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Cyber Hierarchy Multiscale Integrated Energy Management of Intelligent Hybrid Electric Vehicles

Automotive Innovation 2022年第4期5卷 438-452页

作者： Yanfei Gao shichun yang Xibo Wang Wei Li Qinggao Hou Qin Cheng School of Automotive Engineering Shandong Jiaotong University5001 Haitang RoadJinan 250357China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Key Laboratory of Transport Industry for Transport Vehicle Testing Diagnosis and Maintenance Technology of the Ministry of CommunicationsShandong Jiaotong UniversityJinan 250357China Shandong New Energy Vehicles Test and Identify Research Institute Shandong Jiaotong UniversityJinan 250023China

The full-lifespan management concept provides a new pathway to seeking solutions from macro-application scenarios to micro-mechanism *** paper presents a cyber hierarchy multiscale optimal control method for multiple intelligent hybrid vehicles to fully release the potentials of vehicle components while guaranteeing driving safety and *** can be generally divided into the cyber intelligent driving system on the cyber-end and the intelligent vehicle system on the *** the cyber-end,the state information of the surrounding vehicles is transmitted via the Vehicle-to-Everything structure and further processed in the cloud platform to generate future driving behaviors based on a car-following *** the vehicle-end,an optimized control sequence for vehicle components at micro-levels is derived by incorporating a physics-informed neural network model for battery health *** results show that global optimization needs high coupling between the macro-and micro-physical *** introducing the genetic algorithm for time smoothing,the improved driving strategy is capable of macro-and micro-coupling,and thus improves the controllable performance in time ***,this method spans the complexity of space,time,and chemistry,enhances the interpretation performance of machine learning,and slows down the battery aging in the process of multiscale optimization.

关键词： Cyber hierarchy Multiscale optimal control Physics-informed machine learning Genetic algorithm Battery

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Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems

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Energy and AI 2020年第1期1卷 133-144页

作者： Billy Wu W.Dhammika Widanage shichun yang Xinhua Liu Dyson School of Design Engineering Imperial College LondonUnited Kingdom Warwick Manufacturing Group University of WarwickUnited Kingdom School of Transportation Science and Engineering Beihang UniversityChina

Effective management of lithium-ion batteries is a key enabler for a low carbon future,with applications including electric vehicles and grid scale energy *** lifetime of these devices depends greatly on the materials used,the system design and the operating *** complexity has therefore made real-world control of battery systems ***,with the recent advances in understanding battery degradation,modelling tools and diagnostics,there is an opportunity to fuse this knowledge with emerging machine learning techniques towards creating a battery digital *** this cyber-physical system,there is a close interaction between a physical and digital embodiment of a battery,which enables smarter control and longer *** perspectives paper thus presents the state-of-the-art in battery modelling,in-vehicle diagnostic tools,data driven modelling approaches,and how these elements can be combined in a framework for creating a battery digital *** challenges,emerging techniques and perspective comments provided here,will enable scientists and engineers from industry and academia with a framework towards more intelligent and interconnected battery management in the future.

关键词： battery Battery smart

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An Innovative State-of-charge Estimation Method of Lithium-ion Battery Based on 5th-order Cubature Kalman Filter

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Automotive Innovation 2021年第4期4卷 448-458页

作者： Huang Yi shichun yang Sida Zhou Xinan Zhou Xiaoyu Yan Xinhua Liu School of Vehicle and Mobility Tsinghua UniversityBeijingChina School of Transportation Science and Engineering Beihang UniversityBeijingChina

The lithium-ion batteries have drawn much attention as the major energy storage ***,the battery state estimation still suffers from inaccuracy under dynamic operational conditions,with the unstable environmental noise influencing the robustness of *** paper presents a 5th-order cubature Kalman filter with improvements on adaptivity for real-time state-of-charge *** second-order equivalent circuit model is developed for describing the characteristics of battery,and parameter identification is carried out according to particle swarm *** developed method is validated in stable and dynamic conditions,and simulation results show a satisfactory consistency with the experimental *** maximum estimation error under static conditions is less than 3%and the maximum error under dynamic conditions is 5%.Numerical analysis indicates that the method has better convergence and robustness than the traditional method under the disturbances of initial error,which demonstrates the potential for EV applications in harsh *** proposed method shows application potential for both online estimations and cloud-computing system,indicating its diverse application prospect in electric vehicles.

关键词： 5th-order cubature Kalman filter Parameter identification Equivalent circuit model State of charge Lithium-ion battery

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Atomic/nano-scale in-situ probing the shuttling effect of redox mediator in Na-O_(2) batteries

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Journal of Energy Chemistry 2021年第5期30卷 438-443页

作者： Kai yang Yiwei Li Langlang Jia Yan Wang Zijian Wang YuChen jia shichun yang Magda Titirici Xinhua Liu Luyi yang Feng Pan School of Advanced Materials Peking University Shenzhen Graduate SchoolShenzhen 518055GuangdongChina School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Department of Chemical Engineering Imperial College LondonLondon SW72AZUK

Sodium-oxygen batteries(Na-O_(2))have attracted extensive attention as promising energy storage systems due to their high energy density and low *** mediators are often employed to improve Na-O_(2) battery performance,however,their effect on the formation mechanism of the oxygen reduction product(NaO_(2))is still ***,we have investigated the formation mechanism of NaO_(2) during the discharge process in the presence of a redox mediator with the help of atomic/nano-scale in-situ characterization tools used in concert(*** force microscope,electrochemical quartz crystal microbalance(EQCM)and laser nano-particle analyzer).As a result,real-time observations on different time scales show that by shuttling electrons to the electrolyte,the redox mediator enables formation of NaO_(2) in the solution-phase instead of within a finite region near the electrode *** findings provide new fundamental insights on the understanding of Na-O_(2) batteries and new consequently perspectives on designing high performance metal-O_(2) batteries and other related functions.

关键词： Na-O_(2)battery In-situ AFM EQCM Redox mediator Shuttling effect

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End-cloud collaboration method enables accurate state of health and remaining useful life online estimation in lithium-ion batteries

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Journal of Energy Chemistry 2023年第7期82卷 1-17,I0001页

作者： Bin Ma Lisheng Zhang Hanqing Yu Bosong Zou Wentao Wang Cheng Zhang shichun yang Xinhua Liu School of Transportation Science and Engineering Beihang UniversityBeijing 102206China China Software Testing Center Beijing 100038China Institute for Clean Growth and Future Mobility Coventry UniversityCV15FBUnited Kingdom Dyson School of Design Engineering Imperial College LondonLondon SW72AZUK

Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal *** estimation and prediction of battery health conditions are crucial for battery safety *** this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven *** on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate *** double exponential decay model is utilized as an empirical model to output highly real-time prediction *** Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time ***,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μ*** proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network.

关键词： State of health Remaining useful life End-cloud collaboration Ensemble learningDifferential thermal voltammetry

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Perspective on solid‐electrolyte interphase regulation for lithium metal batteries

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SmartMat 2021年第1期2卷 5-11页

作者： Mingguang Wu Yong Li Xinhua Liu shichun yang Jianmin Ma Shixue Dou School of Physics and Electronics Hunan UniversityChangshaChina State Key Laboratory of Advance Design and Manufacturing for Vehicle Body College of Electrical and Information EngineeringHunan UniversityChangshaChina School of Transportation Science and Engineering Beihang UniversityBeijingChina Institute for Superconducting and Electronic Materials Australian Institute of Innovative MaterialsUniversity of WollongongNorth WollongongNew South WalesAustralia

The solid‐electrolyte interphase(SEI)generated between the electrode and the electrolyte strongly influences the performance of *** the most at-tractive next‐generation energy storage system with ultrahigh energy density,the development of lithium metal batteries(LMBs)has been greatly plagued by the uncontrollable lithium(Li)dendrite and serious electrolyte decom-position resulting from the self‐derived unstable SEI with poor *** this perspective,the recent progress of regulating the nature and composition of the SEI to stabilize the Li metal in LMBs is summarized,followed by a discussion of the formation mechanism and the property of the *** strategies for constructing a stable SEI are summarized,for example,design of a compatible electrolyte with the anode,adding self‐sacrificing additives or solvation control additives,and the regulation of nonfaradaic electric ad-sorption and desorption ***,the guideline for the rational design of the SEI is proposed.

关键词： additive electrolytes lithium metal batteries metallic lithium anode solid electrolyte interphase

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Enabling dendrite-free charging for lithium batteries based on transport-reaction competition mechanism in CHAIN framework

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Journal of Energy Chemistry 2022年第12期75卷 408-421,I0011页

作者： Lisheng Zhang Siyan Chen Wentao Wang Hanqing Yu Haicheng Xie Huizhi Wang shichun yang Cheng Zhang Xinhua Liu School of Transportation Science and Engineering Beihang UniversityBeijing 102206China College of Automotive Engineering Jilin UniversityChangchun 130022JilinChina Department of Mechanical Engineering Imperial College LondonLondon SW72BXUK Institute for Clean Growth and Future Mobility Coventry UniversityCoventryCV15FBUK

Worldwide trends in mobile electrification will skyrocket demands for lithium-based battery production,driven by the popularity of electric ***,both lithium metal batteries and lithium ion batteries face severe safety issues due to dendrite nucleation and growth *** deposition is significantly influenced by interfacial factors and charging *** this paper,an electrochemical model considering the internal and external factors is proposed based on Monte Carlo *** influence of internal solid electrolyte interphase(SEI)porosity,thickness and the external conditions on dendrite growth process is systematically *** simulation results support that the three factors investigated in this model could synergistically regulate the dendrite growth *** competition mechanisms are proposed to tailor lithium deposition for Li-based batteries and numerical solutions for variation pattern of dendrite growth with time are fitted.A three-step process describing kinetic process of lithium deposition is *** achieve dendrite-free charging process,charging strategies and emerging materials design should be considered,including physicochemical materials engineering,artificial SEI,and design for dynamic safety *** work could contribute to the foundation for insights of Li deposition mechanism,which is promising to provide guidelines for next-generation high-energy-density and safe batteries in CHAIN framework.

关键词： Li-based batteries Model Dendrite growth Synergistic adjustment Competition mechanism

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延期状态下电子雷管电子控制模块的高过载加载实验

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高压物理学报 2025年第1期39卷 98-108页

作者：叶紫阳吴红波杨仕春黄菓树李天浩孙翼马成帅任梦雨安徽理工大学化工与爆破学院安徽淮南232001 安徽江南化工股份有限公司安徽合肥230031 无锡盛景微电子股份有限公司江苏无锡214000 安徽中金立华矿业工程有限公司安徽安庆246003

为探究电子雷管内的电子控制模块在延期状态下受冲击载荷时的失效机制,采用分离式霍普金森压杆(split Hopkinson pressure bar,SHPB)对电子雷管试件进行了高过载加载测试,得到了整体电子控制模块和分离出钽电容的其余电子控制模块受不... 详细信息

为探究电子雷管内的电子控制模块在延期状态下受冲击载荷时的失效机制,采用分离式霍普金森压杆(split Hopkinson pressure bar,SHPB)对电子雷管试件进行了高过载加载测试,得到了整体电子控制模块和分离出钽电容的其余电子控制模块受不同加载压力时的失效情况。结果显示:钽电容在1.495×10^(5)g过载时出现电压下降现象,且过载越大,短路失效情况越明显;在一定过载范围内,钽电容因其特有的自愈性,可在短时间内回到起始量级;当过载超过临界范围,达到3.848×10^(5)g时,钽电容损坏且无法逆转。模块内其余组件的抗过载能力强于电容,芯片在4.155×10^(5)g过载后检测异常,电阻元件失效发生在4.249×10^(5)g以上过载。

关键词：电子雷管电子控制模块分离式霍普金森压杆高过载失效

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Recent development and progress of structural energy devices

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Chinese Chemical Letters 2022年第4期33卷 1817-1830页

作者： Yong Liu Zhongxun Yu Jia Chen Chenxi Li Zhengjie Zhang Xiaoyu Yan Xinhua Liu shichun yang Beihang University Beijing 100191China College of Materials Science and Engineering Beijing University of Chemical TechnologyBeijing 100029China

In order to fully replace the traditional fossil energy supply system, the efficiency of electrochemical energy conversion and storage of new energy technology needs to be continuously improved to enhance its market competitiveness. The structural design of energy devices can achieve satisfactory energy conversion and storage performance. To achieve lightweight design, improve mechanical support, enhance electrochemical performance, and adapt to the special shape of the device, the structural energy devices develop very quickly. To help researchers analyze the development and get clear on developing trend,this review is prepared. This review summarizes the latest developments in structural energy devices, including special attention to fuel cells, lithium-ion batteries, lithium metal batteries, and ***, the existing problems of structural energy devices are discussed, and the current challenges and future opportunities are summarized and prospected. Structural energy devices can undoubtedly overcome the performance bottlenecks of traditional energy devices, break the limitations of existing materials and structures, and provide a guidance for the development of equipment with high performance,light weight and low cost in the future.

关键词： Structural energy devices Fuel cells Lithium-ion batteries Lithium metal batteries Supercapacitors

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Multi‑scale Battery Modeling Method for Fault Diagnosis

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Automotive Innovation 2022年第4期5卷 400-414页

作者： shichun yang Hanchao Cheng Mingyue Wang Meng Lyu Xinlei Gao Zhengjie Zhang Rui Cao Shen Li Jiayuan Lin yang Hua Xiaoyu Yan Xinhua Liu School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Department of Mechanical Engineering Imperial College LondonLondon SW72AZUK National New Energy Vehicle Technology Innovation Center Beijing 102602China

Fault diagnosis is key to enhancing the performance and safety of battery storage ***,it is challenging to realize efficient fault diagnosis for lithium-ion batteries because the accuracy diagnostic algorithm is limited and the features of the different faults are *** model-based method has been widely used for degradation mechanism analysis,state estimation,and life prediction of lithium-ion battery systems due to the fast speed and high development *** paper reviews the mainstream modeling approaches used for battery ***,a review of the battery’s degradation mechanisms and the external factors affecting the aging rate is ***,the different modeling approaches are summarized,from microscopic to macroscopic scales,including density functional theory,molecular dynamics,X-ray computed tomography technology,electrochemical model,equivalent circuit model,distributed model and neural network ***,the advantages and disadvantages of these model approaches are discussed for fault detection and diagnosis of batteries in different application ***,the remaining challenges of model-based battery diagnosis and the future perspective of using cloud control and battery intelligent networking to enhance diagnostic performance are discussed.

关键词： Lithium-ion battery Simulation model Fault diagnosis Electrochemical performance State of health estimation

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