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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin jun xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Contrastive Learning

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Transient chemical-mediated epigenetic modulation confers unrestricted lineage potential on human primed pluripotent stem cells

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Science China Life Sciences 2025年

作者： Shi Chen Yuanyuan He Lejun Lv Bei Liu Cheng Li Hongkui Deng jun xu Department of Cell Biology School of Basic Medical Sciences Peking University Stem Cell Research Center Peking University Health Science Center Peking University Academy of Advanced Interdisciplinary Studies Peking University BeiCell Therapeutics School of Life Sciences Center for Bioinformatics Center for Statistical Science Peking University MOE Engineering Research Center of Regenerative Medicine School of Basic Medical Sciences State Key Laboratory of Natural and Biomimetic Drugs Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation College of Life Sciences Peking-Tsinghua Center for Life Sciences Peking University

Human primed pluripotent stem cells are capable of generating all the embryonic ***,their extraembryonic trophectoderm potentials are *** remains unclear how to expand their developmental potential to trophectoderm *** we show that transient treatment with a cocktail of small molecule epigenetic modulators imparts trophectoderm lineage potentials to human primed pluripotent stem cells while preserving their embryonic *** chemically treated cells can generate trophectoderm-like cells and downstream trophoblast stem cells,diverging into syncytiotrophoblast and extravillous trophoblast *** and CUT&Tag analyses reveal that these induced cells share transcriptional profiles with in vivo trophectoderm and cytotrophoblast,and exhibit reduced H3K27me3 modification at gene loci specific to trophoblast lineages compared with primed pluripotent *** exploration highlighted the critical roles of epigenetic modulators HDAC2,EZH1/2,and KDM5s in the activation of trophoblast lineage *** findings demonstrate that transient epigenetic resetting activates unrestricted lineage potential in human primed pluripotent stem cells,and offer new mechanistic insights into human trophoblast lineage specification and in vitro models for studying placental development and related disorders.

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研究生教育促进新质生产力的机制研究

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黑龙江高教研究 2025年第1期43卷 91-97页

作者：周均旭王涛广西大学广西南宁530004

基于2011一2020年我国30个省份的面板数据,运用双向固定效应模型、中介效应模型和门槛效应模型探究了研究生教育对新质生产力的影响效应。结果表明:在全国层面,研究生教育能够有效促进新质生产力发展,经过一系列稳健性检验结论依然成立... 详细信息

基于2011一2020年我国30个省份的面板数据,运用双向固定效应模型、中介效应模型和门槛效应模型探究了研究生教育对新质生产力的影响效应。结果表明:在全国层面,研究生教育能够有效促进新质生产力发展,经过一系列稳健性检验结论依然成立;科技创新在研究生教育促进新质生产力发展的影响过程中发挥部分中介作用;研究生教育在促进新质生产力发展过程中存在产学研合作的门槛效应;区域异质性分析表明,研究生教育显著促进东部地区新质生产力发展,中西部地区次之,东北地区则不显著。对此,应聚焦研究生教育高质量发展,重视科技创新机制转化作用,充分发挥产学研合作调节效应,优化研究生教育布局结构,促进区域新质生产力形成与协调发展。

关键词：新质生产力研究生教育科技创新产学研合作

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Bayesian Inference of Nucleus Resonance and Neutron Skin

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原子能科学技术 2023年第4期57卷 729-742页

作者： xu jun School of Physics Science and Engineering Tongji UniversityShanghai 200092China Shanghai Advanced Research Institute Chinese Academy of SciencesShanghai 201210China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China

In this proceeding,some highlight results on the constraints of the nuclear matter equation of state(EOS)from the data of nucleus resonance and neutron-skin thickness using the Bayesian approach based on the Skyrme-Hartree-Fock model and its extension have been ***,the anti-correlation and positive correlations between the slope parameter and the value of the symmetry energy at the saturation density under the constraint of the neutron-skin thickness and the isovector giant dipole resonance have been discussed ***’s shown that the Bayesian analysis can help to find a compromise for the“PREXII puzzle”and the“soft Tin puzzle”.The possible modifications on the constraints of lower-order EOS parameters as well as the relevant correlation when higher-order EOS parameters are incorporated as independent variables have been further *** a given model and parameter space,the Bayesian approach serves as a good analysis tool suitable for multi-messengers versus multi-variables,and is helpful for constraining quantitatively the model parameters as well as their correlations.

关键词： Bayesian inference nuclear matter equation of state nucleus resonance neutron-skin thickness

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Constraining Isovector Nuclear Interactions with Giant Dipole Resonance and Neutron Skin in ^(208)Pb from a Bayesian Approach

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Chinese Physics Letters 2021年第4期38卷 28-33页

作者： jun xu The Interdisciplinary Research Center Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai 201210China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China

The remaining uncertainties in relation to isovector nuclear interactions call for reliable experimental measurements of isovector probes in finite *** on the Bayesian analysis,although neutron-skin thickness data or isovector giant dipole resonance data in ^(208)Pb can constrain only one isovector interaction parameter,correlations among other parameters can also be *** combined data for both the neutron-skin thickness and the isovector giant dipole resonance helps to significantly constrain all isovector interaction parameters;as such,it serves as a useful methodology for future research.

关键词： dipole interaction finite

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Data-driven short circuit resistance estimation in battery safety issues

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Journal of Energy Chemistry 2023年第4期79卷 37-44页

作者： Yikai Jia jun xu Department of Mechanical Engineering and Engineering Science The University of North Carolina at CharlotteCharlotteNC 28223USA Vehicle Energy&Safety Laboratory(VESL) North Carolina Battery ComplexityAutonomous Vehicle and Electrification(BATT CAVE)Research CenterThe University of North Carolina at CharlotteCharlotteNC 28223USA School of Data Science The University of North Carolina at CharlotteCharlotteNC 28223USA

Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working *** tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing *** samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel *** work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.

关键词： Lithium-ion battery Safety risk Internal short circuit Short circuit resistance Convolutional neural networks

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Steel scrap melting model for a dephosphorisation basic oxygen furnace

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Journal of Iron and Steel Research International 2020年第8期27卷 972-980页

作者： Shuai Deng An-jun xu School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing 100083China

Dephosphorisation basic oxygen furnaces (deP-BOFs) greatly differ from conventional BOFs in the melting process, especially its many limits on adding scrap. A mathematical model of the steel scrap melting process was established in MATLAB to investigate the mechanism of scrap melting in deP-BOF in terms of coupling effects of the carbon content of the molten steel, temperature, scrap preheating and converter blowing time on the melting rate and size of the steel scraps. The scrap melting rate was influenced by both the heat and mass transfer during the melting process: at 1350℃, when the carbon content was increased from 4.5 to 5.0 mass%, the scrap melting rate increased by 43%;for the carbon content of 4.5 mass%, when the temperature was increased from 1350 to 1400℃, the scrap melting rate increased by 60%. The carbonisation was found to be the restrictive step of the scrap melting process in deP-BOFs with respect to conventional ones. The scrap heating from room temperature to 800℃ reduced the crusting thickness on the scrap surface but there was no obvious influence on the melting rate. The scrap melting size in the deP-BOF was rather limited by its low melting rate and short melting time.

关键词： Scrap Melting Dephosphorisation basic oxygen furnace Mathematical model Heat transfer Mass transfer

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Bayesian inference of neutron-skin thickness and neutron-star observables based on effective nuclear interactions

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 97-105页

作者： Jia Zhou jun xu Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China University of Chinese Academy of Sciences Beijing 100049China School of Physics Science and Engineering Tongji UniversityShanghai 200092China

We have obtained the constraints on the density dependence of the symmetry energy from neutron-skin thickness data by parityviolating electron scatterings and neutron-star observables using a Bayesian approach,based on the standard Skyrme-HartreeFock(SHF)model and its extension as well as the relativistic mean-field(RMF)*** the neutron-skin thickness data(neutron-star observables)mostly constrain the symmetry energy at subsaturation(suprasaturation)densities,they may more or less constrain the behavior of the symmetry energy at suprasaturation(subsaturation)densities,depending on the energy-density functional *** showing the final posterior density dependence of the symmetry energy,we also compare the slope parameters of the symmetry energy at 0.10 fm-3as well as the values of the symmetry energy at twice saturation density from three effective nuclear *** present work serves as a comparison study based on relativistic and non-relativistic energy-density functionals,for constraining the nuclear symmetry energy from low to high densities using a Bayesian approach.

关键词： symmetry energy neutron skin neutron star

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Damage evolution and crack propagation in rocks with dual elliptic flaws in compression

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Acta Mechanica Solida Sinica 2017年第6期30卷 573-582页

作者： jun xu Zhaoxia Li Department of Engineering Mechanics Southeast University Nanjing 210096 China Jiangsu Key Laboratory of Engineering Mechanics Southeast University Nanjing 210096 China

To give an insight into the understanding of damage evolution and crack propagation in rocks,a series of uniaxial and biaxial compression numerical tests are carried *** investigations show that damage evolution occurs firstly in the weak rock,the area around the flaw and the area between the flaw and the neighboring rock *** mostly generate as tensile cracks under uniaxial compression and shear cracks under biaxial *** patterns are classified and *** relationship between the accumulated lateral displacement and the short radius（b）is fitted,and the equation of crack path is also established.

关键词： Damage evolution Crack propagation Elliptic flaw

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Shear viscosity of nuclear matter

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Nuclear Science and Techniques 2013年第5期24卷 71-75页

作者： xu jun Shanghai Institute of Applied Physics Chinese Academy of SciencesJiading Campus Department of Physics and Astronomy Texas A & M University-CommerceCommerce

This paper reports my recent study[1]on the shear viscosity of neutron-rich nuclear matter from a relaxation time *** isospin- and momentum-dependent interaction is used in the *** of density,temperature,and isospin asymmetry of nuclear matter on its shear viscosity have been *** to the symmetry energy,the symmetry shear viscosity is defined and its density and temperature dependence are studied.

关键词：剪切粘度核物质不对称弛豫时间相互作用同位旋依赖性丰中子

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