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Semi-supervised estimation of capacity degradation for lithium ion batteries with electrochemical impedance spectroscopy

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Journal of Energy Chemistry 2023年第1期76卷 404-413,I0010页

作者： Rui Xiong Jinpeng Tian Weixiang Shen Jiahuan Lu fengchun sun Department of Vehicle Engineering School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVictoria 3122Australia

Machine learning-based methods have emerged as a promising solution to accurate battery capacity estimation for battery management systems.However,they are generally developed in a supervised manner which requires a considerable number of input features and corresponding capacities,leading to prohibitive costs and efforts for data collection.In response to this issue,this study proposes a convolutional neural network(CNN)based method to perform end-to-end capacity estimation by taking only raw impedance spectra as input.More importantly,an input reconstruction module is devised to effectively exploit impedance spectra without corresponding capacities in the training process,thereby significantly alleviating the cost of collecting training data.Two large battery degradation datasets encompassing over 4700 impedance spectra are developed to validate the proposed method.The results show that accurate capacity estimation can be achieved when substantial training samples with measured capacities are given.However,the estimation performance of supervised machine learning algorithms sharply deteriorates when fewer samples with measured capacities are available.In this case,the proposed method outperforms supervised benchmarks and can reduce the root mean square error by up to 50.66%.A further validation under different current rates and states of charge confirms the effectiveness of the proposed method.Our method provides a flexible approach to take advantage of unlabelled samples for developing data-driven models and is promising to be generalised to other battery management tasks.

关键词： Lithium-ion battery Capacity degradation Electrochemical impedance spectroscopy Deep learning

Green Energy and Intelligent Transportation—promoting green and intelligent mobility

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Green Energy and Intelligent Transportation 2022年第1期1卷 1-1页

作者： fengchun sun Beijing Institute of Technology China

Peace,development and exchanges are the eternal themes of the world.Transportation has greatly expanded the scope of human activities and promoted the exchanges among different countries and regions,shortening the distance between people and facilitating the building of a community with a shared future for mankind.Human beings have always maintained a keen interest in exploring the vast space of the Earth since the ancient times.The communication between Asia and Europe and the Age of Exploration connected the originally isolated regions of human civilizations,crossing the barriers of time and space,which promoted the integration,exchanges and development of the economy,culture and art between the East and the West.Nowadays,human beings are developing in four dimensions of land,sea,air and space to advance civilizations.

关键词： maintained Peace expanded

Key technologies for electric vehicles

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Green Energy and Intelligent Transportation 2022年第2期1卷 135-137页

作者： Rui Xiong Jonghoon Kim Weixiang Shen Chen Lv Hailong Li Xiaoyong Zhu Wanzhong Zhao Bingzhao Gao Hongyan Guo Chengming Zhang fengchun sun Department of Vehicle Engineering School of Mechanical EngineeringBeijing Institute of TechnologyNo.5 South Zhongguancun StreetHaidian DistrictBeijing 100081China Energy Storage and Conversion Laboratory Department of Electrical EngineeringCollege of EngineeringChungnam National UniversityDaejeon34134South Korea School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVictoria 3122Australia School of Mechanical and Aerospace Engineering Nanyang Technological University639798Singapore School of Business Society and Engineering Mälardalen UniversitySE 72123VäteråsSweden School of Electrical and Information Engineering Jiangsu UniversityZhenjiangChina Department of Vehicle Engineering Nanjing University of Aeronautics and AstronauticsNanjingChina Clean Energy Automotive Engineering Center Tongji UniversityShanghai 201804China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China Department of Electrical Engineering Harbin Institute of TechnologyHarbinChina

1.Introduction Electric vehicles(EVs)are playing an increasingly important role in decarbonizing the transportation sector.They constitute a promising solution to a set of global challenges such as climate change and air pollution.EVs are an integration of a wide spectrum of techniques,such as battery monitoring,battery safety and vehicle energy management.In this regard,the EV development still faces significant challenges,which necessitate innovations in EV technologies.Given this,Green Energy and Intelligent Transportation(GEITS)organizes a special issue of“Key Technologies for Electric Vehicles”that attempts to advance knowledge in the area of EVs and provides a platform for researchers and engineers to share recent research results and discuss critical challenges in this field.A wide spectrum of topics are discussed,including but not limited to the following.

关键词： battery Key challenges

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数据驱动的钠离子电池健康状态评估方法研究

电源学报 2024年第1期22卷 1-10页

作者：陆楠孙越彭鹏熊瑞孙逢春北京理工大学机械与车辆学院北京100081 南方电网调峰调频发电有限公司储能科研院广州510630

钠离子电池健康状态估计是其安全高效应用的基础,也是钠电池规模化储能应用的关键。然而,钠离子电池即用即衰,衰退机理不明晰,老化过程受工况和场景影响,准确的健康状态估计极其困难。为此,提出了数据驱动的钠离子电池健康状态估计方法... 详细信息

钠离子电池健康状态估计是其安全高效应用的基础,也是钠电池规模化储能应用的关键。然而,钠离子电池即用即衰,衰退机理不明晰,老化过程受工况和场景影响,准确的健康状态估计极其困难。为此,提出了数据驱动的钠离子电池健康状态估计方法,探究了钠离子电池的充电数据与容量衰退的映射关系,提出了结合方差筛选、灰色关联分析和递归特征消除的特征选择方法,应用多元线性回归、支持向量机、高斯过程回归和误差反向传播神经网络4类机器学习方法估计钠离子电池的健康状态。验证结果表明,4类方法的健康状态估计均方根误差小于1.6%,其中高斯过程回归的误差小于0.8%,实现了钠离子电池健康状态精准估计。

关键词：钠离子电池健康状态数据驱动老化特征机器学习

珠江口盆地白云凹陷东部古近系文昌组沉积演化特征

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中国石油大学学报（自然科学版） 2024年第1期48卷 77-90页

作者：刘太勋孙丰春彭光荣汪旭东孙辉解斌苏兆佳中国石油大学(华东)地球科学与技术学院山东青岛266580 中海石油深海开发有限公司广东深圳518054 中海石油(中国)有限公司深圳分公司广东深圳518054

充分利用新三维地震资料,结合测井以及录井资料,对珠江口盆地白云凹陷古近系文昌组层序地层、沉积特征及沉积演化进行研究,重新建立文昌组三级层序格架内的沉积体系演化过程。结果表明:白云凹陷东部文昌组自下而上共划分为5套三级层序,... 详细信息

充分利用新三维地震资料,结合测井以及录井资料,对珠江口盆地白云凹陷古近系文昌组层序地层、沉积特征及沉积演化进行研究,重新建立文昌组三级层序格架内的沉积体系演化过程。结果表明:白云凹陷东部文昌组自下而上共划分为5套三级层序,分别对应于初始裂陷期(WCSQ1)、拆离裂陷早期(WCSQ2,WCSQ3)、拆离裂陷晚期(WCSQ4,WCSQ5)3个构造演化阶段;初始裂陷期为多个孤立的箕状半地堑,以发育缓坡轴向物源辫状河三角洲、陡坡近源扇三角洲和滨浅湖沉积为特征;拆离裂陷早期断裂活动强烈,湖盆迅速扩张,半深湖—深湖局限发育,沉积中心北移,北部番禺低隆起发育大型辫状河三角洲沉积;拆离裂陷晚期断裂活动减弱,湖盆逐渐萎缩,沉积中心稳定在白云凹陷中部,主要发育小型辫状河三角洲沉积,滨浅湖发育;大型辫状河三角洲及扇三角洲砂体是白云凹陷东部的有利储集体。

关键词：沉积相沉积模式文昌组白云凹陷珠江口盆地

Review:Research Progress for Electric Vehicle Hub Motor Driving Technology

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Journal of Harbin Institute of Technology(New Series) 2020年第3期27卷 74-91页

作者： Junqiu Li Jiwei Liu Chao sun fengchun sun State Engineering Laboratory of Electric Vehicles Beijing Institute of TechnologyBeijing 100081China

Due to high efficiency,high controllability,high integration,lightweight,and other advantages,electric vehicle with hub motor driving technology has become an emerging trend of chassis technology.This paper concludes the current state⁃of⁃the⁃art of hub motor drive technologies.Firstly,it summarizes recent hub motor drive products and makes suggestions for hub motor drive schemes in different application scenarios.Then research on hub motor drive key technologies such as integrated design,thermal optimization,lightweight,and intensity optimization is investigated.Considering the high response accuracy and zero delay characteristic of hub motor driving system combined with advanced distributed dynamics control technology that can further improve vehicle performance,this paper also analyzes existing chassis dynamics control technologies of hub motor driving system.Considering the development trend of vehicle electrification,intelligentization,network connection,and current research,this paper makes some forecasts for hub motor drive technologies development in the conclusion.

关键词： hub motor drive current research integrated optimization technique control technology development direction

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新能源汽车碳减排潜力分析

北京理工大学学报 2024年第2期44卷 111-122页

作者：王震坡詹炜鹏孙逢春邓钧君崔丁松黎小慧北京理工大学机械与车辆学院电动车辆国家工程研究中心北京100081

在“碳达峰、碳中和”双碳目标驱动下,新能源汽车凭借其碳减排优势受到了广泛关注.旨在促进新能源汽车碳减排潜力评估的相关研究,从新能源汽车碳排放计量与分析、车网协同优化低碳运行、车辆碳排放总量态势预测等三个方面进行分析与综述... 详细信息

在“碳达峰、碳中和”双碳目标驱动下,新能源汽车凭借其碳减排优势受到了广泛关注.旨在促进新能源汽车碳减排潜力评估的相关研究,从新能源汽车碳排放计量与分析、车网协同优化低碳运行、车辆碳排放总量态势预测等三个方面进行分析与综述,归纳了相关领域最新研究成果,总结各类建模方法优缺点,重点阐述了汽车节能减排核算体系与行业碳排放管理体系等相关成果,并提出新能源汽车碳减排潜力分析研究的发展趋势及未来研究方向.

关键词：新能源汽车碳排放减排潜力

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新技术形势下“车能路云”融合发展战略研究

中国工程科学 2024年第1期26卷 45-58页

作者：岳超钟佳儒宁启立陈晓慧孙超王文伟廉玉波李克强孙逢春北京理工大学机械与车辆学院北京100081 北京理工大学深圳汽车研究院广东深圳518000 比亚迪汽车工业有限公司汽车工程研究院广东深圳518118 清华大学车辆与运载学院北京100084

“车能路云”融合发展将汽车、能源、交通、互联网云有机地融为一体,有利于加速形成智能、低碳、安全、高效的全新出行与生活生态体系,高质量推进汽车产业发展;在新技术形势下,进一步形成“智能的车+互动的能+数字的路+协同的云”的良... 详细信息

“车能路云”融合发展将汽车、能源、交通、互联网云有机地融为一体,有利于加速形成智能、低碳、安全、高效的全新出行与生活生态体系,高质量推进汽车产业发展;在新技术形势下,进一步形成“智能的车+互动的能+数字的路+协同的云”的良好生态,充分发挥其价值优势是未来我国“车能路云”融合发展的重要任务。本文结合新能源变革、智能网联汽车发展、人工智能以及碳中和等新技术形势,分析了我国汽车产业发展的形势;从车端、能源节点、路端、云端与产业融合5个方面,介绍了“车能路云”的系统构成、发展现状、相互关系与总体框架,并对我国“车能路云”融合发展面临的挑战进行了总结。在此基础上,提出了“车能路云”融合发展的建议,涵盖坚持应用导向、推动正向创新、城市级应用示范、多元化撬动投入以及促循环产生成效5个方面,以期为我国“车能路云”高质量发展提供参考,推动汽车强国、交通强国、制造强国的建设。

关键词：新能源汽车智能网联汽车 “车能路云”融合 “四链”融合

China's battery electric vehicles lead the world:achievements in technology system architecture and technological breakthroughs

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Green Energy and Intelligent Transportation 2022年第1期1卷 2-25页

作者： Hongwen He fengchun sun Zhenpo Wang Cheng Lin Chengning Zhang Rui Xiong Junjun Deng Xiaoqing Zhu Peng Xie Shuo Zhang Zhongbao Wei Wanke Cao Li Zhai National Engineering Research Centre of Electric Vehicles Beijing Institute of TechnologyBeijing100081PR China

Developing new energy vehicles has been a worldwide consensus,and developing new energy vehicles characterized by pure electric drive has been China's national strategy.After more than 20 years of high-quality development of China's electric vehicles(EVs),a technological R&D layout of“Three Verticals and Three Horizontals”has been created,and technological advantages have been accumulated.As a result,China's new energy vehicle market has ranked first in the world since 2015.To systematically solve the key problems of battery electric vehicles(BEVs)such as“driving range anxiety,long battery charging time,and driving safety hazards”,China took the lead in putting forward a“system engineering-based technology system architecture for BEVs”and clarifying its connotation.This paper analyzes the research status and progress of the three core components of this architecture,namely,“BEV platform,charging/swapping station,and real-time operation monitoring platform”,and their key technological points.The three major demonstration projects of the 2008 Beijing Olympic Games,the 2022 Beijing Winter Olympics,and the intelligent and connected autonomous battery electric bus project are discussed to specify the applications of BEVs in China.The key research directions for upgrading BEV technologies remain to be further improving the vehicle-level all-climate environmental adaptability and all-day safety of BEVs,systematically solving the charging problem of BEVs and improving their application convenience,and safeguarding safety with early warning and implementing active/passive safety protection for the whole life cycle of power batteries on the basis of BEVs'operation big data.BEVs have acquired new technological features such as intelligent and networked technology empowerment,extensive integration of control-by-wire systems,a platform of chassis hardware,and modularization of functional software.

关键词： Battery electric vehicle(BEV) Charging/swapping station Operation monitoring platform Technology system Motor drive system All-climate Battery Battery safety China