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Thermal characteristic evolution of lithium-ion batteries during the whole lifecycle

Journal of Energy Chemistry 2024年第5期92卷 534-547页

作者： Guangxu Zhang Xuezhe Wei Donghai Chen Xueyuan Wang Siqi Chen Jiangong Zhu haifeng dai School of Materials Science and Engineering Tongji UniversityShanghai 201804China Clean Energy Automotive Engineering Center Tongji UniversityShanghai 201804China School of Automotive Studies Tongji UniversityShanghai 201804China

This work extensively investigates the thermal characteristic evolution of lithium-ion batteries under different degradation paths,and the evolution mechanism through multi-angle characterization is revealed.Under different degradation paths,the evolution trend of temperature rise rate remains unchanged with respect to depth of discharge during the adiabatic discharge process,albeit to varying degrees of alteration.The temperature rise rate changes significantly with aging during the adiabatic discharge process under low-temperature cycling and high-rate cycling paths.The total heat generation rate,irreversible heat generation rate,and reversible heat generation rate exhibit similar evolution behavior with aging under different degradation paths.The interval range of endothermic process of reversible electrochemical reactions increases and the contribution of irreversible heat to the total heat increases with aging.To further standardize the assessment of different degradation paths on the thermal characteristics,this work introduces the innovative concept of“Ampere-hour temperature rise”.In low-temperature cycling and high-rate cycling paths,the ampere-hour temperature rise increases significantly with aging,particularly accentuated with higher discharge rates.Conversely,in high-temperature cycling and high-temperature storage paths,the ampere-hour temperature rise remains relatively stable during the initial stages of aging,yet undergoes a notable increase in the later stages of aging.The multi-angle characterization reveals distinct thermal evolution behavior under different degradation paths primarily attributed to different behavior changes of severe side reactions,such as lithium plating.The findings provide crucial insights for the safe utilization and management of lithium–ion batteries throughout the whole lifecycle.

关键词： Lithium-ion batteries Adiabatic discharge Thermal characteristics Ampere-hour temperaturerise Degradation

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

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Journal of Energy Chemistry 2024年第4期91卷 59-72页

作者： Hang Wu Siqi Chen Yan Hong Chengshan Xu Yuejiu Zheng Changyong Jin Kaixin Chen Yafei He Xuning Feng Xuezhe Wei haifeng dai Clean Energy Automotive Engineering Center Tongji UniversityShanghai 201804China College of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai 200093China State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China

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.

关键词： Lithium-ion battery Battery safety Thermal runaway State of charge Numerical analysis

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Fault Diagnosis of Proton Exchange Membrane Fuel Cell Based on Nonlinear Impedance Spectrum

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Automotive Innovation 2023年第4期6卷 597-610页

作者： Hao Yuan Shaozhe Zhang Xuezhe Wei haifeng dai School of Automotive Studies Tongji UniversityShanghaiChina

Electrochemical impedance spectroscopy(EIS)contributes to developing the fault diagnosis tools for fuel cells,which is of great significance in improving service life.The conventional impedance measurement techniques are limited to linear responses,failing to capture high-order harmonic responses.However,nonlinear electrochemical impedance analysis incorporates additional nonlinear information,enabling the resolution of such responses.This study proposes a novel multi-stage fault diagnosis method based on the nonlinear electrochemical impedance spectrum(NEIS).First,the impact of alternating current excitation amplitude on NEIS is analyzed.Then,a series of experiments are conducted to obtain NEIS data under various fault conditions,encompassing recoverable faults like flooding,drying,starvation,and their mixed faults,spanning different degrees of fault severity.Based on these experiments,both EIS and NEIS datasets are established,and principal component analysis is utilized to extract the main features,thereby reducing the dimensionality of the original data.Finally,a fault diagnosis model is constructed with the support vector machine(SVM)and random forest algorithms,with model hyperparameters optimized by a hybrid genetic particle swarm optimization(HGAPSO)algorithm.The results show that the diagnostic accuracy of NEIS is higher than that of traditional EIS,with the HGAPSO-SVM model achieving a 100%accurate diagnosis under the NEIS dateset and self-defined fault labels.

关键词： Fuel cell Nonlinear electrochemical impedance spectrum Fault diagnosis

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Research on the impact of high-temperature aging on the thermal safety of lithium-ion batteries

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Journal of Energy Chemistry 2023年第12期87卷 378-389,I0010页

作者： Guangxu Zhang Xuezhe Wei Siqi Chen Gang Wei Jiangong Zhu Xueyuan Wang Guangshuai Han haifeng dai Clean Energy Automotive Engineering Center Tongji UniversityShanghai 201804China School of Automotive Studies Tongji UniversityShanghai 201804China Institute for Advanced Study Tongji UniversityShanghai 200092China Shanghai AI NEV Innovative Platform Co. Ltd.Shanghai 201804China

Understanding the thermal safety evolution of lithium-ion batteries during high-temperature usage conditions bears significant implications for enhancing the safety management of aging batteries.This work investigates the thermal safety evolution mechanism of lithium-ion batteries during high-temperature aging.Similarities arise in the thermal safety evolution and degradation mechanisms for lithium-ion batteries undergoing cyclic aging and calendar aging.Employing multi-angle characterization analysis,the intricate mechanism governing the thermal safety evolution of lithium-ion batteries during high-temperature aging is clarified.Specifically,lithium plating serves as the pivotal factor contributing to the reduction in the self-heating initial temperature.Additionally,the crystal structure of the cathode induced by the dissolution of transition metals and the reductive gas generated during aging attacking the crystal structure of the cathode lead to a decrease in thermal runaway triggering temperature.Furthermore,the loss of active materials and active lithium during aging contributes to a decline in both the maximum temperature and the maximum temperature rise rate,ultimately indicating a decrease in the thermal hazards of aging batteries.

关键词： Lithium-ion batteries High-temperature aging Thermal safety Degradation Lithium plating

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Deep learning enhanced lithium-ion battery nonlinear fading prognosis

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Journal of Energy Chemistry 2023年第3期78卷 565-573,I0015页

作者： Shanling Ji Jianxiong Zhu Zhiyang Lyu Heze You Yifan Zhou Liudong Gu Jinqing Qu Zhijie Xia Zhisheng Zhang haifeng dai School of Mechanical Engineering Southeast UniversityNanjing 211189JiangsuChina Guangdong Provincial Key Lab of Green Chemical Product Technology South China University of TechnologyGuangzhou 510006GuangdongChina Engineering Research Center of New Light Sources Technology and Equipment Ministry of EducationNanjing 211189JiangsuChina Clean Energy Automotive Engineering Center School of Automotive EngineeringTongji UniversityShanghai 201804China School of Mathematics Southeast UniversityNanjing 211189JiangsuChina

With the assistance of artificial intelligence,advanced health prognosis technique plays a critical role in the lithium-ion(Li-ion) batteries management system.However,conventional data-driven early aging prediction exhibited dramatic drawbacks,i.e.,volatile capacity nonlinear fading trajectories create obstacles to the accurate multistep ahead prediction due to the complex working conditions of batteries.Herein,a novel deep learning model is proposed to achieve a universal and accurate Li-ion battery aging prognosis.Two battery datasets with various electrode types and cycling conditions are developed to validate the proposed approaches.Knee-point probability(KPP),extracted from the capacity loss curve,is first proposed to detect knee points and improve state-of-health(SOH) predictive accuracy,especially during periods of rapid capacity decline.Using one-cycle data of partial raw voltage as the model input,the SOH and KPP can be simultaneously predicted at multistep ahead,whereas the conventional method showed worse accuracy.Furthermore,to explore the underlying characteristics among various degradation tendencies,an online model update strategy is developed by leveraging the adversarial adaptationinduced transfer learning technique.This work gains new sights into the comprehensive Li-ion battery management and prognosis framework through decomposing capacity degradation trajectories and adversarial learning on the unlabeled samples.

关键词： Battery aging prognosis Deep learning Knee-point probability Sate-of-health

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Nonlinear health evaluation for lithium-ion battery within full-lifespan

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Journal of Energy Chemistry 2022年第9期31卷 333-341,I0010页

作者： Heze You Jiangong Zhu Xueyuan Wang Bo Jiang Hao Sun Xinhua Liu Xuezhe Wei Guangshuai Han Shicong Ding Hanqing Yu Weihan Li Dirk Uwe Sauer haifeng dai School of Automotive Studies Tongji UniversityShanghai 201804China National Fuel Cell Vehicle&Powertrain System Research&Engineering Center Shanghai 201804China Institute for Advanced Study Tongji UniversityShanghai 200092China Shanghai AI NEV Innovative Platform Co. Ltd.Shanghai 201804China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives(ISEA)RWTH Aachen UniversityAachen 52062Germany

Lithium-ion batteries(LIBs), as the first choice for green batteries, have been widely used in energy storage, electric vehicles, 3C devices, and other related fields, and will have greater application prospects in the future. However, one of the obstacles hindering the future development of battery technology is how to accurately evaluate and monitor battery health, which affects the entire lifespan of battery use. It is not enough to assess battery health comprehensively through the state of health(SoH) alone, especially when nonlinear aging occurs in onboard applications. Here, for the first time, we propose a brand-new health evaluation indicator—state of nonlinear aging(SoNA) to explain the nonlinear aging phenomenon that occurs during the battery use, and also design a knee-point identification method and two SoNA quantitative methods. We apply our health evaluation indicator to build a complete LIB full-lifespan grading evaluation system and a ground-to-cloud service framework, which integrates multi-scenario data collection, multi-dimensional data-based grading evaluation, and cloud management functions. Our works fill the gap in the LIBs’ health evaluation of nonlinear aging, which is of great significance for the health and safety evaluation of LIBs in the field of echelon utilization such as vehicles and energy storage. In addition, this comprehensive evaluation system and service framework are expected to be extended to other battery material systems other than LIBs, yet guiding the design of new energy ecosystem.

关键词： Lithium-ion battery State of nonlinear aging Knee-point Grading evaluation system Echelon utilization

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Light and Period Variations in Two K-type Contact Binaries:HI Leo and V523 Cas

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Research in Astronomy and Astrophysics 2022年第12期22卷 260-272页

作者： Yuangui Yang Shuang Wang Huiyu Yuan haifeng dai School of Physics and Electronic Information Huaibei Normal UniversityHuaibei 235000China

We presented a low-precision spectrum for HI Leo,Transiting Exoplanet Survey Satellite data for V523 Cas,and new photometry for both K-type contact binaries.Comparing their light curves on different observing dates,we found small intrinsic variabilities,such as variable amplitudes for HI Leo and the varying heights around the second maxima for V523 Cas.By the Wilson-Devinney Code,we deduced six photometric solutions.The dark spot of V523 Cas may appear on the surface of the more massive component on BJD 2458768,while it disappears on BJD 2458779.Our results indicate that the two binaries are W-type shallow-contact binaries(f≤10%).From the eclipse timing residuals,we found that the orbital periods may continuously increase,accompanied by one to two light-time effects due to additional bodies.The modulated periods and semi-amplitudes are P_(3)=25.8(±1.0)yr and A_(3)=0_·^(d)0066(6)for HI Leo,P_(3)=-14.8(±2.0)yr and A_(3)=0_·^(d)0448(12),P_(4)=18.89(±0.14)yr and A4=0_·^(d)0025(2)for V523 Cas,respectively.The orbital period secularly increases at a rate of dP/dt=2.86(±0.11)×10^(-7)day yr^(-1)for HI Leo and dP/dt=3.45(±0.07)×10^(-8)day yr^(-1)for V523 Cas,which may be attributed to mass transfer from the secondary to the primary.With mass transferring,the shallow-contact binaries,HI Leo and V523 Cas,will evolve into the broken-contact configurations.

关键词： (stars:)binaries(including multiple):close (stars:)binaries:eclipsing stars:activity Online material:machine-readable table

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All-temperature area battery application mechanism,performance,and

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The Innovation 2023年第4期4卷 118-134页

作者： Siqi Chen Xuezhe Wei Guangxu Zhang Xueyuan Wang Jiangong Zhu Xuning Feng haifeng dai Minggao Ouyang Clean Energy Automotive Engineering Center Tongji UniversityShanghai 201804China State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China

Further applications of electric vehicles(EVs)and energy storage stations are limited because of the thermal sensitivity,volatility,and poor durability of lithium-ion batteries(LIBs),especially given the urgent requirements for all-climate utilization and fast charging.This study comprehensively reviews the thermal characteristics and management of LIBs in an all-temperature area based on the performance,mechanism,and thermal management strategy levels.

关键词： battery performance mechanism

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从电池管理到电化学数字电源

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电气工程学报 2024年第1期19卷 3-22页

作者：朱建功戴海峰王学远姜波魏学哲同济大学汽车学院上海201804

电源技术的发展对绿色交通、规模化储能、智慧电网等领域具有重要作用。以电化学器件为代表的电化学电源具有反应机理复杂、多物理场、多尺度特性,同时工作过程中表现出强非线性、时变性及空间分布等特点,为电源的管理带来了挑战。本文... 详细信息

电源技术的发展对绿色交通、规模化储能、智慧电网等领域具有重要作用。以电化学器件为代表的电化学电源具有反应机理复杂、多物理场、多尺度特性,同时工作过程中表现出强非线性、时变性及空间分布等特点,为电源的管理带来了挑战。本文以动力电池为对象,分别从模型、测量和管理三个方面阐述当前电池管理技术的研究现状及发展趋势,认为局限于本地的管理技术将逐渐走向全局的数字化管控,提出电化学数字电源的概念并诠释其内涵,旨在助力新能源汽车、氢电储能、新型电网、充电基础设施等电化学电源应用场景的发展。

关键词：电池模型测量管理电化学数字电源

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基于电化学机理模型的锂离子电池早期内短路电热特征研究

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上海理工大学学报 2024年第1期46卷 10-20页

作者：吴文涛乔冬冬王学远魏学哲戴海峰同济大学新能源汽车工程中心上海201804 同济大学汽车学院上海201804

锂离子电池的内短路故障是诱发其热失控的主要原因之一,早期内短路特征研究能够为电池管理系统的故障诊断和安全预警提供支撑,对提高电动汽车的安全性具有重要意义。构建了锂离子电池内短路电化学机理模型,实现了不同内短路阻值下的锂... 详细信息

锂离子电池的内短路故障是诱发其热失控的主要原因之一,早期内短路特征研究能够为电池管理系统的故障诊断和安全预警提供支撑,对提高电动汽车的安全性具有重要意义。构建了锂离子电池内短路电化学机理模型,实现了不同内短路阻值下的锂枝晶内短路故障模拟。结果表明,由锂枝晶导致的电池内短路产热98%以上来源于正负极产生的焦耳热,早期内短路过程中正负极集流体表面的温升小于1.5 K,不显著的外部热特征无法用于早期内短路故障诊断。与正常电池相比,内短路故障将使得电池充电速度变慢,放电速度变快,端电压异常下降,上述电特征可以为构建早期内短路故障诊断方法提供依据。

关键词：锂离子电池早期内短路电化学机理模型

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