Lithium-Ion Battery Pack Based on Fuzzy Logic Control Research on Multi-Layer Equilibrium Circuits

In order to solve the problem of inconsistent energy in the charging and discharging cycles of lithium-ion battery packs,a new multilayer equilibrium topology is designed in this paper.The structure adopts a hierarchical structure design,which includes intra-group equilibrium,primary inter-group equilibrium and secondary inter-group equilibrium.This structure greatly increases the number of equilibrium paths for lithium-ion batteries,thus shortening the time required for equilibrium,and improving the overall efficiency.In terms of control strategy,fuzzy logic control(FLC)is chosen to control the size of the equilibrium current during the equilibrium process.We performed rigorous modeling and simulation of the proposed system by MATLAB and Simulink software.Experiments show that the multilayer equilibrium circuit structure greatly exceeds the traditional single-layer equilibrium circuit in terms of efficacy,specifically,the Li-ion battery equilibrium speed is improved by 12.71%in static equilibrium,14.48%in charge equilibrium,and 11.19%in discharge equilibrium.In addition,compared with the maximum value algorithm,the use of the FLC algorithm reduces the equalization time by about 3.27%and improves the energy transfer efficiency by about 66.49%under the stationary condition,which verifies the feasibility of the equalization scheme.

Ion Dynamics in Concentrated Electrolyte Solutions:Relating Equilibrium Fluctuations of the Ions to Transport Properties in Battery Cells

In recent years,the interest in the development of highly concentrated electrolyte solutions for battery applications has increased enormously.Such electrolyte solutions are typically characterized by a low flammability,a high thermal and electrochemical stability and by the formation of a stable solid electrolyte interphase(SEI)in contact to electrode materials.However,the classification of concentrated electrolyte solutions in terms of the classical scheme"strong"or"weak"has been controversially discussed in the literature.In this paper,a comprehensive theoretical framework is presented for a more general classification,which is based on a comparison of charge transport and mass transport.By combining the Onsager transport formalism with linear response theory,center-of-mass fluctuations and collective translational dipole fluctuations of the ions in equilibrium are related to transport properties in a lithium-ion battery cell,namely mass transport,charge transport and Li^(+)transport under anion-blocking conditions.The relevance of the classification approach is substantiated by showing that i)it is straightforward to classify highly concentrated electrolytes and that ii)both fast charge transport and fast mass transport are indispensable for achieving fast Li^(+)transport under anion-blocking conditions.

激光除漆频率对LIBS准确性影响研究

验证激光诱导击穿光谱(Laser-Induced Breakdown Spectroscopy,LIBS)技术在千赫兹级激光条件下检测准确性对LIBS技术应用于大区域、高效率激光除漆过程监测具有重要意义。本文采用高频(kHz级)1064nm红外脉冲光纤激光器清洗飞机蒙皮漆层,结合能谱仪测试结果及原子光谱数据库数据,研究千赫兹激光对LIBS光谱谱峰波长和峰值强度的影响,并验证LIBS技术在千赫兹级激光除漆过程中的准确性。结果表明千赫兹谱峰较赫兹谱峰波长位置向蓝光区域偏移,偏移量不大于0.18nm。380nm~425nm范围内的谱峰完全消失,425nm~550nm范围内的谱峰信噪比下降。能谱仪测试结果与赫兹级LIBS光谱协同验证了千赫兹级激光条件下LIBS技术检测效果的准确性。表明在大区域、高效率飞机蒙皮激光除漆过程中,LIBS技术可用于除漆过程监测。本研究可为千赫兹级激光除漆过程LIBS监测提供参考。

“LIBS关键技术与应用”专辑前言

激光诱导击穿光谱(LIBS)是一种基于原子发射光谱的物质分析技术,具有样品预处理简单、系统简洁、原位在线探测、多元素同步分析等优点。随着激光器、光谱仪、人工智能等相关技术的发展,LIBS被广泛应用于流程工业、地理环境、生物医学、深空探测等诸多领域,被誉为化学分析技术的“未来巨星”。

激光诱导击穿光谱(LIBS)技术在低碳钢铁冶金行业的应用

激光诱导击穿光谱技术(Laser induced breakdown spectroscopy,简称LIBS)是一种基于激光等离子体的发射光谱技术,具有样品制备简单,分析迅速,多元素同时分析,现场在线和远程分析等独特优势,已在钢铁冶金领域取得了越来越广泛的应用与发展。综述了近年来LIBS技术在钢铁冶金领域的应用研究进展,从冶金生产的全流程进行介绍,包括矿石、熔融钢水/铁水、钢铁产品及炉渣和废气分析。同时,还总结了LIBS技术在钢铁冶金领域应用的优点和缺点,并对该技术的应用前景及未来发展方向进行展望。

基于LIBS的GdFe合金材料快速检测技术研究

为了明晰LIBS(激光诱导击穿光谱)技术检测稀土合金材料的光谱特点,进一步开发基于LIBS的快速检测方法,推动LIBS技术在稀土领域的应用。利用激光诱导击穿光谱仪对GdFe合金材料激发光谱,结合信号强度及背景噪音,研究确定了最佳设置参数。分别考察激光器和光谱仪的参数设置对光谱的影响,根据激发光谱中相关谱线的变化趋势,探讨GdFe合金材料的LIBS检测方法。实验发现,GdFe合金样品与激光孔(Laser aperture)的距离(Z值)、激光能量和积分时间是影响LIBS光谱信号强度和背景噪音的关键参数。因金属和合金样品表面常覆盖氧化层,考察了脉冲激光的预剥蚀次数对光谱稳定性的影响,研究得出,在双脉冲均为164 mJ激光能量的激发下,预剥蚀1次可保证光谱效果。同时研究了两个激光器同时激发和延迟激发对GdFe合金光谱成因的影响,发现单脉冲激发与双脉冲同时激发所得光谱的信号强度并非两束脉冲单独激发的累加信号。通过光谱分析,确定了Z值0.8 mm、两个激光器的脉冲能量164 mJ、积分时间12μs、脉冲延时时间0μs,GdFe合金材料的光谱效果最佳,可为GdFe合金材料的LIBS检测方法建立提供参考,拓展LIBS技术在稀土领域的应用,为稀土合金产品的快速检测技术发展提供基础研究数据。

高精度煤质成分快速定量分析LIBS系统研究

煤质成分的快速、高精度定量分析是工厂对能源高效利用的重要环节。本文通过利用搭建的激光诱导击穿技术煤质快速分析仪,对所采集煤样工业特性固定碳(FixC),灰分(Ash),干燥无灰基的挥发分(Vdaf),热值(Q)进行了定量测量,并对测得的数据与实验室人工测量数据进行对比分析,检验得出该方法在煤质分析方面准确快速。通过对设备稳定性和动态精密度的测试,结果表明了快速煤质分析仪具有较高的稳定性,满足国标规定值。在预测灰分值分布跨度为5%~60%的煤样时,通过增加样品量,增加模型中对大灰分煤样的预测权重,实现预测均方根误差RMSEP<1%的预测精度,挥发分和全硫的RMSEP<1%,热值的RMSEP<0.18 MJ/kg。预测结果均达到工业分析要求,可以满足工业现场的应用需求,具有应用于煤质在线检测方面的广阔前景。

圆柱形空间约束对LIBS检测煤粉颗粒流的优化研究

为了提高激光诱导击穿光谱技术(LIBS)检测煤粉颗粒流时光谱信号的质量和检测结果的可靠性,根据颗粒流的检测特点,设计了一种圆柱形空间约束,并分析了其对LIBS直接检测煤粉颗粒流的实验系统的优化效果。先后对比分析了添加约束前后煤中一些重要元素的特征谱线的绝对强度、信噪比(SNR)和脉冲到脉冲间的相对标准偏差(RSD)等重要信息。结果表明:圆柱形空间约束能够有效地提升LIBS检测煤粉颗粒流的光谱强度和信号的稳定光谱信号的重复性,达到提高检测结果的可靠性的目的。

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.

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.

激光诱导击穿光谱(LIBS)法微损快速检测党参中Pb

中药材重金属元素快速检测对污染监控及人们健康具有重要意义。激光诱导击穿光谱技术(Laser induced breakdown spectroscopy,LIBS)属于一种快速检测方法,研磨压片等预处理方法相对样品消解已有所简化,但破坏了样品的物理性质,且不能满足中药材大宗品种、大批量检测需求。若进一步简化样品预处理,将更加凸显LIBS快速检测的优势。采用Pb溶液浸泡法获得不同Pb含量的党参切片样品,依次获取Pb LIBS光谱强度,通过排序初步判断Pb含量高低,随机从各含量梯度样品中抽取样品,将其分为三份:38个A样用于ICP-MS检测,建立定标曲线,从而获取B样和C样中Pb真实含量,10个B样作为Pb浓度已知的参考定标样品,用于待测党参样品中Pb微损检测,19个C样用于验证B样微损检测准确性。建立的微损定标曲线线性相关系数R^(2)为0.7764,可用于切片党参LIBS快速检测,对待测党参切片样品检测平均相对误差为3.74%,与电感耦合等离子体质谱(ICP-MS)法对比,相关系数R^(2)为0.7957,验证了LIBS技术微损检测的可行性。制备的党参参考定标样品可多次重复用于待测样定标和仪器标定等。实验对待测党参样品仅进行切片处理,避免了研磨、压片等预处理,更加充分地体现LIBS快速检测的优势,为LIBS技术应用于中药材重金属元素快检等领域提供了一种新方法。

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.

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.

国外高校图书馆人工智能素养教育调查研究——基于人工智能LibGuide的分析

人工智能对高校图书馆信息素养教育提出了新的挑战与更高要求。LibGuide作为开展信息素养教育的一种重要途径,目前已在国外高校图书馆的信息素养教育中被广泛应用。文章调研了40所国外一流高校图书馆,并选取其中创建有人工智能LibGuide的26所高校图书馆为样本,分析其LibGuide建设特点,并从人工智能知识、人工智能使用、人工智能信息引用、人工智能思维、人工智能伦理五个角度分析了人工智能LibGuide的内容要素。基于调查结果,从加强图书馆在AI素养教育中的作用、建立完善的AI素养教育内容体系、针对不同对象或应用场景开展AI素养教育、丰富AI素养教育形式等方面,为我国高校图书馆开展AI素养教育提出相关建议。

Hyphae-mediated bioassembly of carbon fibers derivatives for advanced battery energy storage

Ingenious design and fabrication of advanced carbon-based sulfur cathodes are extremely important to the development of high-energy lithium-sulfur batteries,which hold promise as the next-generation power source.Herein,for the first time,we report a novel versatile hyphae-mediated biological assembly technology to achieve scale production of hyphae carbon fibers(HCFs)derivatives,in which different components including carbon,metal compounds,and semiconductors can be homogeneously assembled with HCFs to form composite networks.The mechanism of biological adsorption assembly is also proposed.As a representative,reduced graphene oxides(rGOs)decorated with hollow carbon spheres(HCSs)successfully co-assemble with HCFs to form HCSs@rGOs/HCFs hosts for sulfur cathodes.In this unique architecture,not only large accommodation space for sulfur but also restrained volume expansion and fast charge transport paths are realized.Meanwhile,multiscale physical barriers plus chemisorption sites are simultaneously established to anchor soluble lithium polysulfides.Accordingly,the designed HCSs@rGOs/HCFs-S cathodes deliver a high capacity(1189 mA h g^(-1)at 0.1 C)and good high-rate capability(686 mA h g^(-1)at 5 C).Our work provides a new approach for the preparation of high-performance carbon-based electrodes for energy storage devices.

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.

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.

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.

激光诱导击穿光谱(LIBS)结合字典学习对气溶胶光谱数据筛选方法的研究

气溶胶是大气中的重要组分,对气候、生态环境等均有重要的影响。激光诱导击穿光谱(LIBS)在用于气溶胶检测时,由于气溶胶的离散分布,导致采集到大量无效光谱。通过制备7种不同浓度的NaCl气溶胶样品,选取NaCl溶液(10%)的5000条光谱数据进行分类,其中70%作为训练集,30%作为测试集,建立一种结合字典学习对有效光谱数据进行筛选的方法——K-SVD-SVM。当字典基向量数设置为3时,模型分类性能最优,准确率(Accuracy)、精确率(Precision)、召回率(Recall)、精确率和召回率的调和平均(F1)分别达到96%、95%、95%、0.95。此外,采用K-SVD-SVM方法对7种不同浓度的气溶胶样品进行筛选后,输入结合遗传算法的极限学习机(GA-ELM)模型开展定量分析,同时将未筛选的原始光谱数据输入定量模型进行对比。未筛选的原始数据测试集RMSE和R^(2)分别是0.0303和0.8726,筛选光谱后,分别提升至0.0187和0.9809。结果表明,K-SVD-SVM方法有着较好的分类性能,且采用此方法筛选出的有效数据可以为气溶胶中元素定量分析提供数据支撑。

基于LIBS光谱实现燃煤企业碳排放量高精度快速预测

准确预测煤炭的碳排放数据是实现中国“双碳”目标的重要基础。在煤炭入炉前完成碳排放量数据和煤质指标的精确、快速预测,将转变目前“先排放,后检测”的碳排放数据计算方式,对落实“双碳”战略意义重大。以煤炭碳含量和煤质指标的精准预评估为研究目标,通过自行搭建激光诱导击穿光谱(Laser Induced Breakdown Spectroscopy,LIBS)系统和LIBS光谱统计分析,利用主成分分析-偏最小二乘(PCA-PLS)结合小样本算法对训练集进行回归训练,建立了一种煤炭的碳排放预测模型,并通过在新疆A电厂和山东B电厂中的实际应用,证明了LIBS系统在煤质指标分析中的可靠性。结果表明:所提出的预测方法与传统方法相比绝对误差最大为0.0256 t,表现出较好的碳排放预测能力。所提方法可以用于燃煤企业碳排放量的精准预测,为实现煤炭碳排放和煤质指标的预评估提供了一种较为高效的技术解决路径。