Chinese Journal of Electrical Engineering最新文献_第6页

Multi-Dimensional Characterization of Lithium-Ion Battery States via Voltage and Multiscale Mechanical Feature Integration from Electrochemical-Thermal-Mechanical Models 基于电压和电化学-热-力学模型的多尺度力学特征集成的锂离子电池状态多维表征

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-07 DOI: 10.23919/CJEE.2025.000193

Xiaoyu Li;Shen Zhao;Xinyu Wei;Yanli Zhu;Jun Tian

{"title":"Multi-Dimensional Characterization of Lithium-Ion Battery States via Voltage and Multiscale Mechanical Feature Integration from Electrochemical-Thermal-Mechanical Models","authors":"Xiaoyu Li;Shen Zhao;Xinyu Wei;Yanli Zhu;Jun Tian","doi":"10.23919/CJEE.2025.000193","DOIUrl":"https://doi.org/10.23919/CJEE.2025.000193","url":null,"abstract":"Accurate state characterization of lithium-ion batteries (LIBs) is critical for enhancing their reliability and extending the lifespan of battery management systems. The inherent coupling of electrochemical, thermal, and mechanical phenomena necessitates multidimensional parameter sensing for a precise state assessment. Herein, a coupled electrochemical-thermal-mechanical (ETM) multi-physics modeling framework is proposed to reveal the multiscale parameter coevolution mechanism and explore novel state-of-charge (SOC) estimation indicators. By integrating a pseudo-two-dimensional (P2D) electrochemical model, thermogenesis equations, and elastic-plastic mechanics constitutive relations, an aging kinetic model considering the loss of active material (LAM) and loss of lithium inventory (LLI) is constructed. Various driving cycles, including constant current discharge, urban dynamometer driving schedule (UDDS) dynamics, and <tex>$1C$</tex> cyclic charge/discharge experiments, are utilized to verify the proposed model with the two indices of voltage and strain. Based on the validated model, the aging kinetics of the coupled P2D electrochemical-3D thermo-mechanical system are first investigated to quantify the interaction mechanisms of mechanical stress, heat production, and electrochemical polarization under quasi-static and dynamic loading. The results demonstrate that displacement and maximum strain metrics detect microstructural damage earlier, and synergy with voltage signals reduces the estimation deviations of traditional methods under wide temperature and dynamic conditions, offering a novel paradigm for multidimensional state estimation.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"50-72"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11476969","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Zeta-SEPIC Converter-Based Integrated Battery Equalization Method for Lithium-ion Battery Strings 基于Zeta-SEPIC转换器的锂离子电池组集成电池均衡方法

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-07 DOI: 10.23919/CJEE.2026.000007

Xianbin Qi;Penglei Liu;Peng Qin;Mingzhu Fang;Helong Li;Lijian Ding

{"title":"Zeta-SEPIC Converter-Based Integrated Battery Equalization Method for Lithium-ion Battery Strings","authors":"Xianbin Qi;Penglei Liu;Peng Qin;Mingzhu Fang;Helong Li;Lijian Ding","doi":"10.23919/CJEE.2026.000007","DOIUrl":"https://doi.org/10.23919/CJEE.2026.000007","url":null,"abstract":"Battery equalization management is a key technology for ensuring the safe and efficient operation of equipment containing battery energy storage systems, such as electric vehicles, drones, and renewable energy generation. In this paper, an integrated equalizer for lithium-ion battery strings is proposed. This equalizer enables the multiplexing of switches in a traditional centralized equalization system and integrates the bidirectional switch used for battery selection in the switch array and power switch used for energy conversion in the bidirectional Zeta-SEPIC converter, thereby obtaining high-power-density characteristics. This equalizer has a buffer-based structure that guarantees efficiency and expandability when equalizing series-connected battery strings. Compared with conventional methods, the proposed scheme exhibits a controllable equalization current, small number of components, low cost, and high efficiency, and has broad application prospects and practical value. The operating principles, theoretical derivations, and design considerations are thoroughly analyzed. An experimental test platform is built, and experiments are conducted using a four-cell lithium-ion battery string. The experimental and comparison results verified the superiority and feasibility of the Zeta-SEPIC converter-based battery equalizer.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"107-119"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11476840","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Error Suppression of Magnetic Encoder Using Improved Second-Order Generalized Integrator and Harmonic Decoupling Network 基于改进二阶广义积分器和谐波解耦网络的磁编码器误差抑制

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-07 DOI: 10.23919/CJEE.2025.000150

Shuang Wang;Hanyi He;Tianren Li;Hao Li;Jianfei Zhao

{"title":"Error Suppression of Magnetic Encoder Using Improved Second-Order Generalized Integrator and Harmonic Decoupling Network","authors":"Shuang Wang;Hanyi He;Tianren Li;Hao Li;Jianfei Zhao","doi":"10.23919/CJEE.2025.000150","DOIUrl":"https://doi.org/10.23919/CJEE.2025.000150","url":null,"abstract":"Compared with traditional position sensors, magnetic encoders do not require optical components, which are easily damaged, have complex winding structures, and have higher reliability, better environmental resistance, and stronger vibration resistance. However, owing to some non-ideal factors, the output angle of the magnetic encoder may have an amplitude error, phase offset, DC bias, and harmonic deviation, which greatly affect the decoding accuracy. A magnetic encoder error compensation algorithm is proposed based on an improved second-order generalized integrator (ISOGI). First, the errors existing in the magnetic encoder are analyzed and verified and then a dual improved second-order generalized integrator harmonic decoupling network phase-lock loop (DISOGI-HDN-PLL) is proposed, which has the ability to compensate for low-order harmonics and other errors. This proposed method compensates for various errors under constant and high-speed conditions. In addition, it has good response and robustness, effectively improving the decoding accuracy of the magnetic encoder. Simulation and experimental results demonstrate the effectiveness and applicability of the proposed algorithm.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"355-370"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11476979","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Review of GaN HEMTs: Characteristics, Parameter Impacts, and Strategies for Oscillation Suppression GaN hemt的特性、参数影响和振荡抑制策略综述

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2025-08-27 DOI: 10.23919/CJEE.2025.000147

Jinchao Pan;Yachao Ji;Guidong Zhang;Samson S. Yu;Zhong Li

引用次数: 0

Data-Driven Battery SOC Estimation: A CNN-ResNet-BiLSTM Framework 数据驱动电池荷电状态评估：CNN-ResNet-BiLSTM架构

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-07 DOI: 10.23919/CJEE.2026.000008

Chuanxin Fan;Yanfu Liu;Kailong Liu;Qiao Peng

{"title":"Data-Driven Battery SOC Estimation: A CNN-ResNet-BiLSTM Framework","authors":"Chuanxin Fan;Yanfu Liu;Kailong Liu;Qiao Peng","doi":"10.23919/CJEE.2026.000008","DOIUrl":"https://doi.org/10.23919/CJEE.2026.000008","url":null,"abstract":"With the advancement in artificial intelligence technology, a series of hybrid algorithms have been applied to battery state-of-charge (SOC) estimation. However, existing approaches face challenges in extracting deep features and suffer from gradient vanishing, which prevents the construction of deeper networks. A novel data-driven fusion algorithm, the CNN-ResNet-BiLSTM framework, is proposed to further improve the SOC estimation accuracy. The proposed method incorporates a residual network (ResNet) to resolve gradient vanishing in deep convolutional neural networks (CNNs), thereby enabling deeper integration between the CNN and bidirectional long short-term memory (BiLSTM). Furthermore, this study employs grey relation analysis for feature construction to enhance the quality of the derivative and historical category data. Experimental results show that the proposed framework achieves 0.348% root mean square error and 0.255% mean absolute error during a driving cycle, indicating exceptional performance in SOC estimation. This demonstrates the outstanding generalization capability of the proposed framework through cross-condition validation, which provides a theoretical foundation for practical SOC estimation applications.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"133-143"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11476957","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148517810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model Predictive Current Control of Permanent Magnet Synchronous Linear Motor Based on Expanded Control Set 基于扩展控制集的永磁同步直线电机模型预测电流控制

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2025-10-06 DOI: 10.23919/CJEE.2025.000168

Qiaoling Yang;Huijun Shi;Shunwu Liu;Yong Chang

{"title":"Model Predictive Current Control of Permanent Magnet Synchronous Linear Motor Based on Expanded Control Set","authors":"Qiaoling Yang;Huijun Shi;Shunwu Liu;Yong Chang","doi":"10.23919/CJEE.2025.000168","DOIUrl":"https://doi.org/10.23919/CJEE.2025.000168","url":null,"abstract":"Finite control set model predictive current control (FCS-MPCC) often induces notable thrust fluctuations and elevated current harmonics in permanent magnet synchronous linear motor (PMSLM) drives. These issues primarily arise due to the limited number of available voltage vectors, which compromise steady-state accuracy. To address this problem, a model predictive current control strategy utilizing an expanded control set is proposed. In this approach, virtual voltage vectors are synthesized from the fundamental voltage vectors, expanding the control set to include 38 candidate vectors. Using current prediction equations and a value function, the optimal candidate region is identified by preselecting a central voltage vector, which significantly reduces the number of required optimization searches. The voltage vectors within this region are evaluated at two distinct prediction times. After analyzing the results from both moments, the voltage vector that yields the smallest current prediction error is selected as the optimal control input. A simulation analysis is conducted to validate the effectiveness of the proposed method. The results demonstrate that, compared to conventional FCS-MPCC, the expanded control set approach significantly reduces current harmonics and thrust fluctuations, while also mitigating the increase in switching frequency typically associated with a larger control set.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"333-343"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11194304","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MSFF-DM-Based SOH Estimation for Lithium-Ion Battery Packs Utilizing System and Cell Features 基于msff - dm的锂离子电池组SOH估算

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-07 DOI: 10.23919/CJEE.2026.000011

Chaolong Zhang;Yupeng Wu;Anxiang Wang;Min Xie;Panfen Yin;Guoqing Hua;Kaixin Cheng;Kui Shao

{"title":"MSFF-DM-Based SOH Estimation for Lithium-Ion Battery Packs Utilizing System and Cell Features","authors":"Chaolong Zhang;Yupeng Wu;Anxiang Wang;Min Xie;Panfen Yin;Guoqing Hua;Kaixin Cheng;Kui Shao","doi":"10.23919/CJEE.2026.000011","DOIUrl":"https://doi.org/10.23919/CJEE.2026.000011","url":null,"abstract":"Accurate estimation of the state of health (SOH) is crucial for safe operation and lifespan extension of lithium-ion battery packs. A multiscale feature fusion decision model (MSFF-DM)-based approach for SOH estimation of lithium-ion battery packs utilizing both system-level and cell-level features is proposed. First, the current, voltage, and temperature data of the lithium-ion battery pack are measured during the charging stage, and the interquartile range (IQR) is extracted through incremental energy (IE) analysis to characterize the pack-level system characteristics. Based on the individual cell temperature and voltage, a combined temperature-weighted voltage inconsistency is constructed to capture inter-cell differences. Subsequently, an MSFF-DM estimation model composed of a multiscale feature extraction layer, feature fusion layer, and decision-making layer is developed. After the two types of features are input into the model for training, the experimental data are used for testing to achieve accurate SOH estimation for the battery pack. The results showed that the average absolute error and root mean square error of SOH estimation using the proposed method are 0.36% and 0.44%, respectively, and the average coefficient of determination exceeded 99%. These results demonstrate that the proposed method outperforms the traditional approaches.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"120-132"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11476834","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review of Recent Advanced Predictive Control Methods for Motor Drive Systems in Transportation Electrification 交通运输电气化电机驱动系统的先进预测控制方法综述

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2025-03-06 DOI: 10.23919/CJEE.2025.000125

Kai Ni;Yong Yang;Mingdi Fan;Chun Gan;Yang Xiao;Yihua Hu;Jose Rodriguez

{"title":"Review of Recent Advanced Predictive Control Methods for Motor Drive Systems in Transportation Electrification","authors":"Kai Ni;Yong Yang;Mingdi Fan;Chun Gan;Yang Xiao;Yihua Hu;Jose Rodriguez","doi":"10.23919/CJEE.2025.000125","DOIUrl":"https://doi.org/10.23919/CJEE.2025.000125","url":null,"abstract":"In recent years, the need to ensure the secure and efficient functionality of electric vehicles, more-electric aircraft, and all-electric ships has driven the development of sophisticated control techniques uniquely suited to diverse motor-drive systems. Predictive control methods stand out for their adaptability, multi-objective capabilities, and ease of managing constraints and nonlinearities. The primary objective is to enhance the stability and responsiveness of electric motor control systems, a goal that resonates with the findings of numerous academic studies. It is also imperative to minimize computational burden, which is a critical factor in the engineering of these systems. Furthermore, considering the inevitability of parameter fluctuations in motor control systems due to prolonged use, it is essential to strengthen the robustness of control methodologies. Fault tolerance is a vital aspect and needs to be considered, particularly for applications in the transportation industry. A comprehensive review of recently developed advanced predictive control methods for motor-drive systems in the context of transportation electrification is provided. This emphasizes the enhancement of system performance, alleviation of computational load, strengthening of robustness, and integration of fault-tolerance mechanisms.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"194-215"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10989598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cloud-Edge Collaborative Forecasting for Industrial Photovoltaic-Storage-Charging Systems 工业光伏-储能-充电系统的云边缘协同预测

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-07 DOI: 10.23919/CJEE.2026.000022

Dongxu Guo;Zequan Yang;Xingwen Dong;Xiangqi Meng;Guoxin Yu;Yuejiu Zheng

{"title":"Cloud-Edge Collaborative Forecasting for Industrial Photovoltaic-Storage-Charging Systems","authors":"Dongxu Guo;Zequan Yang;Xingwen Dong;Xiangqi Meng;Guoxin Yu;Yuejiu Zheng","doi":"10.23919/CJEE.2026.000022","DOIUrl":"https://doi.org/10.23919/CJEE.2026.000022","url":null,"abstract":"With the growing integration of renewable energy into modern power grids, photovoltaic (PV) power has emerged as a pivotal element that is frequently coupled with energy-storage systems to enhance dispatch efficiency. However, the inherent variability in PV power generation and user load present significant challenges for accurate system scheduling. A key difficulty is that the PV output is often subject to artificial power curtailment, creating a non-linear relationship with solar irradiance, whereas charging loads exhibit distinct patterns between weekdays and weekends. To address this problem, a cloud-edge collaborative prediction system is proposed to implemented in a local energy management system (EMS). This system adopts a meta-learning-based multihead regression model that integrates XGBoost, support vector regression, random forest, CatBoost, and a multilayer perceptron. For PV power prediction, historical rolling lag features are introduced to capture the curtailment patterns. For load prediction, time-based features are designed to reflect the behavioral habits of electricity consumption over time. The system is successfully deployed at a charging station in the Haier Industrial Park. A practically validated solution is demonstrated for addressing uncertainties in integrated energy systems, along with the effectiveness of edge-deployed algorithms in optimizing storage strategies and reducing operational costs.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"171-184"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11476956","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mechanism Analysis and Advanced Control for Virtual Synchronous Generators Under Weak Grid Conditions During LVRT 弱电网条件下LVRT虚拟同步发电机机理分析及超前控制

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Chinese Journal of Electrical Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-07 DOI: 10.23919/CJEE.2025.000112

Jiadong Sun;Xiangyang Xing;Rui Zhang;Zhiyuan Meng

{"title":"Mechanism Analysis and Advanced Control for Virtual Synchronous Generators Under Weak Grid Conditions During LVRT","authors":"Jiadong Sun;Xiangyang Xing;Rui Zhang;Zhiyuan Meng","doi":"10.23919/CJEE.2025.000112","DOIUrl":"https://doi.org/10.23919/CJEE.2025.000112","url":null,"abstract":"Virtual synchronous generator (VSG) is a grid-friendly converter that can effectively support the grid and operate stably in a weak grid. However, VSGs are susceptible to grid voltage sags, which may induce overcurrent and transient instability due to their synchronous generator-like properties. In particular, as grid strength decreases, the output capacity of the VSG is reduced, making transient instability a more severe issue than overcurrent when a voltage sag occurs. Transient instability poses a threat to power system security and stability. To address these issues, a mechanism analysis and an advanced control strategy are proposed for VSGs operating under weak grid conditions during low-voltage ride-through (LVRT). First, the factors influencing transient stability are analyzed. Second, the characteristics of LVRT-related issues in weak grid conditions are examined. Finally, an advanced LVRT control strategy and a novel virtual impedance (VI) structure are proposed to maintain transient stability and suppress overcurrent. Benefiting from this strategy, transient stability is improved, and the post-fault period is expected to be short and smooth. Simulations and experiments are conducted to verify the effectiveness of the proposed approach.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"12 1","pages":"306-319"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11476967","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0