Investigation on step overcharge to self-heating behavior and mechanism analysis of lithium ion batteries

To obtain intrinsic overcharge boundary and investigate overcharge mechanism,here we propose an innovative method,the step overcharge test,to reduce the thermal crossover and distinguish the overcharge thermal behavior,including 5%state of charge(SOC)with small current overcharge and resting until the temperature equilibrium under adiabatic conditions.The intrinsic thermal response and the self-excitation behaviour are analysed through temperature and voltage changes during the step overcharge period.Experimental results show that the deintercalated state of the cathode is highly correlated to self-heating parasitic reactions.Before reaching the upper limit of Negative/Positive(N/P)ratio,the temperature changes little,the heat generation is significantly induced by the reversible heat(endothermic)and ohmic heat,which could balance each other.Following that the lithium metal is gradually deposited on the surface of the anode and reacts with electrolyte upon overcharge,inducing selfheating side reaction.However,this spontaneous thermal reaction could be“self-extinguished”.When the lithium in cathode is completely deintercalated,the boundary point of overcharge is about 4.7 V(~148%SOC,>40℃),and from this point,the self-heating behaviour could be continuously triggered until thermal runaway(TR)without additional overcharge.The whole static and spontaneous process lasts for 115 h and the side reaction heat is beyond 320,000 J.The continuous self-excitation behavior inside the battery is attributed to the interaction between the highly oxidized cathode and the solvent,which leads to the dissolution of metal ions.The dissolved metal ions destroy the SEI(solid electrolyte interphase)film on the surface of the deposited Li of anode,which induces the thermal reaction between lithium metal and the solvent.The interaction between cathode,the deposited Li of anode,and solvent promotes the temperature of the battery to rise slowly.When the temperature of the battery reaches more than 60℃,the reaction between lithium metal and solvent is accelerated.After the temperature rises rapidly to the melting point of the separator,it triggers the thermal runaway of the battery due to the short circuit of the battery.

A large-area multi-fingerβ-Ga_(2)O_(3) MOSFET and its self-heating effect

The self-heating effect severely limits device performance and reliability.Although some studies have revealed the heat distribution ofβ-Ga_(2)O_(3) MOSFETs under biases,those devices all have small areas and have difficulty reflecting practical con-ditions.This work demonstrated a multi-fingerβ-Ga_(2)O_(3) MOSFET with a maximum drain current of 0.5 A.Electrical characteris-tics were measured,and the heat dissipation of the device was investigated through infrared images.The relationship between device temperature and time/bias is analyzed.

Analytical workload dependence of self-heating effect for SOI MOSFETs considering two-stage heating process

Dynamic self-heating effect(SHE)of silicon-on-insulator(SOI)MOSFET is comprehensively evaluated by ultrafast pulsed I-V measurement in this work.It is found for the first time that the SHE complete heating response and cooling response of SOI MOSFETs are conjugated,with two-stage curves shown.We establish the effective thermal transient response model with stage superposition corresponding to the heating process.The systematic study of SHE dependence on workload shows that frequency and duty cycle have more significant effect on SHE in first-stage heating process than in the second stage.In the first-stage heating process,the peak lattice temperature and current oscillation amplitude decrease by more than 25 K and 4%with frequency increasing to 10 MHz,and when duty cycle is reduced to 25%,the peak lattice temperature drops to 306 K and current oscillation amplitude decreases to 0.77%.Finally,the investigation of two-stage(heating and cooling)process provides a guideline for the unified optimization of dynamic SHE in terms of workload.As the operating frequency is raised to GHz,the peak temperature depends on duty cycle,and self-heating oscillation is completely suppressed.

Self-heating tendency evaluation of sulfide ores based on nonlinear multi-parameters fusion

In order to reveal the nonlinear dynamics characteristics of unsteady self-heating process of sulfide ores, nine different kinds of sulfide ore samples from a pyrite mine in China were taken as experimental materials and their self-heating characteristics were measured in laboratory. Furthermore, the measured temperature was studied by integrating wavelet transform, nonlinear characteristic parameters extraction and fuzzy comprehensive evaluation. The results indicate that only the ore samples 1, 2, 6 and 9 have obvious self-heating phenomenon, and their self-heating initiative temperatures are 220 ℃, 239 ℃, 220 ℃ and 220 ℃, respectively, which means that they are difficult to produce self-heating under normal mining conditions. The correlation dimension of self-heating process is fraction and the maximum Lyapunov exponent is positive, which means that it is feasible to study the self-heating process based on chaotic dynamics theory. The nonlinearities of self-heating process of these four samples （ore samples 1, 2, 6 and 9） are 0.8227, 0.7521, 0.9401 and 0.8827 respectively and the order of the samples according to these results is： sample 6, sample 9, sample 1, sample 2, which is consistent with the measured results of self-heating characteristics. Therefore, the nonlinearity method can be used to evaluate the self-heating tendency of sulfide ores, and it is an effective verification of the reliability of measured results.

Numerical Simulation of the Self-Heating Effect Induced by Electron Beam Plasma in Atmosphere

For exploiting advantages of electron beam air plasma in some unusual applications, a Monte Carlo （MC） model coupled with heat transfer model is established to simulate the characteristics of electron beam air plasma by considering the self-heating effect. Based on the model, the electron beam induced temperature field and the related plasma properties are investigated. The results indicate that a nonuniform temperature field is formed in the electron beam plasma region and the average temperature is of the order of 600 K. Moreover, much larger volume pear-shaped electron beam plasma is produced in hot state rather than in cold state. The beam ranges can, with beam energies of 75 keV and 80 keV, exceed 1.0 m and 1.2 m in air at pressure of 100 torr, respectively. Finally, a well verified formula is obtained for calculating the range of high energy electron beam in atmosphere.

A study of self-heating characteristics of a pyrrhotite-rich sulphide ore stockpile

Original surface chemistry of sulphidesis altered upon contact with air, leading to ''oxidation'', which is accompanied by evolution of heat. The current study reports results of an investigation on extent of exothermicity of an experimental nickel-copper sulphide stockpile that was formed at a mining site in Sudbury, Canada. The ore contained pentlandite and chalcopyrite that are accompanied by a large quantity of pyrrhotite. The self-heating characteristics were recorded by temperature sensors placed inside the stockpile. Ambient conditions such as temperature, humidity, and wind velocity were simultaneously recorded. The inner temperature of the stockpile indicated significant fluctuations due to rapid changes, particularly in the outside temperature. The minimum and maximum temperatures recorded in the outside and inside were 5 and 10.5, 44.3 and 32 ℃, respectively. The self-heating capacity of the sulphide ore stockpile observed represents a mild case compared to that experienced by coals. Possible reasons are discussed.

CFD modelling of Iongwall goaf gas flow to improve gas capture and prevent goaf self-heating

CFD models have been developed to investigate the Iongwall goaf gas flow patternsunder different mining and geological control conditions.The Iongwall goaf wastreated as porous regions and gas flow was modelled as a momentum sink added to themomentum equation.Gas desorption from the caved goaf and destressed coal seamswithin the mining disturbed area was modelled as additional mass sources in the continuityequation.These CFD models were developed according to specific Iongwall layoutsand calibrated against field monitoring data.Two case studies were presented demonstratingthe application of CFD modelling of goaf gas flow characteristics for improved goafgas capture and the reduction of oxygen ingress into the goaf areas for self-heating prevention.Results from the case studies indicate that the optimum goaf drainage strategywould be a combination of shallow (near the face) and deep holes to improve the overalldrainage efficiency and gas purity.For gassy Iongwall faces retreating against the seam dip,it is recommended to conduct cross-measure roof hole drainage targeting the fracturedzones overlying the return corner,rather than high capacity surface goaf drainage deep inthe goaf.

Design and Control of Self-Heat Recuperative Distillation Process for Separation of Close-Boiling Mixtures: n-Butanol and iso-Butanol

In order to explore the advantages of self-heat recuperative distillation(SHRD) process, the design and control of the SHRD process was studied for the separation of n-butanol and iso-butanol mixtures. The economic superiority of SHRD process is presented when a comparison on the total annual cost(TAC) of the conventional distillation process, the vapor recompression distillation process and the SHRD process was made. For the SHRD process, 37.74% and 11.35% savings of TAC can be achieved as compared to the conventional distillation process and vapor recompression distillation process, respectively. The dynamic characteristics of this promising SHRD sequence had been studied, and the dynamic responses demonstrated that 10% changes in both feed flow rate and feed composition can be well handled by the control strategy with dual-temperature control. It is proven that the SHRD system not only can provide economical savings but also can operate normally with good controllability.

Investigation and active suppression of self-heating induced degradation in amorphous InGaZnO thin film transistors

Self-heating effect in amorphous InGaZnO thin-film transistors remains a critical issue that degrades device performance and stability, hindering their wider applications. In this work, pulsed current–voltage analysis has been applied to explore the physics origin of self-heating induced degradation, where Joule heat is shortly accumulated by drain current and dissipated in repeated time cycles as a function of gate bias. Enhanced positive threshold voltage shift is observed at reduced heat dissipation time, higher drain current, and increased gate width. A physical picture of Joule heating assisted charge trapping process has been proposed and then verified with pulsed negative gate bias stressing scheme, which could evidently counteract the self-heating effect through the electric-field assisted detrapping process. As a result, this pulsed gate bias scheme with negative quiescent voltage could be used as a possible way to actively suppress self-heating related device degradation.

Electrothermal simulation of the self-heating effects in 4H-SiC MESFETs

A thermal model of 4H-SiC MESFET is developed based on the temperature dependences of material parameters and three-region I - V model. The static current characteristics of 4H-SiC MESFET have been obtained with the consideration of the self-heating effect on related parameters including electron mobility, saturation velocity and thermal conductivity. High voltage performances are analysed using equivalent thermal conductivity model. Using the physicalbased simulations, we studied the dependence of self-heating temperature on the thickness and doping of substrate. The obtained results can be used for optimization of the thermal design of the SiC-based high-power field effect transistors.

Influence of self-heating on the millimeter-wave and terahertz performance of MBE grown silicon IMPATT diodes

The influence of self-heating on the millimeter-wave(mm-wave)and terahertz(THz)performance of double-drift region(DDR)impact avalanche transit time(IMPATT)sources based on silicon(Si)has been investigated in this paper.The dependences of static and large-signal parameters on junction temperature are estimated using a non-sinusoidal voltage excited(NSVE)large-signal simulation technique developed by the authors,which is based on the quantum-corrected drift-diffusion(QCDD)model.Linear variations of static parameters and non-linear variations of large-signal parameters with temperature have been observed.Analytical expressions representing the temperature dependences of static and large-signal parameters of the diodes are developed using linear and 2nd degree polynomial curve fitting techniques,which will be highly useful for optimizing the thermal design of the oscillators.Finally,the simulated results are found to be in close agreement with the experimentally measured data.

A new physics-based self-heating effect model for 4H-SiC MESFETs

A new self-heating effect model for 4H-SiC MESFETs is proposed based on a combination of an analytical and a computer aided design （CAD） oriented drain current model. The circuit oriented expressions of 4H-SiC low-field electron mobility and incomplete ionization rate, which are related to temperature, are presented in this model, which are used to estimate the self-heating effect of 4H-SiC MESFETs. The verification of the present model is made, and the good agreement between simulated results and measured data of DC I - V curves with the self-heating effect is obtained.

Machine Learning-Based Predictions on the Self-Heating Characteristics of Nanocomposites with Hybrid Fillers

A machine learning-based prediction of the self-heating characteristics and the negative temperature coefficient(NTC)effect detection of nanocomposites incorporating carbon nanotube(CNT)and carbon fiber(CF)is proposed.The CNT content was fixed at 4.0 wt.%,and CFs having three different lengths(0.1,3 and 6 mm)at dosage of 1.0 wt.%were added to fabricate the specimens.The self-heating properties of the specimens were evaluated via self-heating tests.Based on the experiment results,two types of artificial neural network(ANN)models were constructed to predict the surface temperature and electrical resistance,and to detect a severe NTC effect.The present predictions were compared with experimental values to verify the applicability of the proposed ANN models.The ANN model for data prediction was able to predict the surface temperature and electrical resistance closely,with corresponding R-squared value of 0.91 and 0.97,respectively.The ANN model for data detection could detect the severe NTC effect occurred in the nanocomposites under the self-heating condition,as evidenced by the accuracy and sensitivity values exceeding 0.7 in all criteria.

Numerical study of self-heating effects of small-size MOSFETs fabricated on silicon-on-aluminum nitride substrate

Compared with bulk-silicon technology, silicon-on-insulator (SOI) technology possesses many advan-tages but it is inevitable that the buried silicon dioxide layer also thermally insulates the metal – oxide – silicon field-effect transistors (MOSFETs) from the bulk due to the low thermal conductivity. One of the alternative insulator to replace the buried oxide layer is aluminum nitride (AlN), which has a thermal conductivity that is about 200 times higher than that of SiO2 (320 W·m ? 1·K? 1 versus 1.4 W·m? 1·K? 1). To investigate the self-heating effects of small-size MOSFETs fabricated on silicon-on-aluminum nitride (SOAN) substrate, a two-dimensional numerical analysis is performed by using a device simulator called MEDICI run on a Solaris workstation to simulate the electri-cal characteristics and temperature distribution by comparing with those of bulk and standard SOI MOSFETs. Our study suggests that AlN is a suitable alternative to silicon dioxide as a buried dielectric in SOI and expands the appli-cations of SOI to high temperature conditions.

Reduction of self-heating effect in SOI MOSFET by forming a new buried layer structure

An inherent self-heating effect of the silicon-on-insulator (SOI) devices limits their application at high current levels. In this paper a novel solution to reduce the self-heating effect is proposed, based on N+ and O+ co-implantation into silicon wafer to form a new buried layer structure. This new structure was simulated using Medici program, and the temperature distribution and output characteristics were compared with those of the conventional SOI counterparts. As expected, a reduction of self-heating effect in the novel SOI device was observed.

Convenient Self-Heating Instant Food Causes Significant Increasing Human Exposure to Organophosphate Esters

The self-heating lunch box(SHLB)is a kind of popular instant food in China,yet little is known about the associated chemical release risk during its heating process.In this study,we investigated organophosphate esters(OPEs)in original unheated food(UF),SHLB-heated processed food(HF)and potential OPE release from SHLB packaging materials.Significantly higher concentrations of OPEs were observed in HF(267±246 ng/g dry weight(dw))than in UF(163±211 ng/g dw)(p<0.001),suggesting an introduction of additional OPEs during heating processes.Tris(2-chloroethyl)phosphate,triethyl phosphate,and tris(2-chloroisopropyl)phosphate exhibited the highest absolute increased amounts,with 137,48.8,and 149%growth in HF than in UF,respectively.Migration testing revealed that packaging materials were rich in OPEs and can release considerable OPEs into food simulates(range,14.7-90.8 ng/g;mean,47.9±21.8).Influencing factors(temperature,contact time,oily food)on OPE migration from packaging materials to food were assessed.Higher temperature and longer contact time increased OPE contents in food simulates.Moreover,the presence of abundant OPEs in UF and significant correlations among different OPEs(p<0.05)suggested contamination happened during food processing and storage.With one SHLB meal a day,a 12-fold increase of OPE intake was observed for humans compared to those following a traditional dietary habit.In the high-exposure(95th percentile)scenario,hazard quotients of nine OPEs ranged from 0.00005 to 0.05.Our results suggested that the SHLB exposure pathway of OPEs should be particularly paid attention to in specific subpopulations that prefer this dietary habit.

基于自产热和外传热的锂离子电池热学模型参数辨识方法

锂离子电池热学模型参数(热容和热阻)的准确辨识对电池热电耦合建模及状态参数估计至关重要。然而传统测量方法成本高且测试周期长,如何利用充放电工况结合产热和传热机理研究快速热参数辨识方法具有重要意义。以8A×h软包锂离子电池为研究对象,建立分布式热路模型;设计双向脉冲工况实验,采用自适应粒子群算法(APSO)进行辨识;同时采用其他工况进行验证,实验和仿真温度误差小于0.1℃。另外,将热容和热阻转换为比热容和导热系数,并与其他文献中同类电池的参数进行比对,量级接近。研究结果表明,该方法可以有效解决层叠式软包锂离子电池热学模型参数辨识难的问题,且简便易行、成本低。

导电作用下碳纳米管-碳纤维沥青混合料的自愈合研究

针对沥青路面因车辆荷载、温度荷载等带来的裂缝扩展问题,采用碳纳米管-碳纤维制备导电沥青混合料,进行电-热愈合试验,分析沥青混合料裂缝愈合前后的电阻率值、断裂能、极限承载力和微观结构,研究导电作用下碳纳米管-碳纤维沥青混合料的自愈合水平。结果表明,碳纳米管掺量在0.5%,1.0%时可以显著提高沥青混合料的自愈合能力;导电沥青混合料的自愈合水平与愈合前、后电阻率比值存在Sine函数关系;在50℃、20 min环境下小梁试件的极限承载力和断裂应变能得到最大限度的恢复。

吸波沥青混合料的制备及微波自愈合特性

吸波材料具有良好的微波传热能力,可用于沥青路面微裂缝自修复。本研究选取了炭黑粉、羰基铁粉和镍锌铁氧体粉3种吸波材料替换部分矿粉制备了SMA-13吸波沥青混合料。通过车辙试验、低温弯曲破坏试验和冻融劈裂试验对比分析了不同吸波沥青混合料的路用性能,并采用半圆弯曲(SCB)试验研究了吸波材料类型、掺量、微波加热时间等因素对吸波沥青混合料表面温度分布和自愈合性能的影响。利用扫描电子显微镜(SEM)和X射线衍射(XRD)分析吸波材料的微观特性。结果表明,随吸波材料掺量从10%增至30%,炭黑粉沥青混合料的动稳定度和冻融劈裂强度比都呈现出逐渐上升趋势,而低温弯曲应变则表现出先增加后减小的特征;羰基铁粉沥青混合料动稳定度和低温弯曲应变均呈现先增加后减小的趋势,而冻融劈裂强度比表现出逐渐减小的特征;镍锌铁氧体粉沥青混合料动稳定度和低温弯曲应变均呈现逐渐减小趋势,而冻融劈裂强度比则与之相反。吸波沥青混合料的表面温度随着吸波材料掺量和微波加热时间的增加而逐渐上升,能够快速达到沥青混合料裂缝面的愈合温度,从而增强沥青混合料的微波自愈合性能。

GaN HEMT源漏通道区电阻的自热和准饱和效应模型

GaN HEMT在栅极与源极和漏极之间存在一段通道区域,在等效电路模型中通常等效为一电阻,称为源漏通道区电阻R_(D,S)。准确构建GaN HEMT R_(D,S)模型,对于分析GaN HEMT直流和射频特性,构建GaN HEMT大信号模型具有十分重要的意义。本研究给出考虑自热和准饱和效应的R_(D,S)模型。首先由源漏通道区温度T_(CH)与耗散功率P_(diss)的关系,推导出非线性自热效应模型。进一步基于准饱和效应和Trofimenkoff模型,给出源漏通道区电子漂移速度与电场强度的关系表达式,构建非线性R_(D,S)模型。在环境温度Tamb=300~500 K时,源漏通道区二维电子气2DEG面密度n_(S,acc)(T_(CH))和迁移率μ_(acc)(T_(CH))随T_(CH)的升高而下降,这导致低偏置条件下的源漏通道区电阻R_(D0,S0)随T_(CH)呈非线性增长。将本研究和文献报道的R_(D,S)模型与TCAD(Technology Computer Aided Design)仿真数据进行对比,结果显示:本研究与文献报道的漏通道区电阻RD模型的平均相对误差分别为0.32%和1.78%,均方根误差(RMSE)分别为0.039和0.20Ω;RS模型的平均相对误差分别为0.76%和1.73%,RMSE分别为0.023和0.047Ω。与文献报道的实验数据进行对比,结果显示:本研究与文献RD模型的平均相对误差分别为0.91%和1.59%,RMSE分别为0.012和0.015Ω;RS平均相对误差分别为1.22%和2.77%,RMSE分别为0.0015和0.0034Ω。本研究提出的R_(D,S)模型具有更低的平均相对误差和均方根误差,能够更加准确地表征GaN HEMT线性工作区R_(D,S)随漏源电流I_(DS)的变化。可将本模型用于器件的设计优化,也可作为Spice模型用于电路仿真。