最新刊期
卷 71 ， 期 6 ， 2025
- “在人工智能领域，专家建立了深度学习体系，为智能技术发展提供新方向。”
- “在新型储能技术领域，我国研究聚焦工程实践和政策导向，国际研究注重材料机理与理论创新，电池储能研究热度最高，我国正迈向系统协同与智能化发展阶段。”摘要：To reveal the research landscape and development trajectories of typical emerging energy storage technologies in China, this study focuses on five representative types: battery energy storage, molten salt energy storage, compressed air energy storage, flywheel energy storage, and hydrogen energy storage. A comparative bibliometric analysis was conducted based on core literature from the CNKI and Web of Science (WOS) databases during 2015—2025. The results indicate that, overall, domestic research is characterized by engineering practice and policy orientation, whereas international studies emphasize material mechanisms and theoretical innovation, reflecting a differentiated evolution of research pathways. Among them, battery energy storage exhibits the highest research intensity: domestic studies focus on state-of-charge (SOC) estimation, safety management, and system operation, while international research concentrates on solid electrolytes and post-lithium material systems. Molten salt energy storage has evolved from solar-thermal coupling toward multi-temperature thermochemical applications, emphasizing heat transfer efficiency and thermal performance improvement. Compressed air energy storage research centers on thermo-hydro-mechanical modeling and heat recovery optimization, showing strong potential for long-duration peak regulation. Flywheel energy storage has shifted from structural and control optimization to system integration and inertia support, and hydrogen energy storage demonstrates multi-energy coupling among wind, solar, and hydrogen systems, highlighting progress in hydrogen production efficiency. Overall, China’s research on emerging energy storage technologies is transitioning from single-technology breakthroughs toward system-level synergy and intelligent development. The complementary relationship between short-term power-type and long-duration capacity-type storage technologies is becoming clearer, with future progress expected to move toward higher safety, lower cost, longer lifespan, and multi-energy integration-providing critical support for the construction of a new-type power system.关键词：emerging energy storage;battery energy storage;molten salt energy storage;compressed air energy storage;flywheel energy storage;hydrogen energy storage;bibliometric analysis205|76|0更新时间：2026-01-13
- “最新研究提出一种结合物理模型和深度学习的锂离子电池荷电状态估计方法，有效提升模型在复杂工况下的建模能力，实验结果表明具有高预测精度和鲁棒性。”摘要：Accurate estimation of the State of Charge (SOC) is fundamental to ensure the reliable operation of lithium-ion batteries. To address the issue of insufficient input features in existing deep learning methods, this paper proposes an SOC estimation method based on a combination of a physical model and a deep learning algorithm. This method exploits the local feature extraction capability of the Convolutional Neural Network (CNN) and the temporal sequence processing ability of the Bi-directional Gated Recurrent Unit (BiGRU). By introducing the terminal voltage output from a first-order Resistor-Capacitor （RC） model as an input feature, which is combined with the measured voltage and current to form the neural network input, the modeling capability of the CNN-BiGRU under complex dynamic operating conditions is enhanced. Experimental results demonstrate the good SOC estimation performance of the CNN-BiGRU model. For the Center for Advanced Life Cycle Engineering （CALCE) dataset of University of Maryland, the root mean square error (RMSE) is 0.16% and the mean absolute error (MAE) is 0.12% at room temperature (25 ℃). Furthermore, the proposed model exhibits high prediction accuracy and robustness for lithium-ion batteries under varying ambient temperatures and different degradation levels.关键词：lithium-ion battery;SOC estimation;physical model;CNN-BiGRU model50|29|0更新时间：2026-01-13
- “在电池管理领域，研究人员提出了一种基于CL-NARX神经网络的SOC估计模型，有效提高了估计精度和鲁棒性，为锂离子电池安全运行提供技术支持。”摘要：To address the problems of insufficient estimation accuracy, error accumulation, and poor robustness of traditional State of Charge (SOC) estimation models under actual operating conditions, this paper proposes a Closed-loop Nonlinear Autoregressive eXogenous (CL-NARX) neural network model to improve SOC estimation accuracy. The model enhances the fitting capability for complex battery processes by introducing a closed-loop feedback mechanism, effectively suppressing error accumulation, and strengthening robustness by optimizing key hyperparameters. The experimental results show that the model achieves optimal performance, when the training iteration number is 150, the number of neurons in the hidden layer is 10, the input delay layers are 5, and the output delay layers are 2, with estimation errors significantly superior to other neural network models. The maximum error, RMSE, MAE, and MAPE are reduced to 2.58%, 1.41%, 1.36%, and 4.57%, respectively. The model demonstrates high accuracy, effective error handling, and strong robustness, providing reliable technical support for the safe operation of lithium-ion batteries.关键词：lithium-ion battery;State of Charge (SOC);Closed-Loop Nonlinear Autoregressive eXogenous (CL-NARX);backpropagation (BP) neural network45|40|0更新时间：2026-01-13
- “在动力电池领域，专家提出了基于MOSFET热量回收的低温预热方法，通过电-热耦合模型优化，有效提升了电池低温性能。”摘要：The performance of power batteries declines significantly in low-temperature environments, which not only reduces the driving range but also severely impacts the battery’s service life. A low-temperature preheating method for power batteries based on waste heat recovery using Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) is proposed. By dynamically adjusting the drive voltage of the MOSFET, internal heating is achieved through controlling the discharge of the battery pack, and external heating is applied to batteries through air convection, realizing combined internal-external low-temperature preheating of the battery pack. Simultaneously, an electrothermal coupling model is established, and a subtraction-average-based optimizer is used to optimize the low-temperature preheating strategy. An experimental platform for low-temperature preheating of a 12-cell lithium-ion battery pack is set up for experimental verification. The results show that the scheme takes only 124 s to heat the battery from -20 °C to 0 °C, with a temperature rise rate of 9.68 °C/min. Compared to the non-optimized scheme, the time is reduced by 10.8%, and the energy loss is reduced by 10.3%, achieving a comprehensive optimal of heating time and energy loss.关键词：lithium-ion battery;power battery;low temperature preheating;subtraction-average-based optimizer88|33|0更新时间：2026-01-13
- “最新研究进展显示，专家建立了融合LSTM和Informer网络的锂离子电池SOH估计方法，为电动汽车续航性能和安全问题提供解决方案。”摘要：Lithium-ion batteries are prone to capacity degradation during long-term operation, which significantly affects the driving range and safety of electric vehicles. To accurately estimate the battery’s state of health (SOH), this study proposes a hybrid SOH estimation method that integrates a Long Short-Term Memory (LSTM) network with an Informer architecture. The Local Outlier Factor (LOF) algorithm is employed to preprocess the charging data of experimental batteries, and the maximum tangent angle of the charging voltage curve, along with its corresponding time, is extracted as health features. The correlation between these health features and SOH is analyzed using the Spearman correlation coefficient. By combining the advantages of LSTM in capturing local temporal dependencies with the Informer’s ability to model global relationships, an LSTM–Informer serial network is constructed. The extracted health features are used as model inputs to achieve accurate SOH estimation. Experimental results demonstrate that the proposed method achieves high estimation accuracy, with the maximum absolute error maintained within 2.5%, and both the root mean square error (RMSE) and mean absolute error (MAE) within 1%. Compared with traditional single-network methods, the proposed method exhibits superior estimation performance and generalization capability.关键词：lithium-ion battery;state of health (SOH);outlier handling;Long Short-Term Memory (LSTM) network;Informer network71|39|0更新时间：2026-01-13
- “在固体氧化物燃料电池领域，专家提出了基于动态补偿机制的模型预测控制方法，有效提升了电池的动态响应性能，为稳定控制问题提供解决方案。”摘要：To address the stable control problem of the output voltage in solid oxide fuel cells (SOFC), a model predictive control (MPC) method based on a dynamic compensation mechanism is proposed. A model is established according to the thermoelectric mechanism of SOFC, and its rationality is verified through steady-state and dynamic performance analysis. An MPC controller incorporating dynamic compensation terms is designed on the basis of the model, where a state prediction compensation and a control weight self-adjustment mechanism are introduced to enhance the dynamic response performance of SOFC. Experimental results show that, compared with the linear active disturbance rejection control (LADRC) method, the proposed MPC method reduces the voltage stabilization time by 76.0% and 86.7% respectively under two typical operating conditions: reference voltage tracking and load current disturbance. Meanwhile, the overshoot is decreased by 0.02 V and 0.25 V respectively, demonstrating superior dynamic tracking and anti-disturbance performance.关键词：solid oxide fuel cell (SOFC);mechanism modeling;dynamic compensation mechanism;model predictive control;active disturbance rejection control37|24|0更新时间：2026-01-13
- “在电动汽车充电领域，研究者提出了一种新策略，通过强化学习算法优化充电过程，有效降低充电成本并提升充电速度。”摘要：Most of the existing charging methods primarily focus on charging speed and charging safety, ignoring the economic loss of the user during the charging process. To address this limitation, this paper proposes a fast-charging strategy that takes into account battery degradation and time-of-use electricity price. The time-of-use electricity price serves as an input parameter; the battery degradation and power loss are converted into charging economic loss, which is optimized by using the reinforcement learning algorithm and the electrochemical-thermal-aging coupling model. The results show that the proposed method can adaptively adjust the charging rate according to the time-of-use electricity price. Given the same charging speed, this method reduces economic loss by 20.9% compared with the constant-current and constant-voltage charging method and 15.3% compared with the multi-stage constant current charging method. Under the same physical constraints, this method is 21.1% faster than the pulse charging method and 9.9% faster than the constant current constant voltage method, optimizing both charging cost and charging speed.关键词：lithium-ion battery;time-of-use electricity price;battery degradation;fast-charging strategy91|43|0更新时间：2026-01-13
- “在固体氧化物燃料电池系统故障识别领域，专家提出了融合聚类和RBF-SVM的故障识别方法，为提高故障识别准确率提供解决方案。”摘要：To accurately identify faults in Solid Oxide Fuel Cell (SOFC) systems and overcome the challenges of traditional methods such as difficulties in parameter determination, high result randomness, and limitations in complex data processing, a fault identification method based on fusion clustering and Radial Basis Function Support Vector Machine (RBF-SVM) is proposed. This method employs a clustering algorithm based on a fusion mechanism to process the performance degradation fault data of the SOFC system reformer catalyst, obtaining clustering labels under different fault levels, and then uses the RBF-SVM algorithm to train the classified fault data to develop a fault identification model. This model can map fault feature information to higher-dimensional spaces to enhance fault identification capabilities and is further applied to identify air and fuel leakage faults. Experimental results demonstrate that the proposed fusion clustering algorithm effectively classifies faults, and the RBF-SVM fault identification model achieves 99.3% accuracy in identifying reformer catalyst degradation faults, 99.9% accuracy for air leakage faults, and 99.4% accuracy for fuel leakage faults.关键词：solid oxide fuel cell (SOFC);faults identification;fusion clustering;radial basis function support vector machine (RBF-SVM)82|31|0更新时间：2026-01-13
- “在新能源传输领域，专家采用CFD软件分析海底电缆电磁场分布，为保护海洋生态提供新思路。”摘要：Submarine cables serve as critical new energy transmission infrastructure connecting land and sea, and the electromagnetic radiation generated during their operation exerts significant impacts on the marine ecological environment. To address this issue, this study employs Computational Fluid Dynamics (CFD) software and finite element simulation to conduct an in-depth analysis of the electromagnetic field distribution patterns in high-voltage alternating current submarine cables. Simulation accuracy is enhanced through refined mesh division and optimization of material parameters, while a 2D axisymmetric model is constructed to simplify calculations. The results demonstrate that: the surface potential of the cable exhibits significant spatial heterogeneity, with the electric field intensity reaching 9.02×106 V/m on the inner side of the insulation layer and a local minimum of 0 V/m in the core region, reflecting the localized characteristics of strong electric field sources; the magnetic field is distributed in concentric circles centered on the cable core, with the central magnetic flux density significantly higher than that in the peripheral areas, showing a gradient decay with increasing distance; the ferromagnetic properties of the armor layer cause magnetic field distortion, and the phase differences of a three-phase current further exacerbate the spatial non-uniformity of the magnetic field.关键词：finite element simulation;2D axisymmetric model;three-core submarine cable;electromagnetic radiation;electromagnetic field characteristics99|40|0更新时间：2026-01-13
- “最新研究发现，氧化锌纳米颗粒与土霉素共暴露显著提高细菌接合频率，加剧耐药性传播风险。”摘要：Taking the conjugative transfer of antibiotic resistance genes (ARGs) as an example for horizontal gene transfer, the effects of zinc oxide nanoparticles (ZnONPs) and oxytetracycline (OTC) co-exposure on the ARGs conjugative transfer frequency within the same bacterial genus (intra-genus) and across different genera (inter-genus) were investigated. Further, the mechanisms by which co-exposure influences the conjugative transfer were explored. The results showed that the co-exposure of 1 mg/L ZnONPs and 20 μg/L OTC increased intra-genus and inter-genus conjugation frequencies by 2.08-fold and 2.34-fold, respectively, which was significantly higher than the individual exposures. The co-exposure elevated intracellular reactive oxygen species (ROS) generation, enhanced cell membrane permeability, promoted extracellular polymeric substance secretion, and upregulated conjugation-related genes while downregulating negative regulatory genes. These results indicate that the nanomaterials and antibiotics co-residue in environments may exacerbate the risk of bacterial resistance transmission.关键词：antibiotic resistance gene;conjugative transfer;nanomaterials;zinc oxide;oxytetracycline;co-exposure;antibiotic resistance45|26|0更新时间：2026-01-13
- “据最新研究，三峡库区香溪河VOCs污染特征及健康风险评估显示，水体和沉积物未对大气VOCs污染产生贡献，土壤中农药残留1，2，4-三氯苯对大气VOCs污染产生贡献。”摘要：In order to reveal the distribution and characteristics of volatile organic compounds (VOCs) along typical tributaries of the Three Gorges Reservoir Region, evaluate the environmental impact and health risks of VOCs, 8 sites were set up along the Xiangxi River in 2021 (March, June, September, and December), the samples of air, water, soil (altitude 175-190 m), and sediment(altitude below 145 m) were collected, 59 VOCs were determined, the ·OH loss rate(R) and ozone formation potential(OFP) were calculated, and the hazard index (HI) and lifetime carcinogenic risk (LCR) of VOCs were evaluated. The results showed that VOCs were not detected in all samples of water and sediment, VOCs of most soil samples was not detected in summer and autumn, 1,2,3-trichlorobenzene (0.35-0.41 μg/kg) and 1,2,4-trichlorobenzene(0.39-0.52 μg/kg) of all soil samples were detected in spring, 1,2,4-trichlorobenzene(0.34-0.42 μg/kg) was detected in winter, the spatial distribution of 1,2,3-trichlorobenzene and 1,2,4-trichlorobenzene were upstream, downstream, tributaries, and midstream from large to small. The average concentration of atmospheric VOCs was (14.69±9.1) μg/m3, with aromatic hydrocarbons (56.3%), oxygenated volatile organic compounds (25.2%), halogenated hydrocarbons (18.5%); from large to small, the seasonal variation was spring, autumn, summer, and winter, the spatial variation were upstream, midstream, downstream, tributaries. most of the top 7 substances about the contribution rankings of R and OFP were aromatic hydrocarbons at different sites and four seasons. The HI was less than 1 at every site, and the range of LCR was from 5.2×10-6 to 9.6×10-6. The research has shown that there was no contribution to atmospheric VOCs pollution in water and sediments, while pesticide residues such as 1,2,4-trichlorobenzene of soil contributed to atmospheric VOCs pollution, aromatic hydrocarbons were the main active components for contribution species of R and OFP. The HIs were all at an acceptable safety level, the LCRs were all in grade Ⅱ of low probability. The study can provide theoretical reference for controlling VOCs emissions and reducing their environmental impact and health risks along the Xiangxi River.关键词：Xiangxi River;volatile organic compounds (VOCs);·OH loss rate;ozone formation potential;health risk38|35|0更新时间：2026-01-13
- “最新研究揭示没食子酸甲酯消除羟基自由基的机制，可作为羟基自由基清除剂。”摘要：The reaction mechanism of the scavenging of hydroxyl radical(·OH) by methyl gallate(MG) in physiological environment (aqueous phase at 310.15 K and 1.013×105 Pa) was investigated by using the density functional theory methods M06-2X and MN15 in combination with the SMD model of the self-consistent reaction field theory at the two levels of SMD/MN15/6-311++G(4df,3pd)//SMD/M06-2X/6-311+G(d,p). There are three reaction channels for MG scavenging ·OH: H extracting by ·OH, addition of ·OH to unsaturated C, and single electron transfer from MG to ·OH. The calculations show that in the extraction channel, the reaction of ·OH extracting hydroxyl H is the most advantageous, which is a barrier-free and significantly exothermic process; the reaction of ·OH extracting methyl H is a subdominant reaction, which is an exothermic process with a free energy barrier of 37.8 to 41.2 kJ/mol. In the addition reaction channel, the addition of ·OH with unsaturated C is an exothermic process with a free energy barrier of 0.3 to 47.3 kJ/mol; the single-electron transfer from MG to ·OH is a slightly endothermic process with a free energy barrier of 42.1 kJ/mol. The results indicate that MG can eliminate ·OH radicals through three pathways: extraction H, addition, and electron transfer, and MG can be a good scavenger for ·OH radicals.关键词：methyl gallate;hydroxyl radical;density functional theory;self-consistent reaction field theory;transition state;electron transfer;free energy barrier37|22|0更新时间：2026-01-13
- “在光催化领域，研究人员合成了新型不对称四氮杂卟啉钴配合物CoPz（SBu）7（OPr），实现了高效光催化氧化苄胺合成N-苄基-1-苯基甲亚胺。”摘要：The asymmetric metal-free hepta(butylthio)-mono(propoxy)porphyrazine (H2Pz(SBu)7(OPr)) and its cobalt complex CoPz(SBu)7(OPr) were successfully synthesized, which were well characterized by ultraviolet-visible absorption spectroscopy (UV-Vis), 1H nuclear magnetic resonance spectroscopy (1H NMR) and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). The photocatalytic performance of CoPz(SBu)7(OPr) under visible light (≥420 nm) irradiation was investigated using atmospheric O2 as the oxidant. The results show that CoPz(SBu)7(OPr) can effectively photocatalyze the oxidation of benzylamine to N-benzyl-1-phenylmethanimine under visible light. The conversion of benzylamine reaches up to 99.2% after 3 h, and the selectivity for N-benzyl-1-phenylmethanimine is 92.9%. Superoxide anion radical (O2·-) and singlet oxygen (1O2) are the main reactive oxygen species in this photocatalytic process.关键词：cobalt thioporphyrazine;photocatalysis;amine;imine39|52|0更新时间：2026-01-13
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