SOC estimation of lithium-ion power battery for HEV based on advanced wavelet neural network

In order to improve the estimation accuracy of the battery＇s state of charge（SOC） for the hybrid electric vehicle（HEV）,the SOC estimation algorithm based on advanced wavelet neural network（WNN） is presented.Based on advanced WNN,the SOC estimation model of a lithium-ion power battery for the HEV is first established.Then,the convergence of the advanced WNN algorithm is proved by mathematical deduction.Finally,using an adequate data sample of various charging and discharging of HEV batteries,the neural network is trained.The simulation results indicate that the proposed algorithm can effectively decrease the estimation errors of the lithium-ion power battery SOC from the range of ±8% to ±1.5%,compared with the traditional SOC estimation methods.

Analysis on the capacity degradation mechanism of a series lithium-ion power battery pack based on inconsistency of capacity

The lithium-ion battery has been widely used as an energy source. Charge rate, discharge rate, and operating tem- perature are very important factors for the capacity degradations of power batteries and battery packs. Firstly, in this paper we make use of an accelerated life test and a statistical analysis method to establish the capacity accelerated degradation model under three constant stress parameters according to the degradation data, which are charge rate, discharge rate, and operating temperature, and then we propose a capacity degradation model according to the current residual capacity of a Li-ion cell under dynamic stress parameters. Secondly, we analyze the charge and discharge process of a series power battery pack and interpret the correlation between the capacity degradations of the battery pack and its charge/discharge rate. According to this cycling condition, we establish a capacity degradation model of a series power battery pack under inconsistent capacity of cells, and analyze the degradation mechanism with capacity variance and operating temperature difference. The comparative analysis of test results shows that the inconsistent operating temperatures of cells in the series power battery pack are the main cause of its degradation; when the difference between inconsistent temperatures is narrowed by 5 ℃, the cycle life can be improved by more than 50%. Therefore, it effectively improves the cycle life of the series battery pack to reasonably assemble the batteries according to their capacities and to narrow the differences in operating temperature among cells.

Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17 W during charging were designed and simulated in the range of 0-12000 s using COMSOL Multiphysics software. This study efficiently employs the Taguchi optimization technique to develop lithium-ion batteries capable of storing a predetermined average electric power during the charging phase. Therefore, this method enables the battery to achieve complete charging within a specific timeframe tailored to a specificapplication. The implementation of this method can save costs, time, and materials compared with other alternative methods, such as the trial-and-error approach.

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.

Deep Learning Hybrid Model for Lithium-Ion Battery Aging Estimation and Prediction

The degradation process of lithium-ion batteries is intricately linked to their entire lifecycle as power sources and energy storage devices,encompassing aspects such as performance delivery and cycling utilization.Consequently,the accurate and expedient estimation or prediction of the aging state of lithium-ion batteries has garnered extensive attention.Nonetheless,prevailing research predominantly concentrates on either aging estimation or prediction,neglecting the dynamic fusion of both facets.This paper proposes a hybrid model for capacity aging estimation and prediction based on deep learning,wherein salient features highly pertinent to aging are extracted from charge and discharge relaxation processes.By amalgamating historical capacity decay data,the model dynamically furnishes estimations of the present capacity and forecasts of future capacity for lithium-ion batteries.Our approach is validated against a novel dataset involving charge and discharge cycles at varying rates.Specifically,under a charging condition of 0.25 C,a mean absolute percentage error(MAPE)of 0.29%is achieved.This outcome underscores the model's adeptness in harnessing relaxation processes commonly encountered in the real world and synergizing with historical capacity records within battery management systems(BMS),thereby affording estimations and prognostications of capacity decline with heightened precision.

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.

Managing the surge:A comprehensive review of the entire disposal framework for retired lithium-ion batteries from electric vehicles

Anticipating the imminent surge of retired lithium-ion batteries(R-LIBs)from electric vehicles,the need for safe,cost-effective and environmentally friendly disposal technologies has escalated.This paper seeks to offer a comprehensive overview of the entire disposal framework for R-LIBs,encompassing a broad spectrum of activities,including screening,repurposing and recycling.Firstly,we delve deeply into a thorough examination of current screening technologies,shifting the focus from a mere enumeration of screening methods to the exploration of the strategies for enhancing screening efficiency.Secondly,we outline battery repurposing with associated key factors,summarizing stationary applications and sizing methods for R-LIBs in their second life.A particular light is shed on available reconditioning solutions,demonstrating their great potential in facilitating battery safety and lifetime in repurposing scenarios and identifying their techno-economic issues.In the realm of battery recycling,we present an extensive survey of pre-treatment options and subsequent material recovery technologies.Particularly,we introduce several global leading recyclers to illustrate their industrial processes and technical intricacies.Furthermore,relevant challenges and evolving trends are investigated in pursuit of a sustainable end-of-life management and disposal framework.We hope that this study can serve as a valuable resource for researchers,industry professionals and policymakers in this field,ultimately facilitating the adoption of proper disposal practices.

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Flexible bidirectional pulse charging regulation achieving long-life lithium-ion batteries

Typical application scenarios,such as vehicle to grid(V2G)and frequency regulation,have imposed significant long-life demands on lithium-ion batteries.Herein,we propose an advanced battery life-extension method employing bidirectional pulse charging(BPC)strategy.Unlike traditional constant current charging methods,BPC strategy not only achieves comparable charging speeds but also facilitates V2G frequency regulation simultaneously.It significantly enhances battery cycle ampere-hour throughput and demonstrates remarkable life extension capabilities.For this interesting conclusion,adopting model identification and postmortem characterization to reveal the life regulation mechanism of BPC:it mitigates battery capacity loss attributed to loss of lithium-ion inventory(LLI)in graphite anodes by intermittently regulating the overall battery voltage and anode potential using a negative charging current.Then,from the perspective of internal side reaction,the life extension mechanism is further revealed as inhibition of solid electrolyte interphase(SEI)and lithium dendrite growth by regulating voltage with a bidirectional pulse current,and a semi-empirical life degradation model combining SEI and lithium dendrite growth is developed for BPC scenarios health management,the model parameters are identified by genetic algorithm with the life simulation exhibiting an accuracy exceeding 99%.This finding indicates that under typical rate conditions,adaptable BPC strategies can extend the service life of LFP battery by approximately 123%.Consequently,the developed advanced BPC strategy offers innovative perspectives and insights for the development of long-life battery applications in the future.

Mathematical modeling and simulations of stress mitigation by coating polycrystalline particles in lithium-ion batteries

A chemo-mechanical model is developed to investigate the effects on the stress development of the coating of polycrystalline Ni-rich LiNixMnyCo_(z)O_(2)(x≥0.8)(NMC)particles with poly(3,4-ethylenedioxythiophene)(PEDOT).The simulation results show that the coating of primary NMC particles significantly reduces the stress generation by efficiently accommodating the volume change associated with the lithium diffusion,and the coating layer plays roles both as a cushion against the volume change and a channel for the lithium transport,promoting the lithium distribution across the secondary particles more homogeneously.Besides,the lower stiffness,higher ionic conductivity,and larger thickness of the coating layer improve the stress mitigation.This paper provides a mathematical framework for calculating the chemo-mechanical responses of anisotropic electrode materials and fundamental insights into how the coating of NMC active particles mitigates stress levels.

Thermodynamic equilibrium theory-guided design and synthesis of Mg-doped LiFe_(0.4)Mn_(0.6)PO_(4)/C cathode for lithium-ion batteries

Mn-rich LiFe_(1-x)Mn_(x)PO_(4)(x>0.5),which combines the high operation voltage of LiMnPO_(4)with excellent rate performa nce of LiFePO4,is hindered by its sluggish kinetic properties.Herein,thermodynamic equilibrium analysis of Mn^(2+)-Fe^(2+)-Mg^(2+)-C_(2)O_(4)^(2-)-H_(2)O system is used to guide the design and preparation of insitu Mg-doped(Fe_(0.4)Mn_(0.6))_(1-x)Mg_(x)C_(2)O_(4)intermediate,which is then employed as an innovative precursor to synthesize high-performance Mg-doped LiFe_(0.4)Mn_(0.6)PO_(4).It indicates that the metal ions with a high precipitation efficiency and the stoichiometric precursors with uniform element distribution can be achieved under the optimized thermodynamic conditions.Meanwhile,accelerated Li+diffusivity and reduced charge transfer resistance originating from Mg doping are verified by various kinetic characterizations.Benefiting from the contributions of inherited homogeneous element distribution,small particle size,uniform carbon layer coating,enhanced Li+migration ability and structural stability induced by Mg doping,the Li(Fe_(0.4)Mn_(0.6))_(0.97)Mg_(0.03)PO_(4)/C exhibits splendid electrochemical performance.

Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery(LiB)time series data.As the energy sector increasingly focuses on integrating distributed energy resources,Virtual Power Plants(VPP)have become a vital new framework for energy management.LiBs are key in this context,owing to their high-efficiency energy storage capabilities essential for VPP operations.However,LiBs are prone to various abnormal states like overcharging,over-discharging,and internal short circuits,which impede power transmission efficiency.Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.In response,we introduce an innovative method:a Long Short-Term Memory(LSTM)autoencoder based on Dynamic Frequency Memory and Correlation Attention(DFMCA-LSTM-AE).This unsupervised,end-to-end approach is specifically designed for dynamically monitoring abnormal states in LiB data.The method starts with a Dynamic Frequency Fourier Transform module,which dynamically captures the frequency characteristics of time series data across three scales,incorporating a memory mechanism to reduce overgeneralization of abnormal frequencies.This is followed by integrating LSTM into both the encoder and decoder,enabling the model to effectively encode and decode the temporal relationships in the time series.Empirical tests on a real-world LiB dataset demonstrate that DFMCA-LSTM-AE outperforms existing models,achieving an average Area Under the Curve(AUC)of 90.73%and an F1 score of 83.83%.These results mark significant improvements over existing models,ranging from 2.4%–45.3%for AUC and 1.6%–28.9%for F1 score,showcasing the model’s enhanced accuracy and reliability in detecting abnormal states in LiB data.

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.

Recycled graphite for more sustainable lithium-ion batteries

The demand for lithium-ion batteries(LIBs)is driven largely by their use in electric vehicles,which is projected to increase dramatically in the future.This great success,however,urgently calls for the efficient recycling of LIBs at the end of their life.Herein,we describe a froth flotation-based process to recycle graphite—the predominant active material for the negative electrode—from spent LIBs and investigate its reuse in newly assembled LIBs.It has been found that the structure and morphology of the recycled graphite are essentially unchanged compared to pristine commercial anode-grade graphite,and despite some minor impurities from the recycling process,the recycled graphite provides a remarkable reversible specific capacity of more than 350 mAh g^(−1).Even more importantly,newly assembled graphite‖NMC532 cells show excellent cycling stability with a capacity retention of 80%after 1000 cycles,that is,comparable to the performance of reference full cells comprising pristine commercial graphite.

Nano-alumina@cellulose-coated separators with the reinforcedconcrete-like structure for high-safety lithium-ion batteries

Separators play a critical role in the safety and performance of lithium-ion batteries.However,commercial polyolefin separators are limited by their poor affinity with electrolytes and low melting points.In this work,we constructed a reinforced-concrete-like structure by homogeneously dispersing nano-Al_(2)O_(3) and cellulose on the separators to improve their stability and performance.In this reinforcedconcrete-like structure,the cellulose is a reinforcing mesh,and the nano-Al_(2)O_(3) acts as concrete to support the separator.After constructing the reinforced-concrete-like structure,the separators exhibit good stability even at 200℃(thermal shrinkage of 0.3%),enhanced tensile strain(tensile stress of 133.4 MPa and tensile strains of 62%),and better electrolyte wettability(a contact angle of 6.5°).Combining these advantages,the cells with nano-Al_(2)O_(3)@cellulose-coated separators exhibit stable cycling performance and good rate performance.Therefore,the construction of the reinforced-concretelike structure is a promising technology to promote the application of lithium-ion batteries in extreme environments.

Metal-organic frameworks and their composites for advanced lithium-ion batteries:Synthesis,progress and prospects

Metal-organic frameworks(MOFs)are among the most promising materials for lithium-ion batteries(LIBs)owing to their high surface area,periodic porosity,adjustable pore size,and controllable chemical composition.For instance,their unique porous structures promote electrolyte penetration,ions transport,and make them ideal for battery separators.Regulating the chemical composition of MOF can introduce more active sites for electrochemical reactions.Therefore,MOFs and their related composites have been extensively and thoroughly explored for LIBs.However,the reported reviews solely include the applications of MOFs in the electrode materials of LIBs and rarely involve other aspects.A systematic review of the application of MOFs in LIBs is essential for understanding the mechanism of MOFs and better designing related MOFs battery materials.This review systematically evaluates the latest developments in pristine MOFs and MOF composites for LIB applications,including MOFs as the main materials(anode,cathode,separators,and electrolytes)to auxiliary materials(coating layers and additives for electrodes).Furthermore,the synthesis,modification methods,challenges,and prospects for the application of MOFs in LIBs are discussed.

Pyrometallurgical recycling of end-of-life lithium-ion batteries

The global importance of lithium-ion batteries(LIBs)has been increasingly underscored with the advancement of high-performance energy storage technologies.However,the end-of-life of these batteries poses significant challenges from environmental,economic,and resource management perspectives.This review paper focuses on the pyrometallurgy-based recycling process of lithium-ion batteries,exploring the fundamental understanding of this process and the importance of its optimization.Centering on the high energy consumption and emission gas issues of the pyrometallurgical recycling process,we systematically analyzed the capital-intensive nature of this process and the resulting technological characteristics.Furthermore,we conducted an in-depth discussion on the future research directions to overcome the existing technological barriers and limitations.This review will provide valuable insights for researchers and industry stakeholders in the battery recycling field.

A review of data-driven whole-life state of health prediction for lithium-ion batteries:Data preprocessing,aging characteristics,algorithms,and future challenges

Lithium-ion batteries are the preferred green energy storage method and are equipped with intelligent battery management systems(BMSs)that efficiently manage the batteries.This not only ensures the safety performance of the batteries but also significantly improves their efficiency and reduces their damage rate.Throughout their whole life cycle,lithium-ion batteries undergo aging and performance degradation due to diverse external environments and irregular degradation of internal materials.This degradation is reflected in the state of health(SOH)assessment.Therefore,this review offers the first comprehensive analysis of battery SOH estimation strategies across the entire lifecycle over the past five years,highlighting common research focuses rooted in data-driven methods.It delves into various dimensions such as dataset integration and preprocessing,health feature parameter extraction,and the construction of SOH estimation models.These approaches unearth hidden insights within data,addressing the inherent tension between computational complexity and estimation accuracy.To enha nce support for in-vehicle implementation,cloud computing,and the echelon technologies of battery recycling,remanufacturing,and reuse,as well as to offer insights into these technologies,a segmented management approach will be introduced in the future.This will encompass source domain data processing,multi-feature factor reconfiguration,hybrid drive modeling,parameter correction mechanisms,and fulltime health management.Based on the best SOH estimation outcomes,health strategies tailored to different stages can be devised in the future,leading to the establishment of a comprehensive SOH assessment framework.This will mitigate cross-domain distribution disparities and facilitate adaptation to a broader array of dynamic operation protocols.This article reviews the current research landscape from four perspectives and discusses the challenges that lie ahead.Researchers and practitioners can gain a comprehensive understanding of battery SOH estimation methods,offering valuable insights for the development of advanced battery management systems and embedded application research.

Recent progress about transmission electron microscopy characterizations on lithium-ion batteries

With the rapid development of portable electronics,new energy vehicles,and smart grids,ion batteries are becoming one of the most widely used energy storage devices,while the safety concern of ion batteries has always been an urgent problem to be solved.To develop a safety-guaranteed battery,the characterization of the internal structure is indispensable,where electron microscopy plays a crucial role.Based on this,this paper summarizes the application of transmission electron microscopy(TEM)in battery safety,further concludes and analyzes the aspects of dendrite growth and solid electrolyte interface(SEI)formation that affect the safety of ion batteries,and emphasizes the importance of electron microscopy in battery safety research and the potential of these techniques to promote the future development of this field.These advanced electron microscopy techniques and their prospects are also discussed.

Porous silicon/carbon composites as anodes for high-performance lithium-ion batteries

Silicon anodes are promising for use in lithium-ion batteries.However,their practical application is severely limited by their large volume expansion leading to irreversible material fracture and electrical disconnects.This study proposes a new top-down strategy for preparing microsize porous silicon and introduces polyacrylonitrile(PAN)for a nitrogen-doped carbon coating,which is designed to maintain the internal pore volume and lower the expansion of the anode during lithiation and delithiation.We then explore the effect of temperature on the evolution of the structure of PAN and the electrochemical behavior of the composite electrode.After treatment at 400℃,the PAN coating retains a high nitrogen content of 11.35 at%,confirming the presence of C—N and C—O bonds that improve the ionic-electronic transport properties.This treatment not only results in a more intact carbon layer structure,but also introduces carbon defects,and produces a material that has remarkable stable cycling even at high rates.When cycled at 4 A g^(-1),the anode had a specific capacity of 857.6 mAh g^(-1) even after 200 cycles,demonstrating great potential for high-capacity energy storage applications.