A novel order-reduced thermal-coupling electrochemical model for lithium-ion batteries

Although the single-particle model enhanced with electrolyte dynamics(SPMe)is simplified from the pseudo-twodimensional(P2D)electrochemical model for lithium-ion batteries,it is difficult to solve the partial differential equations of solid–liquid phases in real-time applications.Moreover,working temperatures have a heavy impact on the battery behavior.Hence,a thermal-coupling SPMe is constructed.Herein,a lumped thermal model is established to estimate battery temperatures.The order of the SPMe model is reduced by using both transfer functions and truncation techniques and merged with Arrhenius equations for thermal effects.The polarization voltage drop is then modified through the use of test data because its original model is unreliable theoretically.Finally,the coupling-model parameters are extracted using genetic algorithms.Experimental results demonstrate that the proposed model produces average errors of about 42 mV under 15 constant current conditions and 15 mV under nine dynamic conditions,respectively.This new electrochemicalthermal coupling model is reliable and expected to be used for onboard applications.

Aqueous electrochemical delithiation of cathode materials as a strategy to selectively recover lithium from waste lithium-ion batteries

Lithium recovery from end-of-life Li-ion batteries(LIBs)through pyro-and hydrometallurgical recycling processes involves several refining stages,with high consumption of reagents and energy.A competitive technological alternative is the electrochemical oxidation of the cathode materials,whereby lithium can be deintercalated and transferred to an electrolyte solution without the aid of chemical extracting compounds.This article investigates the potential to selectively recover Li from LIB cathode materials by direct electrochemical extraction in aqueous solutions.The process allowed to recovering up to 98%of Li from high-purity commercial cathode materials(LiMn_(2)O_(4),LiCoO_(2),and Li Ni_(1/3)Mn_(1/3)Co_(1/3)O_(2))with a faradaic efficiency of 98%and negligible co-extraction of Co,Ni,and Mn.The process was then applied to recover Li from the real waste LIBs black mass obtained by the physical treatment of electric vehicle battery packs.This black mass contained graphite,conductive carbon,and metal impurities from current collectors and steel cases,which significantly influenced the evolution and performances of Li electrochemical extraction.Particularly,due to concomitant oxidation of impurities,lithium extraction yields and faradaic efficiencies were lower than those obtained with high-purity cathode materials.Copper oxidation was found to occur within the voltage range investigated,but it could not quantitatively explain the reduced Li extraction performances.In fact,a detailed investigation revealed that above 1.3 V vs.Ag/Ag Cl,conductive carbon can be oxidized,contributing to the decreased Li extraction.Based on the reported experimental results,guidelines were provided that quantitatively enable the extraction of Li from the black mass,while preventing the simultaneous oxidation of impurities and,consequently,reducing the energy consumption of the proposed Li recovery method.

Unveiling the tailorable electrochemical properties of zeolitic imidazolate framework-derived Ni-doped LiCoO_(2) for lithium-ion batteries in half/full cells

As a prevailing cathode material of lithium-ion batteries(LIBs),LiCoO_(2)(LCO)still encounters the tricky problems of structural collapse,whose morphological engineering and cation doping are crucial for surmounting the mechanical strains and alleviating phase degradation upon cycling.Hereinafter,we propose a strategy using a zeolitic imidazolate framework(ZIF)as the self-sacrificing template to directionally prepare a series of LiNi_(0.1)Co_(0.9)O_(2)(LNCO)with tailorable electrochemical properties.The rational selection of sintering temperature imparts the superiority of the resultant products in lithium storage,during which the sample prepared at 700℃(LNCO-700)outperforms its counterparts in cyclability(156.8 mA h g^(-1)at 1 C for 200 cycles in half cells,1 C=275 mA g^(-1))and rate capability due to the expedited ion/electron transport and the strengthen mechanical robustness.The feasibility of proper Ni doping is also divulged by half/full cell tests and theoretical study,during which LNCO-700(167 mA h g^(-1)at 1 C for 100 cycles in full cells)surpasses LCO-700 in battery performance due to the mitigated phase deterioration,stabilized layered structu re,ameliorated electro nic co nductivity,a nd exalted lithium sto rage activity.This work systematically unveils tailorable electrochemical behaviors of LNCO to better direct their practical application.

Characterization and identification towards dynamic-based electrical modeling of lithium-ion batteries

Lithium-ion batteries are widely recognized as a crucial enabling technology for the advancement of electric vehicles and energy storage systems in the grid.The design of battery state estimation and control algorithms in battery management systems is usually based on battery models,which interpret crucial battery dynamics through the utilization of mathematical functions.Therefore,the investigation of battery dynamics with the purpose of battery system identification has garnered considerable attention in the realm of battery research.Characterization methods in terms of linear and nonlinear response of lithium-ion batteries have emerged as a prominent area of study in this field.This review has undertaken an analysis and discussion of characterization methods,with a particular focus on the motivation of battery system identification.Specifically,this work encompasses the incorporation of frequency domain nonlinear characterization methods and dynamics-based battery electrical models.The aim of this study is to establish a connection between the characterization and identification of battery systems for researchers and engineers specialized in the field of batteries,with the intention of promoting the advancement of efficient battery technology for real-world applications.

Electrothermal Model Based Remaining Charging Time Prediction of Lithium-Ion Batteries against Wide Temperature Range

Battery remaining charging time(RCT)prediction can facilitate charging management and alleviate mileage anxiety for electric vehicles(EVs).Also,it is of great significance to improve EV users’experience.However,the RCT for a lithiumion battery pack in EVs changes with temperature and other battery parameters.This study proposes an electrothermal model-based method to accurately predict battery RCT.Firstly,a characteristic battery cell is adopted to represent the battery pack,thus an equivalent circuit model(ECM)of the characteristic battery cell is established to describe the electrical behaviors of a battery pack.Secondly,an equivalent thermal model(ETM)of the battery pack is developed by considering the influence of ambient temperature,thermal management,and battery connectors in the battery pack to calculate the temperature which is then fed back to the ECM to realize electrothermal coupling.Finally,the RCT prediction method is proposed based on the electrothermal model and validated in the wide temperature range from-20℃to 45℃.The experimental results show that the prediction error of the RCT in the whole temperature range is less than 1.5%.

Thermal Stability and Electrochemical Properties of Separators for Lithium-ion Batteries

The mechanical properties,contact angle,thermomechanical and electrochemical properties of PE,PVDF,and ceramic separators were compared.The experimental results show that the PE separator has the largest porosity,the PVDF separator has the best mechanical properties,wettability,and heat resistance.Three kinds of separators were assembled into lithium-ion batteries for electrochemical tests.Among them,the PE separator has the best rate performance,and the ceramic separator has poor performance in charge-discharge cycles.At the same time,the PE and ceramic separators were tested with different amounts of electrolytes at room temperature and a high temperature,and it is found that the capacity of the PE separator is higher at room temperature,while the performance of the ceramic separator is better at a high temperature.The amount of electrolyte also has a certain influence on its electrochemical performance.

Enhanced Electrochemical Performances of Ni Doped Cr_(8)O_(21)Cathode Materials for Lithium-ion Batteries

Cathode materials,nickel doped Cr_(8)O_(21),were synthesized by a solid-state method.The effects of Ni doping on the electrochemical performances of Cr_(8)O_(21) were investigated.The experimental results show that the discharge capacities of the samples depend on the nickel contents,which increases firstly and then decreases with increasing Ni contents.Optimized Ni_(0.5)Cr_(7.5)O_(21)delivers a first capacity up to 392.6 m Ah·g^(-1)at 0.1C.In addition,Ni doped sample also demonstrates enhanced cycling stability and rate capability compared with that of the bare Cr_(8)O_(21).At 1 C,an initial discharge capacity of 348.7 m Ah·g^(-1)was achieved for Ni_(0.5)Cr_(7.5)O_(21),much higher than 271.4 m Ah·g^(-1)of the un-doped sample,with an increase of more than 28%.Electrochemical impedance spectroscopy results confirm that Ni doping reduces the growth of interface resistance and charge transfer resistance,which is conducive to the electrochemical kinetic behaviors during charge-discharge.

Revisiting aluminum current collector in lithium-ion batteries:Corrosion and countermeasures

With the large-scale service of lithium-ion batteries(LIBs),their failures have attracted significant attentions.While the decay of active materials is the primary cause for LIB failures,the degradation of auxiliary materials,such as current collector corrosion,should not be disregarded.Therefore,it is necessary to conduct a comprehensive review in this field.In this review,from the perspectives of electrochemistry and materials,we systematically summarize the corrosion behavior of aluminum cathode current collector and propose corresponding countermeasures.Firstly,the corrosion type is clarified based on the properties of passivation layers in different organic electrolyte components.Furthermore,a thoroughgoing analysis is presented to examine the impact of various factors on aluminum corrosion,including lithium salts,organic solvents,water impurities,and operating conditions.Subsequently,strategies for electrolyte and protection layer employed to suppress corrosion are discussed in detail.Lastly and most importantly,we provide insights and recommendations to prevent corrosion of current collectors,facilitate the development of advanced current collectors and the implementation of next-generation high-voltage stable LIBs.

One-pot Synthesis of Hierarchical Flower-like WS_(2) Microspheres as Anode Materials for Lithium-ion Batteries

3D hierarchical flowerlike WS_(2) microspheres were synthesized through a facile one-pot hydrothermal route.The as-synthesized samples were characterized by powder X-ray powder diffraction (XRD),energy-dispersive spectroscopy (EDS),scanning electron microscopy (SEM) and Raman.SEM images of the samples reveal that the hierarchical flowerlike WS_(2) microspheres with diameters of about 3-5μm are composed of a number of curled nanosheets.Electrochemical tests such as charge/discharge,cyclic voltammetry,cycle life and rate performance were carried out on the WS_(2) sample.As an anode material for lithium-ion batteries,hierarchical flowerlike WS_(2) microspheres show excellent electrochemical performance.At a current density of100 mA·g^(-1),a high specific capacity of 647.8 mA·h·g^(-1) was achieved after 120 discharge/charge cycles.The excellent electrochemical performance of WS_(2) as an anode material for lithium-ion batteries can be attributed to its special 3D hierarchical structure.

Research progress of alkaline earth metal iron-based oxides as anodes for lithium-ion batteries

Anode materials are an essential part of lithium-ion batteries(LIBs),which determine the performance and safety of LIBs.Currently,graphite,as the anode material of commercial LIBs,is limited by its low theoretical capacity of 372 mA·h·g^(−1),thus hindering further development toward high-capacity and large-scale applications.Alkaline earth metal iron-based oxides are considered a promising candidate to replace graphite because of their low preparation cost,good thermal stability,superior stability,and high electrochemical performance.Nonetheless,many issues and challenges remain to be addressed.Herein,we systematically summarize the research progress of alkaline earth metal iron-based oxides as LIB anodes.Meanwhile,the material and structural properties,synthesis methods,electrochemical reaction mechanisms,and improvement strategies are introduced.Finally,existing challenges and future research directions are discussed to accelerate their practical application in commercial LIBs.

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

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

Empowering the Future: Exploring the Construction and Characteristics of Lithium-Ion Batteries

Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic table. The lithium atom has a strong tendency to release one electron and constitute a positive charge, as Li . Initially, lithium metal was employed as a negative electrode, which released electrons. However, it was observed that its structure changed after the repetition of charge-discharge cycles. To remedy this, the cathode mainly consisted of layer metal oxide and olive, e.g., cobalt oxide, LiFePO4, etc., along with some contents of lithium, while the anode was assembled by graphite and silicon, etc. Moreover, the electrolyte was prepared using the lithium salt in a suitable solvent to attain a greater concentration of lithium ions. Owing to the lithium ions’ role, the battery’s name was mentioned as a lithium-ion battery. Herein, the presented work describes the working and operational mechanism of the lithium-ion battery. Further, the lithium-ion batteries’ general view and future prospects have also been elaborated.

Electrochemical performance of a nickel-rich LiNi0.6Co0.2Mn0.2O2 cathode material for lithium-ion batteries under different cut-off voltages

A spherical-like Ni_(0.6)Co_(0.2)Mn_(0.2)(OH)_2 precursor was tuned homogeneously to synthesize LiNi_(0.6)Co_(0.2)Mn_(0.2)O_2 as a cathode material for lithium-ion batteries.The effects of calcination temperature on the crystal structure,morphology,and the electrochemical performance of the as-prepared LiNi_(0.6)Co_(0.2)Mn_(0.2)O_2 were investigated in detail.The as-prepared material was characterized by X-ray diffraction,scanning electron microscopy,laser particle size analysis,charge–discharge tests,and cyclic voltammetry measurements.The results show that the spherical-like LiNi_(0.6)Co_(0.2)Mn_(0.2)O_2 material obtained by calcination at 900°C displayed the most significant layered structure among samples calcined at various temperatures,with a particle size of approximately 10 μm.It delivered an initial discharge capacity of 189.2 m Ah×g^(-1) at 0.2C with a capacity retention of 94.0% after 100 cycles between 2.7 and 4.3 V.The as-prepared cathode material also exhibited good rate performance,with a discharge capacity of 119.6 m Ah×g^(-1) at 5C.Furthermore,within the cut-off voltage ranges from 2.7 to 4.3,4.4,and 4.5 V,the initial discharge capacities of the calcined samples were 170.7,180.9,and 192.8 m Ah×g^(-1),respectively,at a rate of 1C.The corresponding retentions were 86.8%,80.3%,and 74.4% after 200 cycles,respectively.

Mechano-electrochemical perspectives on flexible lithium-ion batteries

With the advent of flexible/wearable electronic devices,flexible lithium-ion batteries(LIBs)have attracted significant attention as optimal power source candidates.Flexible LIBs with good flexibility,mechanical stability,and high energy density are still an enormous challenge.In recent years,many complex and diverse design methods for flexible LIBs have been reported.The design and evaluation of ideal flexible LIBs must take into consideration both mechanical and electrochemical factors.In this review,the recent progress and challenges of flexible LIBs are reviewed from a mechano-electrochemical perspective.The recent progress in flexible LIB design is addressed concerning flexible material and configuration design.The mechanical and electrochemical evaluations of flexible LIBs are also summarized.Furthermore,mechano-electrochemical perspectives for the future direction of flexible LIBs are also discussed.Finally,the relationship between mechanical loading and the electrode process is analyzed from a mechano-electrochemical perspective.The evaluation of flexible LIBs should be based on mechano-electrochemical processes.Reviews and perspectives are of great significance to the design and practicality of flexible LIBs,which is contributed to bridging the gap between laboratory exploration and practical applications.

Characterization and Electrochemical Performance of ZnO Modified LiFePO_4/C Cathode Materials for Lithium-ion Batteries

To improve the electrical conductivity of LiFePO4 cathode materials, the ZnO modified LiFePO4/C cathode materials are synthesized by a two-step process including solid state synthesis method and precipitation method. The structures and compositions of ZnO modified LiFePO4/C cathode materials are characterized and analyzed by X-ray diffraction, scanning electron microscopy, transmission electron microscopy and energy dispersive spectroscopy, which indicates that the existence of ZnOhas little or no effect on the crystal structure, particles size and morphology of LiFePO4. The electrochemical performances are also characterized and analyzed with charge-discharge test, cyclic voltammetry and electrochemical impedance spectroscopy. The results show that the existence of ZnO improves the specific capability and lithium ion diffusion rate of LiFePO4 cathode materials and reduces the charge transfer resistance of cell, and the one with 3 wt% ZnO exhibits the best electrochemical performance.

Electrochemical Performance and EIS Analysis of Commercial Lithium-Ion Battery

Degradation behavior is the main technical problem in the field of commercial application of lithiumion batteries. According to the characteristics of voltage, discharge capacity and inner resistance during the charge/discharge process of commercial lithium-ion batteries of mobile telephone, degradation analysis and related mechanisms are put forward and discussed in the paper. The impedance spectra of prismatic commercial lithium-ion batteries are measured at various state of charge after different charge/discharge cycles. The incastared impedance spectra are discussed with a proposed equivalent circuit. Results indicated that the structure change of electrode materials or swell and shrink of crystal lattice, decompose of electrolyte, dissolution of active materials and solid electrolyte interphase film formation are the main reasons leading to the capacity degradation.

Critical Review on Improved Electrochemical Impedance Spectroscopy-cuckoo Search-Elman Neural Network Modeling Methods for Whole-life-cycle Health State Estimation of Lithium-ion Battery Energy Storage Systems

Efficient and accurate health state estimation is crucial for lithium-ion battery(LIB)performance monitoring and economic evaluation.Effectively estimating the health state of LIBs online is the key but is also the most difficult task for energy storage systems.With high adaptability and applicability advantages,battery health state estimation based on data-driven techniques has attracted extensive attention from researchers around the world.Artificial neural network(ANN)-based methods are often used for state estimations of LIBs.As one of the ANN methods,the Elman neural network(ENN)model has been improved to estimate the battery state more efficiently and accurately.In this paper,an improved ENN estimation method based on electrochemical impedance spectroscopy(EIS)and cuckoo search(CS)is established as the EIS-CS-ENN model to estimate the health state of LIBs.Also,the paper conducts a critical review of various ANN models against the EIS-CS-ENN model.This demonstrates that the EIS-CS-ENN model outperforms other models.The review also proves that,under the same conditions,selecting appropriate health indicators(HIs)according to the mathematical modeling ability and state requirements are the keys in estimating the health state efficiently.In the calculation process,several evaluation indicators are adopted to analyze and compare the modeling accuracy with other existing methods.Through the analysis of the evaluation results and the selection of HIs,conclusions and suggestions are put forward.Also,the robustness of the EIS-CS-ENN model for the health state estimation of LIBs is verified.

Improved Multiple Feature-electrochemical Thermal Coupling Modeling of Lithium-ion Batteries at Low-temperature with Real-time Coefficient Correction

Monitoring various internal parameters plays a core role in ensuring the safety of lithium-ion batteries in power supply applications.It also influences the sustainability effect and online state of charge prediction.An improved multiple feature-electrochemical thermal coupling modeling method is proposed considering low-temperature performance degradation for the complete characteristic expression of multi-dimensional information.This is to obtain the parameter influence mechanism with a multi-variable coupling relationship.An optimized decoupled deviation strategy is constructed for accurate state of charge prediction with real-time correction of time-varying current and temperature effects.The innovative decoupling method is combined with the functional relationships of state of charge and open-circuit voltage to capture energy management ef-fectively.Then,an adaptive equivalent-prediction model is constructed using the state-space equation and iterative feedback correction,making the proposed model adaptive to fractional calculation.The maximum state of charge estimation errors of the proposed method are 4.57% and 0.223% under the Beijing bus dynamic stress test and dynamic stress test conditions,respectively.The improved multiple feature-electrochemical thermal coupling modeling realizes the effective correction of the current and temperature variations with noise influencing coefficient,and provides an efficient state of charge prediction method adaptive to complex conditions.

Physics-informed neural network approach for heat generation rate estimation of lithium-ion battery under various driving conditions

Accurate insight into the heat generation rate(HGR) of lithium-ion batteries(LIBs) is one of key issues for battery management systems to formulate thermal safety warning strategies in advance.For this reason,this paper proposes a novel physics-informed neural network(PINN) approach for HGR estimation of LIBs under various driving conditions.Specifically,a single particle model with thermodynamics(SPMT) is first constructed for extracting the critical physical knowledge related with battery HGR.Subsequently,the surface concentrations of positive and negative electrodes in battery SPMT model are integrated into the bidirectional long short-term memory(BiLSTM) networks as physical information.And combined with other feature variables,a novel PINN approach to achieve HGR estimation of LIBs with higher accuracy is constituted.Additionally,some critical hyperparameters of BiLSTM used in PINN approach are determined through Bayesian optimization algorithm(BOA) and the results of BOA-based BiLSTM are compared with other traditional BiLSTM/LSTM networks.Eventually,combined with the HGR data generated from the validated virtual battery,it is proved that the proposed approach can well predict the battery HGR under the dynamic stress test(DST) and worldwide light vehicles test procedure(WLTP),the mean absolute error under DST is 0.542 kW/m^(3),and the root mean square error under WLTP is1.428 kW/m^(3)at 25℃.Lastly,the investigation results of this paper also show a new perspective in the application of the PINN approach in battery HGR estimation.

Perspective on low-temperature electrolytes for LiFePO 4-based lithium-ion batteries

The olivine-type lithium iron phosphate(LiFePO_(4))cathode material is promising and widely used as a high-performance lithium-ion battery cathode material in commercial batteries due to its low cost,environmental friendliness,and high safety.At present,LiFePO_(4)/C sec-ondary batteries are widely used for electronic products,automotive power batteries,and other occasion-related applications with good thermal stability,stable cycle performance,and low room-temperature self-discharge rate.However,LiFePO_(4)-based battery applications are seriously limited when they are operated in a cold climate.This outcome is due to a considerable decrease in Li+transport capabilities within the elec-trode,particularly leading to a dramatic decrease in the electrochemical capacity and power performance of the electrolyte.Therefore,the design of low-temperature electrolytes is important for the further commercial application of LiFePO_(4) batteries.This paper reviews the key factors for the poor low-temperature performance of LiFePO_(4)-based batteries and the research progress of low-temperature electrolytes.Spe-cial attention is paid to electrolyte components,including lithium salts,cosolvents,additives,and the development of new electrolytes.The factors affecting the anode are also analyzed.Finally,according to the current research progress,some viewpoints are summarized to provide suitable modification methods and research suggestions for improving the practicability of LiFePO_(4)/C commercial batteries at low temperat-ures in the future.