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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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Co-production of hydrogen, oxygen, and electricity via an integrated solar-driven system with decoupled water electrolyzer and Na-Zn ion battery

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Journal of Energy Chemistry 2025年第1期100卷 621-627页

作者： Fei Lv Longjie Liu Jiazhe Wu Pengfei Wang Lixia Pan Dengwei Jing Yubin Chen International Research Center for Renewable Energy State Key Laboratory of Multiphase Flow in Power Engineering Xi'an Jiaotong University

Combining water electrolysis and rechargeable battery technologies into a single system holds great promise for the co-production of hydrogen （H2） and ***,the design and development of such systems is still in its ***,an integrated hydrogen-oxygen （O2）-electricity co-production system featuring a bipolar membrane-assisted decoupled electrolyzer and a Na-Zn ion battery was established with sodium nickelhexacyanoferrate （NaNiHCF） and Zn2+/Zn as dual redox *** decoupled electrolyzer enables to produce H2and O2in different time and space with almost 100%Faradaic efficiency at 100 mA ***,the charged NaNiHCF and Zn electrodes after the electrolysis processes formed a Na-Zn ion battery,which can generate electricity with an average cell voltage of 1.75 V at 10 m A *** connecting Si photovoltaics with the modular electrochemical device,a well-matched solar driven system was built to convert the intermittent solar energy into hydrogen and electric energy with a solar to hydrogen-electricity efficiency of 16.7%,demonstrating the flexible storage and conversion of renewables.

关键词： Hydrogen Electricity Decoupled water electrolyzer Na-Zn ion battery Solar energy

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Application research of multivariate linkage fluctuation analysis on condition evaluation in process industry

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Science China(Technological Sciences) 2018年第3期61卷 397-407页

作者： xiE JunTai GAO JianMin GAO ZhiYong WANG Rongxi WANG Zhen state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.

关键词： complex electromechanical system linkage fluctuation modeling and analysis network structure entropy operation quality evaluation

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Social Sensors (S^2ensors): A Kind of Hardware-Software-Integrated Mediators for Social manufacturing systems Under Mass Individualization

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Chinese Journal of Mechanical engineering 2017年第5期30卷 1150-1161页

作者： Kai Ding Ping-Yu Jiang state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

Currently, little work has been devoted to the mediators and tools for multi-role production interactions in the mass individualization environment. This paper proposes a kind of hardware-software-integrated mediators called social sensors （S2ensors） to facilitate the production interactions among customers, manufacturers, and other stakeholders in the social manufacturing systems （SMS）. The concept, classification, operational logics, and for- malization of S2ensors are clarified. S2ensors collect sub- jective data from physical sensors and objective data from sensory input in mobile Apps, merge them into meaningful information for decision-making, and finally feed the decisions back for reaction and execution. Then, an S2en- sors-Cloud platform is discussed to integrate different S2- ensors to work for SMSs in an autonomous way. A demonstrative case is studied by developing a prototype system and the results show that S2ensors and S2ensors- Cloud platform can assist multi-role stakeholders interact and collaborate for the production tasks. It reveals the mediator-enabled mechanisms and methods for production interactions among stakeholders in SMS.

关键词： Social sensors Social manufacturing system Individualized production Production interaction

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Algorithm for Detecting Volumetric Geometric Accuracy of NC Machine Tool by Laser Tracker

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Chinese Journal of Mechanical engineering 2013年第1期26卷 166-175页

作者： WANG Jindong GUO Junjie state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

Quick and accurate detecting the error of NC machine tool and performing the error compensation are important to improve the machining accuracy of NC machine tool. Currently, there are many methods for detecting the geometric accuracy of NC machine tool. However, these methods have deficiencies in detection efficiency and accuracy as well as in versatility. In the paper, a method with laser tracker based on the multi-station and time-sharing measurement principle is proposed, and this method can rapidly and accurately detect the geometric accuracy of NC machine tool. The machine tool is controlled to move in the preset path in a 3D space or 2D plane, and a laser tracker is used to measure the same motion trajectory of the machine tool successively at different base stations. The original algorithm for multi-station and time-sharing measurement is improved. The space coordinates of the measuring point obtained by the laser tracker are taken as parameter values, and the initial position of each base point can be determined. The redundant equation concerning the base point calibration can be established by the distance information of the laser tracker, and the position of each base point is further determined by solving the equation with least squares method, then the space coordinates of each measuring point can be calibrated. The singular matrix does not occur in calculation with the improved algorithm, which overcomes the limitations of the original algorithm, that the motion trajectory of machine tool is in a 3D space and there exits height difference between the base stations. Adopting the improved algorithm can expand the application of multi-station and time-sharing measurement, and can meet the quick and accurate detecting requirements for different types of NC machine tool.

关键词： laser tracker NC machine tool geometric accuracy redundant equation singular matrix least square method

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Experiments and Simulation of Thermal Behaviors of the Dual-drive Servo Feed System

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Chinese Journal of Mechanical engineering 2015年第1期28卷 76-87页

作者： YANG Jun MEI Xuesong FENG Bin ZHAO Liang MA Chi SHI Hu state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

The machine tool equipped with the dual-drive servo feed system could realize high feed speed as well as sharp precision. Currently, there is no report about the thermal behaviors of the dual-drive machine, and the current research of the thermal characteristics of machines mainly focuses on steady simulation. To explore the influence of thermal characterizations on the precision of a jib boring machine assembled dual-drive feed system, the thermal equilibrium tests and the research on thermal-mechanical transient behaviors are carried out. A laser interferometer, infrared thermography and a temperature-displacement acquisition system are applied to measure the temperature distribution and thermal deformation at different feed speeds. Subsequently, the finite element method （FEM） is used to analyze the transient thermal behaviors of the boring machine. The complex boundary conditions, such as heat sources and convective heat transfer coefficient, are calculated. Finally, transient variances in temperatures and deformations are compared with the measured values, and the errors between the measurement and the simulation of the temperature and the thermal error are 2 ~C and 2.5 pm, respectively. The researching results demonstrate that the FEM model can predict the thermal error and temperature distribution very well under specified operating condition. Moreover, the uneven temperature gradient is due to the asynchronous dual-drive structure that results in thermal deformation. Additionally, the positioning accuracy decreases as the measured point became further away from the motor, and the thermal error and equilibrium period both increase with feed speeds. The research proposes a systematical method to measure and simulate the boring machine transient thermal behaviors.

关键词： dual-drive feed system thermal deformation temperature distribution thermal characteristics measurement FEM

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A novel vibration modeling method for a rotating blade with breathing cracks

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Science China(Technological Sciences) 2019年第2期62卷 333-348页

作者： xiE JingSong ZI YanYang ZHANG MingQuan LUO QinYuan state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

This paper proposes a vibration modeling method for a rotating blade with breathing cracks, considering the coupling of the centrifugal effects, the breathing effects and the crack effects. Firstly, considering the combined effects of the centrifugal stress and the bending stress, a crack breathing model for the rotating blade is proposed. Since the crack surface cannot provide the spanwise centrifugal tensile stress, an additional bending moment will be generated at the crack surface in the rotating ***, an additional bending moment caused by the centrifugal stress is then constructed. In addition, due to the discontinuity of the crack cross section, the additional stiffness caused by the centrifugal effects of the cracked blade will be smaller than that of the normal blade. Therefore, a correction coefficient of the centrifugal stiffness is built. Furthermore, based on the Lagrange equation and the assumed modal method, the vibration equation of the rotating blade with a breathing crack is established(RBC model), and a strategy is constructed for solving this vibration equation. Finally, taking the finite element model(FEM) as a reference, the vibration responses of the RBC model, the open crack model(OC) and the bilinear crack model(BC) are compared. The necessity of the RBC model is illustrated, and the accuracy of the RBC model is verified. The RBC model is a computationally efficient alternative to the finite element analysis for the rotating cracked blade. It can provide an important tool for the vibration modeling and the vibration analysis of the rotating shaft-disk-blade system with cracked blades.

关键词： vibration modeling rotating blade crack breathing model centrifugal effects

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Complex network theory-based condition recognition of electromechanical system in process industry

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Science China(Technological Sciences) 2016年第4期59卷 604-617页

作者： WANG Rongxi GAO JianMin GAO ZhiYong GAO Xu JIANG HongQuan state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

In order to recognize the different operating conditions of a distributed and complex electromechanical system in the process industry,this work proposed a novel method of condition recognition by combining complex network theory with phase space ***,a condition-space with complete information was reconstructed based on phase space reconstruction,and each condition in the space was transformed into a node of a complex ***,the limited penetrable visibility graph method was applied to establish an undirected and un-weighted complex network for the reconstructed ***,the statistical properties of this network were calculated to recognize the different operating conditions.A case study of a real chemical plant was conducted to illustrate the analysis and application processes of the proposed *** results showed that the method could effectively recognize the different conditions of electromechanical systems.A complex electromechanical system can be studied from the systematic and cyber perspectives,and the relationship between the network structure property and the system condition can also be analyzed by utilizing the proposed method.

关键词： complex network condition recognition phase space reconstruction complex electromechanical system

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Material analysis of the fatigue mechanism of rollers in tapered roller bearings

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Science China(Technological Sciences) 2018年第7期61卷 1003-1011页

作者： GUO Wei CAO HongRui ZI YanYang HE ZhengJia state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

Rolling contact fatigue is the main failure mechanism of tapered roller bearings. This study investigated the fatigue mechanism of rollers in a tapered roller bearing that failed in a run-to-failure test. Roller microstructure and crack morphology were investigated through scanning electron microscopy. A microhardness test was performed to investigate the strain hardening of the roller material induced by rolling contact fatigue. Results showed that microcavities and holes are important influential factors of crack initiation and propagation. Crack propagation angle affects crack morphology and propagation mode. Material strain hardening accelerates crack growth. Furthermore, roller misalignment causes uneven hardenability and severe damage to roller ends.

关键词： rolling contact fatigue mechanism crack propagation material microstructure roller misalignment

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Nanoimprint lithography for the manufacturing of flexible electronics

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Science China(Technological Sciences) 2019年第2期62卷 175-198页

作者： SHAO JinYou CHEN xiaoLiang LI xiangMing TIAN HongMiao WANG ChunHui LU BingHeng state key laboratory for manufacturing systems engineering Xi'an Jiaotong University

Flexible electronics have received considerable attention in academies and industries for their promising applications in enormous fields, such as flexible displays, wearable sensors, artificial skins, and flexible energy devices. Challenges remain in developing a flexible and scalable manufacturing method to facilitate the fabrication of multi-functional structures in a flexible electronic system. Nanoimprint lithography is a high resolution and low-cost approach to fabricate nanostructures over a large area. This paper reviews recent progress of nanoimprint lithography and its applications in flexible electronics. The basic principles, classification, research focus, and critical issues of nanoimprint lithography are elaborated. Then, the advantages of nanoimprint lithography are demonstrated in several typical applications related to flexible electronics, including conductive films, optoelectronic devices, flexible sensors, energy harvesting and storage devices, and bioinspired electronic devices. Finally,the challenges and perspectives of nanoimprint lithography in flexible electronic systems are discussed.

关键词： nanoimprint lithography manufacturing flexible electronics nanostructures sensors

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