373224,62333013,and U23A20327)。
文摘With the increasing attention paid to battery technology,the microscopic reaction mechanism and macroscopic heat transfer process of lithium-ion batteries have been further studied and understood from both academic and industrial perspectives.Temperature,as one of the key parameters in the physical fra mework of batteries,affects the performa nce of the multi-physical fields within the battery,a nd its effective control is crucial.Since the heat generation in the battery is determined by the real-time operating conditions,the battery temperature is essentially controlled by the real-time heat dissipation conditions provided by the battery thermal management system.Conventional battery thermal management systems have basic temperature control capabilities for most conventional application scenarios.However,with the current development of la rge-scale,integrated,and intelligent battery technology,the adva ncement of battery thermal management technology will pay more attention to the effective control of battery temperature under sophisticated situations,such as high power and widely varied operating conditions.In this context,this paper presents the latest advances and representative research related to battery thermal management system.Firstly,starting from battery thermal profile,the mechanism of battery heat generation is discussed in detail.Secondly,the static characteristics of the traditional battery thermal management system are summarized.Then,considering the dynamic requirements of battery heat dissipation under complex operating conditions,the concept of adaptive battery thermal management system is proposed based on specific research cases.Finally,the main challenges for battery thermal management system in practice are identified,and potential future developments to overcome these challenges are presented and discussed.
基金supported by the National Natural Science Foundation of China under No. 52177217the Postdoctoral Innovative Talents Support Program under No. BX20240232。
文摘Cell-to-cell variations(CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack's fast-charging performance remain unexplored. This knowledge gap is vital for the proliferation of electric vehicles. This study underlies the relationship between CtCV and charging performance by assessing the pack's charge speed, final electric quantity, and temperature consistency. Cell variations and pack status are depicted using 2D parameter diagrams, and an m PnS configured pack model is built upon a decomposed electrode cell model.Variations in three single electric parameters, i.e., capacity(Q), electric quantity(E), and internal resistance(R), and their dual interactions, i.e., E-Q and R-Q, are analyzed carefully. The results indicate that Q variations predominantly affect the final electric quantity of the pack, while R variations impact the charge speed most. With incremental variances in cell parameters, the pack's fast-charging capability first declines linearly and then deteriorates sharply as variations intensify. This research elucidates the correlations between pack charging capabilities and cell variations, providing essential insights for optimizing cell sorting and assembly, battery management design, and charging protocol development for battery packs.
基金the financial support from the National Natural Science Foundation of China, China (22005207, 52261160384)the Guangdong Basic and Applied Basic Research Foundation, Guangdong Province, China (2019A1515011819)+2 种基金the Outstanding Youth Basic Research Project of Shenzhen, Shenzhen, China (RCYX20221008092934093)the Joint Funds of the National Natural Science Foundation of China, China (U22A20140)the Science and Technology Development Fund, Macao SAR (0090/2021/A2 and 0049/2021/AGJ)
文摘Magnesium ion batteries(MIBs)are a potential field for the energy storage of the future but are restricted by insufficient rate capability and rapid capacity degradation.Magnesium-sodium hybrid ion batteries(MSHBs)are an effective way to address these problems.Here,we report a new type of MSHBs that use layered sodium vanadate((Na,Mn)V_(8)O_(20)·5H_(2)O,Mn-NVO)cathodes coupled with an organic 3,4,9,10-perylenetetracarboxylic diimide(PTCDI)anode in Mg^(2+)/Na^(+)hybrid electrolytes.During electrochemical cycling,Mg^(2+)and Na^(+)co-participate in the cathode reactions,and the introduction of Na^(+)promotes the structural stability of the Mn-NVO cathode,as cleared by several ex-situ characterizations.Consequently,the Mn-NVO cathode presents great specific capacity(249.9 mA h g^(−1)at 300 mA g^(−1))and cycling(1500 cycles at 1500 mA g^(−1))in the Mg^(2+)/Na^(+)hybrid electrolytes.Besides,full battery displays long lifespan with 10,000 cycles at 1000 mA g^(−1).The rate performance and cycling stability of MSHBs have been improved by an economical and scalable method,and the mechanism for these improvements is discussed.
基金funding from National Natural Science Foundation of China(52103053,52102312)Huxiang Young Talents of Hunan Province(2022RC1004)+1 种基金Macao Young Scholars Program(AM2021011)Foundation of State Key Laboratory of Utilization of Woody Oil Resource(GZKF202126)。
文摘The development of aqueous battery with dual mechanisms is now arousing more and more interest.The dual mechanisms of Zn^(2+)(de)intercalation and I^(-)/I_(2)redox bring unexpected effects.Herein,differing from previous studies using Zn I_(2)additive,this work designs an aqueous Bi I_(3)-Zn battery with selfsupplied I^(-).Ex situ tests reveal the conversion of Bi I_(3)into Bi(discharge)and Bi OI(charge)at the 1st cycle and the dissolved I^(-)in electrolyte.The active I^(-)species enhances the specific capacity and discharge medium voltage of electrode as well as improves the generation of Zn dendrite and by-product.Furthermore,the porous hard carbon is introduced to enhance the electronic/ionic conductivity and adsorb iodine species,proven by experimental and theoretical studies.Accordingly,the well-designed Bi I_(3)-Zn battery delivers a high reversible capacity of 182 m A h g^(-1)at 0.2 A g^(-1),an excellent rate capability with 88 m A h g^(-1)at 10 A g^(-1),and an impressive cyclability with 63%capacity retention over 20 K cycles at 10 A g^(-1).An excellent electrochemical performance is obtained even at a high mass loading of 6 mg cm^(-2).Moreover,a flexible quasi-solid-state Bi I_(3)-Zn battery exhibits satisfactory battery performances.This work provides a new idea for designing high-performance aqueous battery with dual mechanisms.
基金This work was financially supported by the National Nat-ural Science Foundation of China No.U20A20247 and 51922038.
文摘Lithium-ion battery(LIB) industry seems to have met its bottle neck in cutting down producing costs even though much efforts have been put into building a complete industrial chain. Actually, manufacturing methods can greatly affect the cost of battery production. Up to now, lithium ion battery producers still adopt manufacturing methods with cumbersome sub-components preparing processes and costly assembling procedures, which will undoubtedly elevate the producing cost. Herein, we propose a novel approach to directly assemble battery components(cathode, anode and separator) in an integrated way using electro-spraying and electro-spinning technologies. More importantly, this novel battery manufacturing method can produce LIBs in large scale, and the products show excellent mechanical strength, flexibility, thermal stability and electrolyte wettability. Additionally, the performance of the as-prepaed Li Fe PO_(4)||graphite full cell produced by this new method is comparable or even better than that produced by conventional manufacturing approach. In brief, this work provides a new promising technology to prepare LIBs with low cost and better performance.
基金financially supported by the Scientific and Technological Plan Projects of Guangzhou City(202103040001),P.R.Chinathe Project of Science and Technology Department of Henan Province(222102240074)the Key Research Programs of Higher Education Institutions of Henan Province(24B150009)。
文摘Lithium-ion batteries(LIBs)featuring a Ni-rich cathode exhibit increased specific capacity,but the establishment of a stable interphase through the implementation of a functional electrolyte strategy remains challenging.Especially when the battery is operated under high temperature,the trace water present in the electrolyte will accelerate the hydrolysis of the electrolyte and the resulting HF will further erode the interphase.In order to enhance the long-term cycling performance of graphite/LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)(NCM811)LIBs,herein,Tolylene-2,4-diisocyanate(TDI)additive containing lone-pair electrons is employed to formulate a novel bifunctional electrolyte aimed at eliminating H_(2)O/HF generated at elevated temperature.After 1000 cycles at 25℃,the battery incorporating the TDI-containing electrolyte exhibits an impressive capacity retention of 94%at 1 C.In contrast,the battery utilizing the blank electrolyte has a lower capacity retention of only 78%.Furthermore,after undergoing 550 cycles at 1 C under45℃,the inclusion of TDI results in a notable enhancement of capacity,increasing it from 68%to 80%.This indicates TDI has a favorable influence on the cycling performance of LIBs,especially at elevated temperatures.The analysis of the film formation mechanism suggests that the lone pair of electrons of the isocyanate group in TDI play a crucial role in inhibiting the generation of H_(2)O and HF,which leads to the formation of a thin and dense interphase.The existence of this interphase is thought to substantially enhance the cycling performance of the LIBs.This work not only improves the performance of graphite/NCM811 batteries at room temperature and high temperature by eliminating H_(2)O/HF but also presents a novel strategy for advancing functional electrolyte development.
基金supported by the Open Project of Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle(No.ZDSYS202304)the National Natural Science Foundation of China(No.62303007)the Anhui Provincial Natural Science Foundation(No.2308085ME142)。
文摘The reliable prediction of state of charge(SOC)is one of the vital functions of advanced battery management system(BMS),which has great significance towards safe operation of electric vehicles.By far,the empirical model-based and data-driven-based SOC estimation methods of lithium-ion batteries have been comprehensively discussed and reviewed in various literatures.However,few reviews involving SOC estimation focused on electrochemical mechanism,which gives physical explanations to SOC and becomes most attractive candidate for advanced BMS.For this reason,this paper comprehensively surveys on physics-based SOC algorithms applied in advanced BMS.First,the research progresses of physical SOC estimation methods for lithium-ion batteries are thoroughly discussed and corresponding evaluation criteria are carefully elaborated.Second,future perspectives of the current researches on physics-based battery SOC estimation are presented.The insights stated in this paper are expected to catalyze the development and application of the physics-based advanced BMS algorithms.
基金supported by the National Natural Science Foundation of China(52203364,52188101,52020105010)the National Key R&D Program of China(2021YFB3800300,2022YFB3803400)+2 种基金the Strategic Priority Research Program of Chinese Academy of Science(XDA22010602)the China Postdoctoral Science Foundation(2022M713214)the China National Postdoctoral Program for Innovative Talents(BX2021321)。
文摘Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.
基金supported by the National Natural Science Foundation of China (52075420)the National Key Research and Development Program of China (2020YFB1708400)。
文摘With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.
