Journal of energy storage最新文献_第2页

Unleashing heterogeneous distributed energy storage potential via aggregation-disaggregation framework for enhanced flexibility in distribution power networks 通过聚合-分解框架释放异构分布式储能潜力，增强配电网灵活性

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120568

Hao Hu , Zhijian Hu , Shiwei Xie , Tiange Li , Shenghui Liu

The increasing integration of renewable energy demands unprecedented flexibility from Distribution Power Networks (DPNs), and exploiting the energy storage characteristics inherent in distributed energy storage systems (DESs) provides critical support for enhancing DPN flexibility. This paper proposes a flexible operational optimization framework incorporating DESs participation in demand response (DR), designed to unlock the energy storage regulation potential inherent in DESs. First, an integrated operating region (OR) profile model is developed for DESs, effectively harnessing flexibility potentials from electric vehicles, energy storage systems, and backup energy storage in 5G base stations, and strategically incorporating thermostatically controlled loads to exploit their inherent thermal energy storage properties. Second, an aggregation-disaggregation mechanism for DESs is introduced to coordinate and regulate the flexibility of massive DESs, with a priority-based methodology being applied to the disaggregation of heterogeneous DESs. Finally, a real-time optimization model is established for aggregated DESs participating in DR of DPN, harnessing the adjustable energy storage characteristics of DESs to dynamically optimize operational power flow and enhance the DR capability. The effectiveness and superiority of the proposed DPN optimization framework have been verified in scenarios of DESs unit, DESs aggregator, and the overall operation of DPN. Compared with other conventional methods, the proposed framework increases the maximum OR of DESs by 2.48%, enhances the DR rate by approximately 5%, increases the utilization rate of renewable energy to over 97%, and effectively enhances the flexibility and economy of DPN.

可再生能源的日益融合要求配电网络（DPN）具有前所未有的灵活性，而利用分布式储能系统（DESs）固有的储能特性为提高DPN的灵活性提供了关键支持。本文提出了一个灵活的运行优化框架，将分布式电网参与需求响应（DR），旨在释放分布式电网固有的储能调节潜力。首先，开发了DESs的集成操作区域（OR）剖面模型，有效地利用了5G基站中电动汽车、储能系统和备用储能的灵活性潜力，并战略性地结合了恒温控制负载，以利用其固有的热能存储特性。其次，引入决策支持系统的聚合-分解机制来协调和调节大规模决策支持系统的灵活性，并将基于优先级的方法应用于异构决策支持系统的分解。最后，建立了参与DPN容灾的聚合分布式电网实时优化模型，利用分布式电网储能可调特性动态优化运行潮流，增强容灾能力。本文提出的DPN优化框架的有效性和优越性已在DESs单元、DESs聚合器和DPN整体运行场景中得到验证。与其他传统方法相比，该框架将DESs的最大OR提高了2.48%，DR率提高了约5%，可再生能源利用率提高到97%以上，有效提高了DPN的灵活性和经济性。

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引用次数: 0

Evaluation of reinforcement learning and model predictive control for apartment heating with heat pump and water storage tank 热泵储水箱公寓供暖强化学习与模型预测控制评价

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120509

Sami Tarvainen, Eero Hirvijoki, Timo Laukkanen

Optimising apartment heating systems is becoming increasingly crucial due to growing use of heat pumps and heat storages. This study compares reinforcement learning (RL) and model predictive control (MPC) to optimise and control a simulated apartment heating system. We explore various RL designs, including binary and continuous action spaces, different reward functions, and three storage sizes. We find that MPC outperforms RL when the optimisation period aligns with the actual problem. This is shown in the lower electricity costs of MPC compared to RL with small and base storage sizes. However, the two methods yielded similar electricity costs with the large storage size. We also find that the RL design significantly affects its performance and robustness. The RL model with binary actions and a reward function promoting the active use of storage and profit maximisation outperforms other RL configurations. In turn, a reward function representing the actual problem of cost minimisation was found to be ineffective for agent training. Future studies that compare the two methods for the optimisation of heating systems with long-term storage could focus on extending the prediction horizon or enhancing the terminal cost term in MPC.

由于越来越多地使用热泵和蓄热装置，优化公寓供暖系统变得越来越重要。本研究比较了强化学习（RL）和模型预测控制（MPC）来优化和控制模拟公寓供暖系统。我们探索了各种强化学习设计，包括二进制和连续动作空间，不同的奖励函数和三种存储大小。我们发现，当优化周期与实际问题一致时，MPC优于RL。这体现在MPC的电力成本较低，而RL具有小型和基本的存储尺寸。然而，这两种方法在存储容量大的情况下产生了相似的电力成本。我们还发现RL设计显著影响其性能和鲁棒性。具有二元行为和奖励函数的RL模型促进了存储的积极使用和利润最大化，优于其他RL配置。反过来，表示成本最小化实际问题的奖励函数被发现对代理训练无效。未来比较这两种方法优化长期储存供暖系统的研究可以集中在延长预测范围或提高MPC的终端成本期限上。

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引用次数: 0

N/S co-doped carbon with balanced micro-mesoporosity for ultra-stable supercapacitors 具有平衡微介孔的氮/硫共掺杂碳用于超稳定超级电容器

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120732

Ting Liu , Menghui Yin , Beibei Li , Salifu Nasir , Qiang Chen

The accelerating demand for sustainable, high-rate, and durable energy storage underscores the need for carbon electrodes that simultaneously offer balanced micro–mesoporosity for rapid ion transport and robust heteroatom functionalities for enhanced interfacial chemistry. In the present work, we convert bitumen asphaltenes and recycled cellulose acetate into N/S co-doped hierarchical carbons via ammonium persulfate-assisted co‑carbonization and KOH activation. The optimized carbon combines an ultrahigh specific surface area of 3527 m² g⁻¹, balanced micro–mesoporosity, and uniformly distributed electroactive N/S species (pyridinic/pyrrolic N, CS, SO_x), enhancing conductivity and pseudocapacitance. In three-electrode tests, the electrode delivered 382.5 F g⁻¹ at 0.5 A g⁻¹ with 74% retention at 10 A g⁻¹. The symmetric aqueous device achieved a specific capacitance of 288.2 F g⁻¹ at 0.5 A g⁻¹, energy densities of 10.01 Wh kg⁻¹ at 257.4 W kg⁻¹ and 5.42 Wh kg⁻¹ at 6728.3 W kg⁻¹, and 108.7% capacitance retention after 10,000 cycles at 5 A g⁻¹. This study advances sustainable energy storage by enabling low-cost, high-performance supercapacitors and promoting solid-waste recycling.

随着对可持续、高速率和耐用能量存储的需求不断增长，碳电极需要同时提供平衡的微介孔以实现快速离子传输和强大的杂原子功能以增强界面化学。在本研究中，我们通过过硫酸铵辅助共碳化和KOH活化，将沥青沥青烯和再生醋酸纤维素转化为N/S共掺杂的分级碳。优化后的碳结合了3527 m2 g−1的超高比表面积、平衡的微介孔和均匀分布的电活性N/S物质（吡啶/吡啶N、CS、SOx），增强了电导率和赝电容。在三电极测试中，电极在0.5 A g−1下传递382.5 F g−1，在10 A g−1下保持74%。该对称水溶液器件在0.5 a g−1时的比电容为288.2 F g−1，在257.4 W kg−1时的能量密度为10.01 Wh kg−1，在6728.3 W kg−1时的能量密度为5.42 Wh kg−1，在5 a g−1下循环10,000次后的电容保持率为108.7%。这项研究通过实现低成本、高性能的超级电容器和促进固体废物回收来推进可持续能源储存。

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引用次数: 0

Enhanced robustness of lithium-ion battery equivalent circuit parameter identification via logarithmic transformation and Levenberg-Marquardt algorithm 利用对数变换和Levenberg-Marquardt算法增强锂离子电池等效电路参数辨识的鲁棒性

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120724

Hehui Zhang , Ting Liu , Kang Li , Yichu Liu , Jianxin Hu , Qingsong Zuo , Liangxing Jiang

Accurate parameter identification for lithium-ion battery equivalent circuit models (ECMs) is critical for battery management systems (BMS) but challenged by initial guess sensitivity and local minima. This study proposes a robust framework integrating logarithmic parameter transformation, the Levenberg-Marquardt (LM) algorithm, and Latin Hypercube Sampling (LHS). The method employs a magnitude-scaled initial guess generation strategy across multiple orders of magnitude through systematic scaling of initial prior estimates, with a four-order-of-magnitude range (0.01× to 100×) implemented as a specific application case. In virtual 2-RC circuit tests, the LM with transformation (LM-Tran) method outperformed three comparative methods — LM without transformation (LM-Normal), Trust-Region-Reflective algorithm without transformation (TRR-Normal), and TRR with transformation (TRR-Tran) — achieving >90% optimal convergence (ExitFlag = 1), R² > 0.9995, and a median computation time of 0.086 s/optimization. And for real LFP18650 battery data across 20%–100% SOC, it yielded <10.5 mV voltage residuals (R² > 0.996). The parallel-ready framework, compatible with GPU acceleration, enables efficient and physically feasible ECM identification, supporting real-time BMS applications in electric vehicles and energy storage systems.

锂离子电池等效电路模型（ecm）参数的准确识别对电池管理系统（BMS）至关重要，但其初始猜测灵敏度和局部最小值是一个挑战。本研究提出了一个整合对数参数变换、Levenberg-Marquardt （LM）算法和拉丁超立方采样（LHS）的鲁棒框架。该方法通过对初始先验估计的系统缩放，采用了跨多个数量级的数量级初始猜测生成策略，并以具体应用实例实现了4个数量级的范围（0.01×至100×）。在虚拟2-RC电路测试中，带变换的LM （LM- tran）方法优于不带变换的LM （LM- normal）、不带变换的Trust-Region-Reflective算法（TRR- normal）和带变换的TRR （TRR- tran）三种比较方法，实现了>；90%的最优收敛（ExitFlag = 1）， R2 > 0.9995，中位计算时间为0.086 s/optimization。对于20%-100% SOC的真实LFP18650电池数据，它产生了<；10.5 mV电压残余（R2 > 0.996）。该框架兼容GPU加速，可实现高效且物理可行的ECM识别，支持电动汽车和储能系统中的实时BMS应用。

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引用次数: 0

A composite immersion cooling system integrating flow guide, bottom liquid cooling and fin shell: A study on its cooling performance 一种集导流、底部液冷和翅片壳为一体的复合浸入式冷却系统的冷却性能研究

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120696

Changkun Wu , Jimin Ni , Xiuyong Shi

In this paper, a composite immersion cooling system(ICS) coupled with flow guide, bottom liquid cooling and fin shell (GBF-ICS) is proposed to solve the problem of battery pack surface overtemperature caused by local insufficient flow under high rate discharge conditions. The results demonstrate that at a 6C discharge rate, the GBF-ICS reduces the maximum surface temperature of the battery module by 45.5% to 48.2% and the temperature difference by 69.1% to 78.9%, compared to conventional ICS. Among them, the flow guide solves the problem of flow stagnation zone between the cells. The smaller the width(Wi) of the guide hole is, the smaller the flow stagnation zone on the side shell. The smaller the length (Le) of the guide hole is, the larger the flow rate on the side shell. The bottom liquid cooling makes up for the limitation of insufficient flow distribution at the bottom of the cell. Regarding the battery side surface fins, the parallel bisected fin configuration (Si2) exhibited optimal cooling performance. The fin segmentation point promotes coolant confluence, leading to an increased local surface heat transfer coefficient. For the top surface fins, coolant primarily reduces surface temperature through heat exchange with the fins. When the system energy consumption is similar (6.88 W for ISC, 7.51 W for GBF-ICS), compared to conventional ICS, the GBF-ICS employing flow guide with Wi = 7 mm and Le = 100 mm, combined with the Si2-To1 fin arrangement, achieved reductions of 44.5% (reach 43.4 °C) in maximum temperature and 69.0% (reach 16.1 °C) in temperature difference.

为了解决高倍率放电条件下由于局部流量不足导致的电池组表面过温问题，提出了一种具有导流、底部液体冷却和翅片壳耦合的复合浸没冷却系统（GBF-ICS）。结果表明，在放电速率为6C时，与常规ICS相比，GBF-ICS可使电池组件的最大表面温度降低45.5% ~ 48.2%，温差降低69.1% ~ 78.9%。其中导流装置解决了单元间的流动滞止区问题。导孔宽度（Wi）越小，侧壳上的流动停滞区越小。导孔长度（Le）越小，侧壳的流量越大。底部液体冷却弥补了电池底部流动分配不足的局限性。对于电池侧表面翅片，平行等分翅片结构（Si2）具有最佳的冷却性能。翅片分割点促进冷却剂汇合，导致局部表面传热系数增加。对于顶部表面翅片，冷却剂主要通过与翅片的热交换来降低表面温度。在系统能耗相同（ISC为6.88 W， GBF-ICS为7.51 W）的情况下，与传统ICS相比，采用Wi = 7 mm、Le = 100 mm导流的GBF-ICS，结合Si2-To1翅片布置，最高温度降低44.5%（达到43.4°C），温差降低69.0%（达到16.1°C）。

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引用次数: 0

Multi-scale 3D printing of negative electrodes: A pathway to enhanced lithium-ion battery performance 负极的多尺度3D打印：提高锂离子电池性能的途径

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2025.120106

Dominika Gastol , Pengcheng Zhu , Yongxiu Chen , Matthew J. Capener , Emma Kendrick

This study introduces a multi-scale, multi-modal approach to the design and 3D printing of high-performance negative electrodes for lithium-ion batteries. Two types of printable inks were formulated using either alginate or carboxymethyl cellulose (CMC) as the primary binder, combined with styrene-butadiene rubber (SBR) and modified with a secondary fluid, 1-octanol. Rheological studies confirm that inks with secondary fluids exhibit higher viscosity and shear-thinning behaviour together with a yield stress of 20 Pa, compared to 14 Pa for non-modified formulations, enabling smooth extrusion and stable patterning in the direct ink writing (DIW) process.

Cryo-SEM analysis confirmed the formation of well-aligned capillary networks that significantly reduced through-plane tortuosity from 6.3 to 4.5, enhancing ionic conductivity.

Electrochemical testing revealed that 3D-printed electrodes outperformed traditional draw-down coated counterparts across multiple metrics. The dual-binder 3D-printed electrode demonstrated a 95 % discharge capacity retention at 5C, compared to 73 % for single-binder with octanol and only 19 % for alginate-based draw-down electrodes. Charge transfer resistance was reduced by over 40 % in printed structures. These results validate that ink-level and structural optimisation through a multi-scale design strategy can significantly improve battery performance, offering a viable route towards scalable, energy-dense, and high-power Li-ion technologies.

本研究引入了一种多尺度、多模态的方法来设计和3D打印高性能锂离子电池负极。以海藻酸盐或羧甲基纤维素（CMC）为主要粘结剂，与丁苯橡胶（SBR）结合，用二次流体1-辛醇进行改性，配制了两种可印刷油墨。流变学研究证实，与未改性配方的14 Pa相比，含有二次流体的油墨具有更高的粘度和剪切变薄行为，同时屈服应力为20 Pa，从而在直接油墨书写（DIW）过程中实现平滑挤压和稳定的图案。低温扫描电镜（cro - sem）分析证实，形成了排列良好的毛细管网络，将通过面扭曲度从6.3降低到4.5，提高了离子电导率。电化学测试表明，3d打印电极在多个指标上都优于传统的收缩涂层电极。双粘结剂3d打印电极在5C下的放电容量保持率为95%，而单粘结剂辛醇电极的放电容量保持率为73%，海藻酸盐电极的放电容量保持率仅为19%。在印刷结构中，电荷转移电阻降低了40%以上。这些结果验证了通过多尺度设计策略进行墨水级和结构优化可以显着提高电池性能，为可扩展，高能量密度和高功率锂离子技术提供了可行的途径。

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引用次数: 0

Optimizing CeNiO3/NiO interfaces for enhanced pseudocapacitive capabilities in energy storage system 优化CeNiO3/NiO接口，增强储能系统的伪电容性能

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120595

Areej Fatima , Asghar Nazir , Muhammad Madni , S. Shah , Abdullah K. Alanazi , G. Stevens , A.N. Ahmed

Novel supercapacitor materials are being engineered to cope with the growing need for environmentally friendly energy storage technologies worldwide. Here, a CeNiO₃/NiO composite synthesized via hydrothermal route exhibits outstanding pseudocapacitive performance, surpassing its individual components (CeNiO₃: 579.19 F/g; NiO: 289.97 F/g) by achieving 762.38 F/g at a 1 A/g current density. SEM reveals a plate-on-flake hierarchical nanostructure (0.038 μm), where NiO nanoplates uniformly anchor on CeNiO₃ nanoflakes, forming a conductive, ion-permeable network. XRD confirms well-defined crystalline phases and strong interfacial coupling between CeNiO₃ and NiO. The composite demonstrates improved conductivity characteristics, reflected by its low R_ct of 15.81 Ω, large electrochemical surface area (110 cm²), and excellent stability retaining 95.76% and 94.42% capacitance after 10,000 (three-electrode) and 5000 (two-electrode) cycles, respectively. Post-stability XRD (Fig. S5) confirms structural robustness. The two-electrode device delivers 25.50 Wh/kg energy density at 0.074 kW/kg power. The enhanced performance arises from the complementary roles of CeNiO₃ (high conductivity) and NiO (abundant redox sites), enabling efficient charge transfer, long term durability and steady ion diffusion makes composite a viable option for next-generation supercapacitors.

为了满足世界范围内对环境友好型储能技术日益增长的需求，人们正在设计新型超级电容器材料。通过水热法合成的CeNiO3/NiO复合材料表现出优异的赝电容性能，在1 a /g电流密度下达到762.38 F/g，优于其单个组分（CeNiO3: 579.19 F/g; NiO: 289.97 F/g）。扫描电镜（SEM）显示出0.038 μm的片状层状纳米结构，其中NiO纳米片均匀地锚定在CeNiO3纳米片上，形成导电的离子渗透网络。XRD证实了CeNiO3和NiO之间具有良好的晶相和强的界面耦合。该复合材料具有良好的电导率特性，其Rct低至15.81 Ω，电化学表面积大（110 cm2），稳定性好，在1万次（三电极）和5000次（两电极）循环后分别保持95.76%和94.42%的电容。稳定性后XRD（图S5）证实了结构的稳健性。该双电极装置在0.074 kW/kg功率下提供25.50 Wh/kg能量密度。增强的性能源于CeNiO3（高导电性）和NiO（丰富的氧化还原位点）的互补作用，实现高效的电荷转移，长期耐用性和稳定的离子扩散，使复合材料成为下一代超级电容器的可行选择。

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引用次数: 0

Study on the influence of guide vanes opening on internal flow characteristics and energy loss mechanisms in pump-turbine pump operating conditions 导流叶片开度对泵-涡轮泵工况内部流动特性及能量损失机理的影响研究

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120740

Junhao Zhang , Chun Xiang , Heng Qian , Hongxun Chen , Puxi Li , Sanxia Zhang , Junhao Zhou

To elucidate the influence of guide vane opening variations on the internal flow characteristics of a pump-turbine under different flow conditions and to clarify the associated energy loss mechanisms, this study examines a reversible mixed-flow pump-turbine unit from a pumped-storage power plant. Numerical simulations were performed for pump-mode operation under a range of guide vane openings (13-25 mm) and flow rates (70-140 L/s). Based on the entropy production theory, the effects of guide vane opening on the unit's external performance, internal flow field, and energy loss mechanisms were systematically analyzed. The results demonstrate that an increase in guide vane opening shifts the peak efficiency point toward higher flow rates. Smaller openings yield higher efficiency at low flow conditions, whereas larger openings promote more stable operation at high flow conditions. Entropy production analysis indicates that the major sources of energy loss are concentrated in the guide vane region, vaneless zone, and volute. Under low-flow operating conditions, a small guide vane opening leads to flow passage constriction and induces local flow separation. In the vaneless zone, pronounced recirculation and vortex structures develop, significantly altering the local velocity gradients. This results in the formation of alternating high-entropy and low-entropy regions within the vaneless area. As the guide vane opening gradually increases, vortical structures in the vaneless zone migrate into the movable guide vane passage, progressively deteriorating the internal flow conditions. This process generates a localized high-entropy region on the pressure side of the guide vanes and a corresponding low-entropy region on the suction side. Under high-flow operating conditions, a small guide vane opening causes high-velocity flow at the trailing edge of the movable guide vanes, generating vortex structures and banded high-entropy regions. With further increases in the guide vane opening, these vortical structures gradually weaken and eventually disappear, leading to a significant reduction in the unit's energy losses.

为了阐明导叶开度变化对不同流动条件下泵-水轮机内部流动特性的影响，并阐明相关的能量损失机制，本研究对抽水蓄能电厂可逆混合流泵-水轮机机组进行了研究。在导叶开口（13-25 mm）和流量（70-140 L/s）范围内进行了泵态运行的数值模拟。基于熵产理论，系统分析了导叶开度对机组外部性能、内部流场及能量损失机理的影响。结果表明，导叶开度的增加使效率峰值向更高的流量移动。较小的开孔在低流量条件下效率更高，而较大的开孔在高流量条件下运行更稳定。熵产分析表明，能量损失的主要来源集中在导叶区、无叶区和蜗壳。在低流量工况下，导叶开度小导致流道收缩，引起局部流动分离。在无叶区，明显的再环流和涡旋结构发展，显著改变了局部的速度梯度。这导致在无叶区域内形成交替的高熵和低熵区域。随着导叶开度的逐渐增大，无叶区螺旋结构向可动导叶通道内迁移，内部流动条件逐渐恶化。该过程在导叶压力侧产生局部高熵区，在吸力侧产生相应的低熵区。在大流量工况下，导叶开度小，可动导叶尾缘处产生高速流动，形成涡结构和带状高熵区。随着导叶开度的进一步增加，这些旋涡结构逐渐减弱并最终消失，导致机组能量损失显著减少。

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引用次数: 0

Structure design and performance optimization of liquid cooling plate of power battery based on machine learning and genetic algorithm 基于机器学习和遗传算法的动力电池液冷板结构设计与性能优化

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-24 DOI: 10.1016/j.est.2026.120672

Tianshi Zhang , Zheng Liu , Shichun Yang , Zhiwu Han , Linghan Xu , Wenjing Yuan , Hui Fan , Xiangnan Yu , Ning Li

The structural parameters of the liquid cooling plate (LCP) have a significant impact on the temperature control of the power battery. In this paper, the rib-column composite structure parameters are optimized by combining the CAWOA-BP neural network and NSGA-II optimization algorithm, and compared with the original structure, its Nu and thermal enhancement coefficient (TEC) are effectively improved. Firstly, the rib-column composite structure was coupled to the serpentine flow channel LCP, and the results showed that the elliptical column and staggered semicircular-rib composite structure EC-SSR had the best performance compared to other composite structures, and its TEC increased by 34.47%. Then, five structural parameters were extracted from it as variables, and Nu and the friction coefficient f were used as target functions to construct the dataset. Than the CAWOA-BP neural network was trained by a training set consisting of 155 sets of sample points, and then the optimal structural parameters were determined by an optimization algorithm and numerical simulation. The Nu of the optimum structure is increased from 2.89 to 6.32 and its TEC is increased by 51.33% compared to the initial structure, although its friction coefficient f is increased from 0.41 to 1.24. Some insights into cooling structures were provided.

液冷板的结构参数对动力电池的温度控制有重要影响。本文结合CAWOA-BP神经网络和NSGA-II优化算法对肋柱复合材料结构参数进行了优化，与原结构相比，其Nu和热增强系数（TEC）得到了有效提高。首先，将肋柱复合结构与蛇纹流道LCP耦合，结果表明，椭圆柱和交错半圆肋复合结构EC-SSR与其他复合结构相比性能最佳，其TEC提高34.47%；然后，从中提取5个结构参数作为变量，以Nu和摩擦系数f作为目标函数构建数据集。然后利用155组样本点组成的训练集对CAWOA-BP神经网络进行训练，并通过优化算法和数值模拟确定最优结构参数。与初始结构相比，优化结构的Nu由2.89提高到6.32，TEC提高了51.33%，摩擦系数f由0.41提高到1.24。对冷却结构提供了一些见解。

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引用次数: 0

Parametric optimization and charging performance enhancement of X-fin employed shell and tube solid-solid PCM based latent heat thermal energy storage system 壳管固固相变潜热储热系统的参数优化及充能性能增强

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-01-23 DOI: 10.1016/j.est.2026.120356

Niketan , Prashant Saini , Atul Dhar , Satvasheel Powar

Latent heat thermal energy storage (LHTES) has emerged as an effective solution for addressing challenges associated with large-scale and long-term energy storage. Despite recent progress in LHTES, further efficiency gains are needed. This study aims to enhance the charging performance by designing and optimizing an X-shaped fin-based shell-and-tube LHTES system using nanoparticle-encapsulated solid-solid phase change material (SS-PCM). The charging behavior of the SS-PCM is examined numerically using a 2D model. This study investigates the impact of the number of fins, structure of fins, the type and volume fraction of nanoparticles, prescribed inner wall temperature, and fin material on the charging behavior of SS-PCM. The findings illustrate that the LHTES system with an increased number of X-fins (Type-5) and improved design using branches (hands) on X-fins configurations (Type-6) results in enhanced heat transfer rate and more uniform temperature distribution. In this study, the impact of three different types of nanoparticles (Cu, Al₂O₃, and Graphene) and five different fin materials (Copper, Aluminum, Nickel, Carbon Steel, and Graphite) on charging performance is examined by employing the modified enthalpy-porosity technique. The LHTES system with X- fins with branches (Type 6) is the optimal design, which efficiently improves the charging performance. Copper is the recommended fin material, as it increases the charging performance by approximately 10.81% compared to carbon steel. The charging time decreases by 96.65% when the prescribed wall temperature is increased from 498 K to 544 K, indicating that even a modest rise in prescribed inner wall temperature (9.23%) can have a substantial impact on system performance. Furthermore, a significant improvement in charging performance is observed on encapsulation of SS-PCM with 4% volume fraction of graphene nanoparticles.

潜热储能（LHTES）已成为解决大规模和长期储能挑战的有效解决方案。尽管最近在LHTES方面取得了进展，但还需要进一步提高效率。本研究旨在通过设计和优化一种基于x形鳍片的壳管式纳米颗粒包封固-固相变材料（SS-PCM）的LHTES系统来提高充电性能。利用二维模型对SS-PCM的充电行为进行了数值研究。研究了翅片数量、翅片结构、纳米颗粒类型和体积分数、规定的内壁温度以及翅片材料对SS-PCM充电行为的影响。研究结果表明，增加x鳍（5型）数量和改进设计在x鳍配置（6型）上使用分支（手）的LHTES系统可以提高传热速率和更均匀的温度分布。在本研究中，采用改进的焓孔技术，研究了三种不同类型的纳米颗粒（Cu、Al2O3和石墨烯）和五种不同的翅片材料（铜、铝、镍、碳钢和石墨）对充电性能的影响。6型X鳍带分支的LHTES系统是最优设计，有效地提高了充电性能。铜是推荐的翅片材料，因为与碳钢相比，它的充电性能提高了约10.81%。当规定的内壁温度从498 K增加到544 K时，充电时间减少了96.65%，这表明即使规定的内壁温度适度升高（9.23%），也会对系统性能产生实质性的影响。此外，采用体积分数为4%的石墨烯纳米颗粒包封SS-PCM后，其充电性能得到了显著改善。

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