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A hierarchical enhanced data-driven battery pack capacity estimation framework for real-world operating conditions with fewer labeled data

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Journal of Energy Chemistry 2024年第4期91卷 417-432页

作者： Sijia Yang caiping zhang Haoze Chen Jinyu Wang Dinghong Chen Linjing zhang Weige zhang National Active Distribution Network Technology Research Center(NANTEC) Beijing Jiaotong UniversityBeijing 100044China

Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered ***,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity *** address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled *** traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the“mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory *** generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate *** only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating *** high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.

关键词： Lithium-ion battery pack Capacity estimation Label generation Multi-machine learning model Real-world operating

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State of health based battery reconfiguration for improved energy efficiency

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Control Theory and Technology 2022年第4期20卷 443-455页

作者： Le Yi Wang George Yin Yi Ding caiping zhang Department of Electrical and Computer Engineering Wayne State UniversityDetroitMI 48202USA Department of Mathematics University of ConnecticutStorrsCT 06269USA US Army CCDC Ground Vehicle Systems Center in Warren WarrenMI 48397USA School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China

This paper analyzes the system-level state of health(SOH)and its dependence on the SOHs of its component battery *** to stochastic natures of battery aging processes and their dependence on charge/discharge rate and depth,operating temperature,and environment conditions,capacities of battery modules decay unevenly and *** on estimated SOHs of battery modules during battery operation,we analyze how the SOH of the entire system deteriorates when battery modules age and become increasingly diverse in their capacities.A rigorous mathematical analysis of system-level capacity utilization is *** is shown that for large battery strings with uniformly distributed capacities,the average string capacity approaches the minimum,implying an asymptotically near worst-case capacity utility without *** is demonstrated that the overall battery usable capacities can be more efficiently utilized to achieve extended operational ranges by using battery *** optimal regrouping algorithm is *** methods,simulation examples,and a case study using real-world battery data are presented.

关键词： Battery system State of health Battery aging Capacity utilization Energy efficiency Battery regrouping

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Characterization and quantification of multi-field coupling in lithium-ion batteries under mechanical constraints

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Journal of Energy Chemistry 2024年第8期95卷 364-379,I0009页

作者： Xue Cai caiping zhang Zeping Chen Linjing zhang Dirk Uwe Sauer Weihan Li National Active Distribution Network Technology Research Center Beijing Jiaotong UniversityBeijing 100044China Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives(ISEA)RWTH Aachen UniversityCampus Boulevard 8952074 AachenGermany Center for Ageing Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems(CARL)Campus-Boulevard 8952074 AachenGermany Juelich Aachen Research Alliance JARA-EnergyAachenGermany Helmholtz Institute Münster(HI MS) IEK-12Forschungszentrum JülichGermany

The safety and durability of lithium-ion batteries under mechanical constraints depend significantly on electrochemical,thermal,and mechanical fields in *** and quantifying the multi-field coupling behaviors requires interdisciplinary ***,we design experiments under mechanical constraints and introduce an in-situ analytical framework to clarify the complex interaction mechanisms and coupling degrees among multi-physics *** proposed analytical framework integrates the parameterization of equivalent models,in-situ mechanical analysis,and quantitative assessment of coupling *** results indicate that the significant impact of pressure on impedance at low temperatures results from the diffusion-controlled step,enhancing kinetics when external pressure,like 180 to 240 k Pa at 10℃,is *** diversity in control steps for the electrochemical reaction accounts for the varying impact of pressure on battery performance across different *** thermal expansion rate suggests that the swelling force varies by less than 1.60%per unit of elevated temperature during the lithiation *** introducing a composite metric,we quantify the coupling correlation and intensity between characteristic parameters and physical fields,uncovering the highest coupling degree in electrochemical-thermal *** results underscore the potential of analytical approaches in revealing the mechanisms of interaction among multi-fields,with the goal of enhancing battery performance and advancing battery management.

关键词： Lithium-ion battery Muti-field coupling Mechanical constraints Interaction mechanisms Quantitative analysis

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Fine mapping of the red plant gene R_1 in upland cotton (Gossypium hirsutum)

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Chinese Science Bulletin 2009年第9期54卷 1529-1533页

作者： ZHAO Liang CAI caiping zhang TianZhen GUO WangZhen National Key Laboratory of Crop Genetics & Germplasm Enhancement Cotton Research Institute Nanjing Agricultural University Nanjing 210095 China

Sub 16 is a substitution line with G. hirsutum cv. TM-1 genetic background except that the 16th chro-mosome (Chr. 16) is replaced by the corresponding homozygous chromosome of G. barbadense cv. 3-79, and T586 is a G. hirsutum multiple gene marker line with 8 dominant mutation genes. The R1 gene for anthocyanin pigmentation was tagged in Chr. 16 in T586. The objective of this research was to screen SSR markers tightly linked with R1 by using the F2 segregating population containing 1259 plants derived from the cross of Sub 16 and T586 and the backbone genetic linkage map from G. hir-sutum×G. barbadense BC1 newly updated by our laboratory. Genetic analysis suggested that the seg-regation ratio of red plants in the F2 population fit Mendelian 1:2:1 inheritance, confirming that the red plant trait was controlled by an incomplete dominance gene. Preliminary mapping of R1 was conducted using 237 randomLy selected F2 individuals and JoinMap v3.0 software. Then, a fine map of R1 was constructed using the F2 segregating population containing 1259 plants, and R1 was located between NAU4956 and NAU6752, with only 0.49 cM to the nearest maker loci (NAU6752). These results pro-vided a foundation for map-based cloning of R1 and further development of cotton cultivars with red fibers by transgenic technology.

关键词：植物基因棉花品种陆地棉精细定位遗传连锁图谱基因标记 SSR标记转基因技术

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Fault diagnosis for lithium-ion batteries in electric vehicles based on signal decomposition and two-dimensional feature clustering

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Green Energy and Intelligent Transportation 2022年第1期1卷 121-132页

作者： Shuowei Li caiping zhang Jingcai Du Xinwei Cong Linjing zhang Yan Jiang Leyi Wang National Active Distribution Network Technology Research Center(NANTEC) Beijing Jiaotong UniversityBeijing 100044China Sunwoda Electronic Co. Ltd.Shenzhen518100China Department of Electrical&Computer Engineering Wayne State UniversityDetroitMI 48202USA

Battery fault diagnosis is essential for ensuring the reliability and safety of electric vehicles(EVs).The existing battery fault diagnosis methods are difficult to detect faults at an early stage based on the real-world vehicle data since lithium-ion battery systems are usually accompanied by inconsistencies,which are difficult to distinguish from faults.A fault diagnosis method based on signal decomposition and two-dimensional feature clustering is introduced in this *** geometry mode decomposition(SGMD)is introduced to obtain the components characterizing battery states,and distance-based similarity measures with the normalized extended average voltage and dynamic time warping distances are established to evaluate the state of *** 2-dimensional feature clustering based on DBSCAN is developed to reduce the number of feature thresholds and differentiate flaw cells from the battery pack with only one parameter under a wide range of *** proposed method can achieve fault diagnosis and voltage anomaly identification as early as 43 days ahead of the thermal *** the results of four electric vehicles and the comparison with other traditional methods validated the proposed method with strong robustness,high reliability,and long time scale warning,and the method is easy to implement online.

关键词： Electric vehicle Fault diagnosis Extended average voltage Dynamic time warping Feature clustering

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Disaggregating Household Expenditures on Food Away from Home in Beijing by Type of Food Facility and Type of Meal

Disaggregating Household Expenditures on Food Away from Home...

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国家自然科学基金委员会管理科学部宏观管理与政策学科青年基金获得者交流研讨会

作者： caiping zhang Junfei Bai School of Economics Central University of Finance and Economics Center for Chinese Agricultural Policy Chinese Academy of SciencesInstitute of Geographical Sciences and National Resources Research

Using data from recently surveyed households, this study investigated factors influencing household food consumption away from home in Beijing by type of food facility and type of meal. Box-Cox transformed double-hurdle models were estimated. Consistent with prior expectations derived from the Becker’s household production and consumption theory, household income, time opportunity cost and other socio-demographic and economic factors were found to be important determinants of household participation and expenditure decisions for dining out. However, the importance of these factors varied by type of food facility and type of meal. Meanwhile, the estimated elasticities with respect to income were correspondingly higher than those for developed countries, suggesting that the demand for food away from home by Chinese households is still in an upward trend.

关键词： China food away from home type of food facility type of meal

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CHARACTERIZATION, DEVELOPMENT AND EXPLOITATION OF ESTDERIVED MICROSATELLITES IN GOSSYPIUM RAIMONDII ULBRICH

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Science Bulletin 2006年第5期51卷 557-561页

作者： WANG Changbiao, GUO Wangzhen, CAI caiping & zhang Tianzhen National Key Laboratory of Crop Genetics & Germplasm Enhancement, Cotton Research Institute, Nanjing Agricultural University, Nanjing 210095, China National Key Laboratory of Crop Genetics & Germplasm Enhancement Cotton Research Institute Nanjing Agricultural University Nanjing 210095 China

Microsatellite DNA or simple sequence repeats (SSRs) can be derived from expressed se- quence tags (ESTs). These markers are important for gene mapping as well as marker-assisted selection (MAS). To develop EST-SSRs for cotton gene map- ping, we selected and characterized functional markers in Gossypium raimondii, which consisted of 58906 non-redundant EST sequences from NCBI. Among them there were 2620 microsatellite se- quences containing 2818 EST-SSRs, which amoun- ted to 4.45% of the non-redundant starting sequence population. This incidence was equivalent to one EST-SSR in every 14.8 kb of G. raimondii genetic material. Among the different motifs ranging from 1 to 6 bp, trinucleotide repeats were most abundant (38.31%), followed by dinucleotide repeats (24.09%) and mononucleotide repeats (23.35%). Among all identified motif types, A/T had the highest frequency (18.67%), followed by AT/TA (14.83%). Among the compound motifs, tandem trinucleotides occurred with the highest frequency (48.65%). In all, we identi- fied 1554 EST-SSRs primer pair sequences. 300 of them were randomly selected to screen the poly- morphisms between the mapping parents G· hirsutum acc. TM-1 and G· barbadense cv. Hai7124, to con- struct linkage groups in cultivated allotetraploid cot- ton. Among them, 129 (43%) primer pairs were found to have polymorphisms. Using these EST-SSRs we can compare EST-SSR distributions among different cotton species and various chromosomal locations.

关键词： Gossypium raimondii Ulbrich EST-SSRs distribution molecular marker polymorphism.

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钢铁企业碳资产绩效评价指标体系构建及应用研究

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环境污染与防治 2017年第7期39卷 807-810页

作者：张彩平张莹南华大学管理学院湖南衡阳421001

在明确碳资源内涵的基础上将碳资产定义为有助于降低碳排放量并能创造低碳价值的各种有形和无形资产,并运用指标管理法构建了由碳资金周转率、碳排放率、碳配额结余率、碳固定资产收益率和低碳技术转化率组成的碳资产绩效评价指标体系... 详细信息

在明确碳资源内涵的基础上将碳资产定义为有助于降低碳排放量并能创造低碳价值的各种有形和无形资产,并运用指标管理法构建了由碳资金周转率、碳排放率、碳配额结余率、碳固定资产收益率和低碳技术转化率组成的碳资产绩效评价指标体系。同时,运用该指标体系评价BS钢铁企业的碳资产绩效,表明该指标体系能从多角度反映碳资产的管理效率和效益。最后,提出了碳资产管理领域需要进一步研究的问题。

关键词：低碳转型碳资产绩效评价指标体系

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基于等效电路模型的锂离子电池峰值功率估计的对比研究

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机械工程学报 2021年第14期57卷 64-76页

作者：蔡雪张彩萍张琳静张维戈高乐北京交通大学国家能源主动配电网技术研发中心北京100044

锂离子电池的功率状态(State of power, SOP)估计在电动汽车的电池管理系统中起着至关重要的作用。准确的参数化模型为SOP估计提供了重要的参数和结构信息。从电池内部机理出发,总结用于表征电化学反应过程的等效元件及方程所构成的等... 详细信息

锂离子电池的功率状态(State of power, SOP)估计在电动汽车的电池管理系统中起着至关重要的作用。准确的参数化模型为SOP估计提供了重要的参数和结构信息。从电池内部机理出发,总结用于表征电化学反应过程的等效元件及方程所构成的等效电路模型,并推导其电压仿真表达式。针对模型参数边界不准确而陷入局部最优和计算效率低的问题,提出基于电化学机理的参数边界确定方法。以DST工况为参数辨识数据集获取八种参数化模型,从模型精度和计算效率来验证参数化模型在FUDS工况下的鲁棒性和时效性。针对非线性模型无法获取峰值功率解析解问题,提出了基于多约束的SOP优化估计方法。最后,根据DST工况+恒功率下获取的SOP真值以验证所提算法在SOC10%放电和90%充电下的有效性。结果表明,温度对电化学反应和扩散限制的主导地位影响显著,所提模型最优估算方法在高低SOC区间的SOP估计误差均在8%以内。

关键词：锂离子电池等效电路模型参数边界参数辨识峰值功率

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任务型教学法在高职英语教学中的应用

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中国职业技术教育 2006年第31期22卷 27-29页

作者：张彩萍苏州农业职业技术学院江苏苏州215008

本文以高职英语精读课实际课堂教学任务的设计为例，从任务的界定、类型及教学模式的设计等几个方面，探讨了如何在英语教学中渗透任务型语言教学理念，以达到强化教学内容的实践性、提高语言交际能力的目的。

关键词：任务型教学法设计原则应用实例

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