Thermal safety boundary of lithium-ion battery at different state of charge

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.

Physics-based battery SOC estimation methods:Recent advances and future perspectives

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.

Small but mighty:Empowering sodium/potassium-ion battery performance with S-doped SnO2 quantum dots embedded in N,S codoped carbon fiber network

SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.

Recent progress and future prospects of high-entropy materials for battery applications

Due to the energy crisis caused by limited fossil fuel reserves,extensive use of the renewable energy sources such as wind or solar energy is deemed to replace the use of traditional fossil fuels in the future^([1−3]).However,most renewable energy sources face the same problem,which is the intermittency of energy.For example,solar energy cannot be utilized at night.That means the continuous energy demand required for large-scale power grids can’t be satisfied by a single solar panel model.

Light-assisted rechargeable zinc-air battery:Mechanism,progress,and prospects

Exploring effective energy storage systems is critical to alleviate energy scarcity.Rechargeable zinc-air batteries are promising energy storage devices.However,conventional rechargeable zinc-air battery systems face many challenges associated with electrolytes and electrodes,causing inferior electrochemistry performance.The light-assisted strategy represents a novel and innovative approach to conventional zinc-air battery technology that uses only electrical energy.This strategy effectively combines both light and electrical energy conversion/storage mechanisms.In addition,light-assisted rechargeable zinc-air batteries can achieve photocharging with or without applied electrical bias by partially using solar energy and the acceleration of oxygen reduction/evolution reaction kinetics.In this paper,the working mechanism and structural design of the light-assisted rechargeable zinc-air batteries are introduced based on the theory of photoelectrochemistry and its characteristics.Then,the latest advances in electrolyte and photocathode design strategies are discussed in detail.The performance enhancement of aqueous light-assisted rechargeable zinc-air batteries using photoelectric materials is explained.Finally,a summary and outlook on the further modification of properties of light-assisted rechargeable zinc-air batteries,especially the photovoltaic electrode catalyst design strategies,are illustrated.This review provides insights and guidance for the design of high-performance light-assisted rechargeable Zn-air batteries for next-generation energy storage devices.

Electro-spraying/spinning: A novel battery manufacturing technology

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.

Review on current development of polybenzimidazole membrane for lithium battery

With the rapid development of portable technology,lithium batteries have emerged as potential candidates for high-performance energy storage systems owing to their high energy density and cycling stability.Among the key components of a lithium battery system,the separator plays a critical role as it directly influences the battery performance benchmark(cycling performance and safety).However,traditional polyolefin separators(polypropylene/polyethylene)are unable to meet the demands of highperformance and safer battery systems due to their poor electrolyte compatibility,thermal runaways,and ultimate growth of dendrites.In contrast,membranes fabricated using polybenzimidazole(PBI)exhibit excellent electrolyte wettability and outstanding thermal dimensional stability,thus holding great potential as separators for high-performance and high-safety batteries.In this paper,we present a comprehensive review of the general requirements for separators,synthesis technology for separators,and research trends focusing PBI membranes in lithium batteries to alleviate the current commercial challenges faced by conventional polyolefin separators.In addition,we discuss the future development direction for PBI battery separators by considering various factors such as production cost,ecological footprint,preparation technology,and battery component compatibility.By exploring these perspectives,we aim to promote the continued application and exploration of PBI-based materials to advance lithium battery technology.

Layered Potassium Titanium Niobate/Reduced Graphene Oxide Nanocomposite as a Potassium‑Ion Battery Anode

With graphite currently leading as the most viable anode for potassium-ion batteries(KIBs),other materials have been left relatively underexamined.Transition metal oxides are among these,with many positive attributes such as synthetic maturity,longterm cycling stability and fast redox kinetics.Therefore,to address this research deficiency we report herein a layered potassium titanium niobate KTiNbO5(KTNO)and its rGO nanocomposite(KTNO/rGO)synthesised via solvothermal methods as a high-performance anode for KIBs.Through effective distribution across the electrically conductive rGO,the electrochemical performance of the KTNO nanoparticles was enhanced.The potassium storage performance of the KTNO/rGO was demonstrated by its first charge capacity of 128.1 mAh g^(−1) and reversible capacity of 97.5 mAh g^(−1) after 500 cycles at 20 mA g^(−1),retaining 76.1%of the initial capacity,with an exceptional rate performance of 54.2 mAh g^(−1)at 1 A g^(−1).Furthermore,to investigate the attributes of KTNO in-situ XRD was performed,indicating a low-strain material.Ex-situ X-ray photoelectron spectra further investigated the mechanism of charge storage,with the titanium showing greater redox reversibility than the niobium.This work suggests this lowstrain nature is a highly advantageous property and well worth regarding KTNO as a promising anode for future high-performance KIBs.

Microstructure design of advanced magnesium-air battery anodes

Metal-air battery is an environmental friendly energy storage system with unique open structure.Magnesium(Mg)and its alloys have been extensively attempted as anodes for air batteries due to high theoretical energy density,low cost,and recyclability.However,the study on Mg-air battery(MAB)is still at the laboratory level currently,mainly owing to the low anodic efficiency caused by the poor corrosion resistance.In order to reduce corrosion losses and achieve optimal utilization efficiency of Mg anode,the design strategies are reviewed from microstructure perspectives.Firstly,the corrosion behaviors have been discussed,especially the negative difference effect derived by hydrogen evolution.Special attention is given to the effect of anode micro-structures on the MAB,which includes grain size,grain orientation,second phases,crystal structure,twins,and dislocations.For further improvement,the discharge performance,long period stacking ordered phase and its enhancing effect are considered.Meanwhile,given the current debates over Mg dendrites,the potential risk,the impact on discharge,and the elimination strategies are discussed.Microstructure control and single crystal would be promising ways for MAB anode.

Rational design of carbon skeleton interfaces for highly reversible sodium metal battery anodes

Sodium metal batteries(SMBs)have attracted increasing attention over time due to their abundance of sodium resources and low cost.However,the widespread application of SMBs as a viable technology remains a great challenge,such as uneven metallic deposition and dendrite formation during cycling.Carbon skeletons as sodiophilic hosts can alleviate the dendrite formation during the plating/stripping.For the carbon skeleton,how to rationalize the design sodiophilic interfaces between the sodium metal and carbon species remains key to developing desirable Na anodes.Herein,we fabricated four kinds of structural features for carbon skeletons using conventional calcination and flash Joule heating.The roles of conductivity,defects,oxygen content,and the distribution of graphite for the deposition of metallic sodium were discussed in detail.Based on interface engineering,the J1600 electrode,which has abundant Na-C species on its surface,showed the highest sodiophilic.There are uniform and rich F-Na species distributed in the inner solid electrolyte interface layer.This study investigated the different Na-deposition behavior in carbon hosts with distinct graphitic arrangements to pave the way for designing and optimizing advanced electrode materials.

A holistic approach to improving safety for battery energy storage systems

The integration of battery energy storage systems(BESS)throughout our energy chain poses concerns regarding safety,especially since batteries have high energy density and numerous BESS failure events have occurred.Wider spread adoption will only increase the prevalence of these failure events unless there is a step change in the management and design of BESS.To understand the causes of failure,the main challenges of BESS safety are summarised.BESS consequences and failure events are discussed,including specific focus on the chain of events causing thermal runaway,and a case study of a BESS explosion in Surprise Arizona is analysed.Based on the technology and past events,a paradigm shift is required to improve BESS safety.In this review,a holistic approach is proposed.This combines currently adopted approaches including battery cell testing,lumped cell mathematical modelling,and calorimetry,alongside additional measures taken to ensure BESS safety including the requirement for computational fluid dynamics and kinetic modelling,assessment of installation level testing of the full BESS system and not simply a single cell battery test,hazard and layers of protection analysis,gas chromatography,and composition testing.The holistic approach proposed in this study aims to address challenges of BESS safety and form the basis of a paradigm shift in the safety management and design of these systems.

Deep neural network-enabled battery open-circuit voltage estimation based on partial charging data

Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion batteries.The main function of the BMSs is to estimate battery states and diagnose battery health using battery open-circuit voltage(OCV).However,acquiring the complete OCV data online can be a challenging endeavor due to the time-consuming measurement process or the need for specific operating conditions required by OCV estimation models.In addressing these concerns,this study introduces a deep neural network-combined framework for accurate and robust OCV estimation,utilizing partial daily charging data.We incorporate a generative deep learning model to extract aging-related features from data and generate high-fidelity OCV curves.Correlation analysis is employed to identify the optimal partial charging data,optimizing the OCV estimation precision while preserving exceptional flexibility.The validation results,using data from nickel-cobalt-magnesium(NCM) batteries,illustrate the accurate estimation of the complete OCV-capacity curve,with an average root mean square errors(RMSE) of less than 3 mAh.Achieving this level of precision for OCV estimation requires only around 50 s collection of partial charging data.Further validations on diverse battery types operating under various conditions confirm the effectiveness of our proposed method.Additional cases of precise health diagnosis based on OCV highlight the significance of conducting online OCV estimation.Our method provides a flexible approach to achieve complete OCV estimation and holds promise for generalization to other tasks in BMSs.

Challenges in Li-ion battery high-voltage technology and recent advances in high-voltage electrolytes

The electrolyte directly contacts the essential parts of a lithium-ion battery,and as a result,the electrochemical properties of the electrolyte have a significant impact on the voltage platform,charge discharge capacity,energy density,service life,and rate discharge performance.By raising the voltage at the charge/discharge plateau,the energy density of the battery is increased.However,this causes transition metal dissolution,irreversible phase changes of the cathode active material,and parasitic electrolyte oxidation reactions.This article presents an overview of these concerns to provide a clear explanation of the issues involved in the development of electrolytes for high-voltage lithium-ion batteries.Additionally,solidstate electrolytes enable various applications and will likely have an impact on the development of batteries with high energy densities.It is necessary to improve the high-voltage performance of electrolytes by creating solvents with high thermal stabilities and high voltage resistance and additives with superior film forming performance,multifunctional capabilities,and stable lithium salts.To offer suggestions for the future development of high-energy lithium-ion batteries,we conclude by offering our own opinions and insights on the current development of lithium-ion batteries.

Constructing Al@C-Sn pellet anode without passivation layer for lithium-ion battery

Al is considered as a promising lithium-ion battery(LIBs)anode materials owing to its high theoretical capacity and appropri-ate lithation/de-lithation potential.Unfortunately,its inevitable volume expansion causes the electrode structure instability,leading to poor cyclic stability.What’s worse,the natural Al2O3 layer on commercial Al pellets is always existed as a robust insulating barrier for elec-trons,which brings the voltage dip and results in low reversible capacity.Herein,this work synthesized core-shell Al@C-Sn pellets for LIBs by a plus-minus strategy.In this proposal,the natural Al2O3 passivation layer is eliminated when annealing the pre-introduced SnCl2,meanwhile,polydopamine-derived carbon is introduced as dual functional shell to liberate the fresh Al core from re-oxidization and alle-viate the volume swellings.Benefiting from the addition of C-Sn shell and the elimination of the Al2O3 passivation layer,the as-prepared Al@C-Sn pellet electrode exhibits little voltage dip and delivers a reversible capacity of 1018.7 mAh·g^(-1) at 0.1 A·g^(-1) and 295.0 mAh·g^(-1) at 2.0 A·g^(-1)(after 1000 cycles),respectively.Moreover,its diffusion-controlled capacity is muchly improved compared to those of its counterparts,confirming the well-designed nanostructure contributes to the rapid Li-ion diffusion and further enhances the lithium storage activity.

Machine learning in metal-ion battery research: Advancing material prediction, characterization, and status evaluation

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.

Electric-controlled pressure relief valve for enhanced safety in liquid-cooled lithium-ion battery packs

The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above IP65,which can trap flammable and explosive gases from battery thermal runaway and cause explosions.This poses serious safety risks and challenges for LCBESS.In this study,we tested overcharged battery inside a commercial LCBP and found that the conventionally mechanical pressure relief valve(PRV) on the LCBP had a delayed response and low-pressure relief efficiency.A realistic 20-foot model of an energy storage cabin was constructed using the Flacs finite element simulation software.Comparative studies were conducted to evaluate the pressure relief efficiency and the influence on neighboring battery packs in case of internal explosions,considering different sizes and installation positions of the PRV.Here,a newly developed electric-controlled PRV integrated with battery fault detection is introduced,capable of starting within 50 ms of the battery safety valve opening.Furthermore,the PRV was integrated with the battery management system and changed the battery charging and discharging strategy after the PRV was opened.Experimental tests confirmed the efficacy of this method in preventing explosions.This paper addresses the safety concerns associated with LCBPs and proposes an effective solution for explosion relief.

MIL-100(V) derived porous vanadium oxide/carbon microspheres with oxygen defects and intercalated water molecules as high-performance cathode for aqueous zinc ion battery

The development of aqueous zinc ion battery cathode materials with high capacity and high magnification is still a challenge.Herein,porous vanadium oxide/carbon(p-VO_(x)@C,mainly VO_(2) with a small amount of V_(2)O_(3)) core/shell microspheres with oxygen vacancies are facilely fabricated by using a vanadium-based metal-organic framework(MIL-100(V)) as a sacrificial template.This unique structure can improve the conductivity of the VO_(x),accelerate electrolyte diffusion,and suppress structural collapse during circulation.Subsequently,H_(2)O molecules are introduced into the interlayer of VO_(x) through a highly efficient in-situ electrochemical activation process,facilitating the intercalation and diffusion of zinc ions.After the activation,an optimal sample exhibits a high specific capacity of 464.3 mA h g^(-1) at0.2 A g^(-1) and 395.2 mA h g^(-1) at 10 A g^(-1),indicating excellent rate performance.Moreover,the optimal sample maintains a capacity retention of about 89.3% after 2500 cycles at 10 A g^(-1).Density functional theory calculation demonstrates that the presence of oxygen vacancies and intercalated water molecules can significantly reduce the diffusion barrier for zinc ions.In addition,it is proved that the storage of zinc ions in the cathode is achieved by reversible intercalation/extraction during the charge and discharge process through various ex-situ analysis technologies.This work demonstrates that the p-VO_(x)@C has great potential for applications in aqueous ZIBs after electrochemical activation.

Interface engineering strategy via electron-defect trimethyl borate additive toward 4.7 V ultrahigh-nickel LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2)battery

The Li metal battery with ultrahigh-nickel cathode(LiNi_(x)M_(1-x)O_(2),M=Mn,Co,and x≥0.9)under high-voltage is regarded as one of the most promising approaches to fulfill the ambitious target of 400 Wh/kg.However,the practical application is impeded by the instability of electrode/electrolyte interface and Ni-rich cathode itself.Herein we proposed an electron-defect electrolyte additive trimethyl borate(TMB)which is paired with the commercial carbonate electrolyte to construct highly conductive fluorine-and boron-rich cathode electrolyte interface(CEI)on LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2)(NCM90)surface and solid electrolyte interphase(SEI)on lithium metal surface.The modified CEI effectively mitigates the structural transformation from layered to disordered rock-salt phase,and consequently alleviate the dissolution of transition metal ions(TMs)and its“cross-talk”effect,while the enhanced SEI enables stable lithium plating/striping and thus demonstrated good compatibility between electrolyte and lithium metal anode.As a result,the common electrolyte with 1 wt%TMB enables 4.7 V NCM90/Li cell cycle stably over 100 cycles with 70%capacity retention.This work highlights the significance of the electron-defect boron compounds for designing desirable interfacial chemistries to achieve high performance NCM90/Li battery under high voltage operation.

An aqueous BiI_(3)-Zn battery with dual mechanisms of Zn^(2+)(de)intercalation and I^(-)/I_(2)redox

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.

Battery pack capacity estimation for electric vehicles based on enhanced machine learning and field data

Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery packs.The challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity estimation.To fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field data.The proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction methods.Then,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation coefficient.Moreover,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV applications.Finally,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 kilometers.The results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing methods.This work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.