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Innovative Energy Storage Solutions for Electric Vehicle Fleets: Challenges and Future Directions in Italy 电动汽车车队的创新储能解决方案:意大利的挑战和未来方向
Pub Date : 2025-11-11 DOI: 10.1002/est2.70290
Hamid Safarzadeh, Francesco Di Maria

The rapid growth of electric vehicle (EV) fleets in Italy is intensifying pressure on the national grid and raising concerns about infrastructure readiness, economic feasibility, and regulatory fragmentation. Energy storage systems (ESS) are central to addressing these challenges, yet their role in fleet electrification remains underexplored in the Italian context. This study investigates the technological, economic, and policy dimensions of energy storage innovations that can support Italy's transition toward sustainable fleet electrification in alignment with EU climate goals. A mixed-methods approach was employed, combining policy and regulatory analysis, 18 expert interviews with fleet operators, energy providers, and policymakers, and a Python-based simulation of EV fleet charging to evaluate technical performance, economic viability, and future deployment scenarios validated by a Delphi panel of 10 experts. The findings reveal that high upfront costs, limited charging infrastructure, and regional policy disparities are the primary barriers to ESS adoption. Simulation results indicate that lithium-ion batteries can reliably meet daily fleet energy demand but are constrained by degradation and grid strain under concentrated charging schedules. Scenario analysis shows that under optimistic conditions, including rapid technology development and expanded infrastructure, fleet-related emissions could be reduced by up to 40% by 2030. Overall, the study underscores that energy storage is a cornerstone of Italy's EV fleet transition and highlights the need for coordinated policy alignment, investment in advanced storage technologies, and expansion of vehicle-to-grid (V2G) services to unlock economic and environmental benefits while positioning Italy as a leader in sustainable mobility.

意大利电动汽车(EV)车队的快速增长正在加大对国家电网的压力,并引发了对基础设施准备情况、经济可行性和监管分散的担忧。储能系统(ESS)是解决这些挑战的核心,但在意大利,其在车队电气化中的作用仍未得到充分探索。本研究调查了储能创新的技术、经济和政策层面,这些创新可以支持意大利向符合欧盟气候目标的可持续车队电气化过渡。采用混合方法,结合政策和监管分析,18位专家与车队运营商、能源供应商和政策制定者进行访谈,以及基于python的电动汽车车队充电模拟,以评估技术性能、经济可行性和未来部署方案,并由10位专家组成的德尔福小组验证。研究结果显示,高昂的前期成本、有限的充电基础设施和地区政策差异是采用ESS的主要障碍。仿真结果表明,在集中充电模式下,锂离子电池能够可靠地满足车队的日常能源需求,但受到退化和电网应变的限制。情景分析表明,在乐观的情况下,包括技术的快速发展和基础设施的扩大,到2030年,与车队相关的排放量可以减少多达40%。总体而言,该研究强调,储能是意大利电动汽车车队转型的基石,并强调需要协调政策调整,投资先进的储能技术,扩大车辆到电网(V2G)服务,以释放经济和环境效益,同时将意大利定位为可持续移动出行的领导者。
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引用次数: 0
Adaptive Power Distribution and Range Enhancement in Electric Vehicles Using Hybrid Energy Storage System 基于混合动力储能系统的电动汽车自适应功率分配与续航里程增强
Pub Date : 2025-11-11 DOI: 10.1002/est2.70292
Sachin Chavan, Saket Yeolekar, Netra Lokhande

The automotive industry's transition to green mobility has increased the focus on electric vehicles (EVs) due to their low emissions and reduced reliance on conventional carbon-based fuels. To support wider EV adoption, enhancing the efficiency and performance of their energy storage systems—particularly, by increasing power and energy density—is essential. Although various advanced energy storage systems (ESSs) are available, batteries remain the most viable option for meeting the average power demands of EVs. However, challenges such as excessive heat generation, limited power density, and reduced operational lifespan hinder optimal performance when relying solely on batteries. A hybrid energy storage system (HESS) presents a promising solution by enabling more efficient power management. Key functions of HESSs include supporting vehicle acceleration, capturing energy during regenerative braking, and reducing stress on the battery. By integrating a battery with a supercapacitor (SC), HESSs can meet instantaneous power demands and facilitate energy recovery during deceleration. This study evaluates the performance of a standalone battery and an HESS by using MATLAB–Simulink simulations. The results show that the SC absorbs most peak current loads over short durations, while the battery supplies the average current. The HESS reduces average battery current demand and extends vehicle range by 38%. Additionally, hybridization allows for a reduction in battery power capacity, resulting in a 33 kg weight decrease. These findings demonstrate the potential of HESS to enhance EV performance, promote energy efficiency, and support the broader adoption of sustainable transportation.

由于电动汽车的低排放和减少对传统碳基燃料的依赖,汽车行业向绿色交通的转型增加了人们对电动汽车(ev)的关注。为了支持更广泛的电动汽车采用,提高其储能系统的效率和性能——特别是通过提高功率和能量密度——是必不可少的。尽管有各种先进的储能系统(ess)可供选择,但电池仍然是满足电动汽车平均电力需求的最可行选择。然而,当完全依赖电池时,诸如产生过多热量、有限的功率密度和缩短的使用寿命等挑战阻碍了最佳性能。混合储能系统(HESS)通过实现更有效的电源管理,提供了一个有前途的解决方案。hess的主要功能包括支持车辆加速,在再生制动过程中捕获能量,以及减少对电池的压力。通过将电池与超级电容器(SC)集成在一起,hess可以满足瞬时功率需求,并促进减速过程中的能量回收。本研究通过使用MATLAB-Simulink仿真来评估独立电池和HESS的性能。结果表明,SC在短时间内吸收了大部分峰值电流负载,而电池提供了平均电流。HESS降低了平均电池电流需求,并将车辆续航里程延长了38%。此外,杂交允许减少电池的电力容量,导致33公斤的重量减少。这些发现证明了HESS在提高电动汽车性能、提高能源效率和支持更广泛采用可持续交通方面的潜力。
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引用次数: 0
Accurate Real-Time Internal Temperature Estimation of Lithium-Ion Batteries With an Aquila-Optimized Adaptive Strong Tracking Extended Kalman Filter 基于aquila优化自适应强跟踪扩展卡尔曼滤波的锂离子电池内部温度实时精确估计
Pub Date : 2025-11-06 DOI: 10.1002/est2.70289
Qiping Chen, Zhikun Xu, Xiaowei Huang, Qingfeng Hu, Zhiqiang Jiang, Changjiang Liao

To address the challenge of directly and accurately measuring the internal temperature of lithium-ion power batteries in electric vehicles, this paper proposes an online precise estimation method for battery internal temperature based on the Aquila Optimizer-optimized Adaptive Strong Tracking Extended Kalman Filter (AO-ASTEKF). Building on a battery equivalent thermal model with parameters identified using the Genetic Algorithm (GA), the Aquila Optimizer (AO) is employed to optimize the initial noise covariance settings of the traditional Extended Kalman Filter (EKF), thereby mitigating the impact of improper initialization. To resolve the estimation deviation caused by fixed noise covariance in EKF, the Sage-Husa adaptive filtering technique is introduced to enable adaptive adjustment of noise covariance values. Furthermore, to counteract the estimation accuracy degradation of the filter due to sudden temperature changes in high-temperature environments, the Strong Tracking (ST) filter is incorporated to enhance the tracking capability of the EKF. Through co-simulation in AMESim and MATLAB/Simulink, the accuracy of the proposed AO-ASTEKF algorithm in estimating battery internal temperature is validated under different ambient temperatures and operating conditions. Experimental results demonstrate that the AO-ASTEKF algorithm improves estimation accuracy by at least 58.46% compared to both the traditional EKF and the Strong Tracking Extended Kalman Filter (STEKF). This method effectively overcomes the limitations of conventional algorithms in accurately estimating battery internal temperature, holding significant importance for ensuring battery safety and enhancing battery performance.

为解决电动汽车锂离子动力电池内部温度直接准确测量的难题,提出了一种基于Aquila优化器优化的自适应强跟踪扩展卡尔曼滤波(AO-ASTEKF)的电池内部温度在线精确估计方法。在利用遗传算法(GA)确定参数的电池等效热模型的基础上,利用Aquila Optimizer (AO)优化传统扩展卡尔曼滤波器(EKF)的初始噪声协方差设置,从而减轻初始化不当的影响。为了解决EKF中噪声协方差固定造成的估计偏差,引入Sage-Husa自适应滤波技术,实现噪声协方差值的自适应调整。此外,为了抵消高温环境下由于温度突然变化导致的滤波器估计精度下降,引入了强跟踪(ST)滤波器来增强EKF的跟踪能力。通过AMESim和MATLAB/Simulink联合仿真,验证了AO-ASTEKF算法在不同环境温度和工况下估算电池内部温度的准确性。实验结果表明,与传统EKF和强跟踪扩展卡尔曼滤波(STEKF)相比,AO-ASTEKF算法的估计精度至少提高了58.46%。该方法有效克服了传统算法在准确估计电池内部温度方面的局限性,对保证电池安全、提高电池性能具有重要意义。
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引用次数: 0
Thermal Performance Enhancement of an Annular Thermal Energy Storage System With Rotating Walls 具有旋转壁面的环形储热系统的热性能增强
Pub Date : 2025-11-04 DOI: 10.1002/est2.70288
Saber Abdollahzadeh Bonab, Sajjad Ahangar Zonouzi

This study numerically investigates the thermal performance enhancement of a PCM-filled annular thermal energy storage (TES) system using rotational walls, considering both the solidification and melting processes. Various rotational configurations are explored. These configurations are separate rotation of the inner and outer walls, simultaneous rotation of both walls with different angular velocities, and rotations in both clockwise (CW) and counterclockwise (CCW) directions. The results show that the rotation of the walls induces forced convection which enhances heat transfer and accelerates PCM melting. The molten layers in proximity to the rotating walls show increased velocity causing improved flow effects. Higher rotational speeds result in stronger fluid flow and enhanced convection within the PCM enclosure, resulting in a larger volumetric fraction of PCM undergoing the melting process. Furthermore, the rotation of the walls promotes a more uniform distribution of heat and a homogeneous distribution of the molten PCM throughout the system. Simultaneously rotating both the inner and outer walls of the PCM enclosure reduces the total melting time which increases the overall efficiency of the TES system. Regarding the solidification process, the rotation of the PCM enclosure walls accelerates the typically slow solidification stage. Increasing the angular velocities causes a higher solidification rate because of enhanced mixing within the system. At the highest angular velocity, rotating the outer wall alone, reduces melting time by 49.06%, while rotating both walls (inner CW–outer CCW) leads to a maximum reduction of 62.15%. In solidification, outer wall rotation decreases the total solidification time by 55.91%, and rotating both walls (CW–CW) achieves up to 56.53% reduction. Overall, the findings of this study show the significant thermal performance enhancement achieved through the rotation of walls in PCM-filled annular TES systems.

本研究在考虑凝固和熔化过程的情况下,数值研究了使用旋转壁填充pcm的环形热储能(TES)系统的热性能增强。探讨了各种旋转构型。这些构型包括内外壁分别旋转、两壁同时以不同角速度旋转、顺时针和逆时针方向旋转。结果表明,壁面的旋转引起强制对流,强化了传热,加速了PCM的熔化。靠近旋转壁面的熔融层速度增加,从而改善了流动效果。更高的转速会导致更强的流体流动和PCM外壳内的对流增强,从而导致更大的PCM体积分数正在熔化过程中。此外,壁的旋转促进了热量的更均匀分布和熔融PCM在整个系统中的均匀分布。同时旋转PCM外壳的内外壁可以减少总熔化时间,从而提高TES系统的整体效率。在凝固过程中,PCM外壳的旋转加速了典型的缓慢凝固阶段。增加角速度可以提高凝固速率,因为系统内的混合增强了。在最高角速度下,仅旋转外壁可使熔化时间缩短49.06%,而同时旋转两壁(内钨-外钨)可使熔化时间缩短62.15%。在凝固过程中,外壁旋转可使总凝固时间缩短55.91%,双壁旋转(CW-CW)可使凝固时间缩短56.53%。总的来说,这项研究的结果表明,在pcm填充的环空TES系统中,通过壁面旋转可以显著提高热性能。
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引用次数: 0
Comparative Computational Study of Semi-Metallic Zintl Hydrides for Hydrogen Storage Applications 半金属锌氢化物储氢应用的比较计算研究
Pub Date : 2025-10-30 DOI: 10.1002/est2.70286
H. Ammi, Z. Charifi, T. Ghellab, T. Saadi, L. Bouhdjer, S. Addala, H. Baaziz

Efficient, safe, and compact solid-state materials are critical for overcoming hydrogen storage challenges. This study introduces a novel class of materials, the hexagonal Zintl-phase hydrides SnMSiH (M = Al, Ga), and establishes their exceptional potential through first-principles density functional theory (DFT) calculations. The key superiority of these materials lies in their unique semimetallic electronic structure, which significantly enhances hydrogen interactions by reducing the activation energy for desorption, enabling efficient and reversible cycling—a critical improvement over insulating or wide-bandgap hydrides. Structurally, the primitive hexagonal framework (space group P3m1) provides optimal diffusion pathways for hydrogen. We report a high gravimetric capacity of 0.58 wt% for SnAlSiH with a near-ambient desorption temperature of 310.69 K, markedly superior to many complex hydrides. SnGaSiH offers a capacity of 0.47 wt% at an even lower desorption temperature of 254.15 K, indicating easy hydrogen release. Thermodynamically, both compounds exhibit significant thermal expansion and high heat capacities, ensuring resilience at operating temperatures. Mechanically, they are highly anisotropic; SnAlSiH's higher compressibility may facilitate volume changes during cycling, while SnGaSiH demonstrates superior mechanical stability (higher elastic constants). This combination of favorable desorption thermodynamics, intrinsic structural stability, and robust mechanical properties distinguishes SnMSiH hydrides as premier candidates for application. This work provides a foundational strategy for further performance enhancement through alloying and defect engineering.

高效、安全、紧凑的固态材料是克服储氢挑战的关键。本研究引入了一类新型材料,六方锌相氢化物SnMSiH (M = Al, Ga),并通过第一性原理密度泛函理论(DFT)计算建立了它们的特殊潜力。这些材料的关键优势在于其独特的半金属电子结构,通过降低解吸活化能显着增强了氢的相互作用,实现了高效和可逆的循环-这是对绝缘或宽带隙氢化物的关键改进。在结构上,原始六边形框架(空间群P3m1)为氢提供了最佳的扩散途径。我们报告了SnAlSiH的高重量容量为0.58 wt%,近环境解吸温度为310.69 K,明显优于许多复杂的氢化物。SnGaSiH在更低的解吸温度(254.15 K)下提供0.47 wt%的容量,表明氢容易释放。热力学上,这两种化合物都表现出显著的热膨胀和高热容,确保了在工作温度下的弹性。机械上,它们是高度各向异性的;SnAlSiH较高的可压缩性可能有助于循环过程中的体积变化,而SnGaSiH具有优越的机械稳定性(更高的弹性常数)。这种良好的解吸热力学、固有的结构稳定性和强大的机械性能的结合使SnMSiH氢化物成为应用的首选候选者。这项工作为通过合金化和缺陷工程进一步提高性能提供了基础策略。
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引用次数: 0
Synergistic Integration of Vanadium Dioxide, Palladium, and Silver Into Graphitic Carbon Nitride for Boosted Supercapacitor Performance 二氧化钒、钯和银协同整合到石墨碳氮中以提升超级电容器性能
Pub Date : 2025-10-30 DOI: 10.1002/est2.70285
Monika Dhanda

The increasing need for effective and sustainable energy storage solutions has spurred the advancement of sophisticated electrode materials for high-performance supercapacitors. This research tackles the fundamental limitations of graphitic carbon nitride (g-C3N4 or GCN) specifically its low conductivity and restricted capacitance by engineering VO2/GCN, Pd/GCN, and Ag/GCN nanocomposites. This research builds on our earlier published studies regarding VO2/GCN, Pd/GCN, and Ag/GCN composites, which were synthesized through hydrothermal and calcination techniques. Comprehensive structural, chemical, and morphological analyses not only validated successful synthesis but also highlighted critical features that contribute to improved electrochemical performance. X-ray diffraction (XRD) confirmed phase purity and the preservation of the GCN lattice, while FT-IR and Raman spectroscopy demonstrated strong electronic interactions between dopants and GCN, facilitating charge transfer. BET analysis indicated mesoporous structures with a high surface area and optimized pore distribution, which directly enhances ion accessibility. FESEM and TEM illustrated well-dispersed VO2, Pd, and Ag nanoparticles on GCN nanosheets, creating interconnected conductive networks that promote rapid electron transport. Elemental mapping verified uniform dopant distribution, ensuring compositional stability during cycling. Collectively, these characterizations elucidate the exceptional electrochemical response, as evidenced by cyclic voltammetry (CV), galvanostatic charge–discharge (GCD), and electrochemical impedance spectroscopy (EIS) measurements. VO2/GCN (3VO/GN) achieved the highest specific capacitance (1416 F/g), the lowest charge-transfer resistance (0.75 Ω), and the maximum double-layer capacitance (4.2 mF), surpassing Pd/GCN (401.1 F/g) and Ag/GCN (195.3 F/g). These findings emphasize the importance of strategic doping methods in optimizing the structural, morphological, and electronic characteristics of GCN to enhance charge storage, positioning VO2/GCN as a prominent candidate for scalable, next-generation supercapacitor technologies.

对有效和可持续的能量存储解决方案的日益增长的需求刺激了高性能超级电容器的复杂电极材料的进步。本研究通过工程VO2/GCN、Pd/GCN和Ag/GCN纳米复合材料解决了石墨氮化碳(g-C3N4或GCN)的基本局限性,特别是其低电导率和限制电容。本研究建立在我们之前发表的关于VO2/GCN、Pd/GCN和Ag/GCN复合材料的研究基础上,这些复合材料是通过水热和煅烧技术合成的。全面的结构、化学和形态分析不仅验证了成功的合成,而且突出了有助于提高电化学性能的关键特征。x射线衍射(XRD)证实了相纯度和GCN晶格的保存,而FT-IR和拉曼光谱证实了掺杂剂与GCN之间强烈的电子相互作用,促进了电荷转移。BET分析表明,介孔结构具有较高的比表面积和优化的孔分布,直接提高了离子的可及性。FESEM和TEM显示了GCN纳米片上分散良好的VO2、Pd和Ag纳米颗粒,形成了相互连接的导电网络,促进了电子的快速传递。元素映射验证了均匀的掺杂分布,确保循环过程中的成分稳定性。总的来说,这些特征阐明了特殊的电化学响应,如循环伏安法(CV)、恒流充放电法(GCD)和电化学阻抗谱法(EIS)测量所证明的那样。VO2/GCN (3VO/GN)的比电容最高(1416 F/g),电荷转移电阻最低(0.75 Ω),双层电容最大(4.2 mF),超过了Pd/GCN (401.1 F/g)和Ag/GCN (195.3 F/g)。这些发现强调了战略性掺杂方法在优化GCN的结构、形态和电子特性以增强电荷存储方面的重要性,将VO2/GCN定位为可扩展的下一代超级电容器技术的重要候选材料。
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引用次数: 0
Fuzzy Logic-Based Power Management Strategy for Bidirectional Solar-Integrated EV Charging 基于模糊逻辑的电动汽车双向太阳能集成充电电源管理策略
Pub Date : 2025-10-29 DOI: 10.1002/est2.70284
Manjiri Mayuresh Tamhankar, Ramchandra Pandurang Hasabe

The rising concern over environmental pollution has accelerated the adoption of electric vehicles worldwide. However, the increased demand for electric vehicle charging places an additional burden on the power grid, which primarily relies on limited fossil fuel resources. The adoption of solar-assisted EV charging has the potential to reduce fossil fuel dependence, lower greenhouse gas emissions, and promote sustainable urban mobility, yielding significant societal and environmental benefits. This paper presents a Fuzzy Logic Control (FLC)-based Power Management Controller (PMC) for a single-phase grid-connected electric vehicle (EV) charging station powered primarily by solar PV and supported by a Battery Energy Storage System (BESS). The proposed system is capable of operating in both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes. The study models various components, including PV arrays, storage batteries, and grid interconnections. The effectiveness of the proposed controller is demonstrated through MATLAB/Simulink simulations across various operational scenarios, highlighting its capability to maintain DC link voltage stability and minimize reliance on the grid. The control strategy is benchmarked against conventional PID and Artificial Neural Network (ANN) controllers. Results show that the proposed controller eliminates voltage overshoot from 9.6% to 0%, reduces settling time from 1.18 to 0.41 s, and shortens rise time from 0.27 to 0.24 s, thereby confirming enhanced voltage regulation and improved transient response. This study is based on simulation analysis, which can be extended through experimental validation for broader applicability.

对环境污染的日益关注加速了全球对电动汽车的采用。然而,电动汽车充电需求的增加给主要依赖有限的化石燃料资源的电网带来了额外的负担。采用太阳能辅助电动汽车充电有可能减少对化石燃料的依赖,降低温室气体排放,促进可持续的城市交通,产生显著的社会和环境效益。提出了一种基于模糊逻辑控制(FLC)的单相并网电动汽车(EV)充电站电源管理控制器(PMC),该充电站主要由太阳能光伏供电,并由电池储能系统(BESS)支持。该系统能够在电网到车辆(G2V)和车辆到电网(V2G)模式下运行。该研究模拟了各种组件,包括光伏阵列、蓄电池和电网互连。通过MATLAB/Simulink在各种操作场景中的仿真证明了所提出控制器的有效性,突出了其保持直流链路电压稳定性和最大限度地减少对电网依赖的能力。该控制策略与传统PID和人工神经网络(ANN)控制器进行了基准测试。结果表明,该控制器将电压超调从9.6%消除到0%,将稳定时间从1.18 s降低到0.41 s,将上升时间从0.27 s缩短到0.24 s,从而增强了电压调节能力,改善了瞬态响应。本研究基于仿真分析,可通过实验验证进行扩展,具有更广泛的适用性。
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引用次数: 0
Design Optimization of Fin Angles for Enhanced Cooling and Efficiency in Solar Panels Using Phase Change Materials 相变材料太阳能板翅片角度优化设计提高散热效率
Pub Date : 2025-10-29 DOI: 10.1002/est2.70281
Youness Bannour, Yassine El Alami, Rehena Nasrin, Adnan Ibrahim, Elhadi Baghaz, Ahmed Faize

The current work investigates approaches to augment photovoltaic (PV) panels through phase change material (PCM) systems' efficiency, with the addition of aluminum fins and varying angles of inclination. A two-dimensional numerical simulation using the enthalpy–porosity method was conducted in ANSYS Fluent for modeling PCM melting behavior. This research studied five cases of PCMs (for the same fin area and size) at five angles of inclination (30°, 60°, 90°, 120°, and 150°). The results show good agreement with literature values. PV tilt angle's influence on heat dissipation for conduction and natural convection ratio in PCM is significant. Case 3 configuration (90° inclination) exhibits the best performance of all configurations: lowest PV temperature (318.2 K), highest electrical efficiency (11.83%), maximum thermal efficiency (46.7%), maximum melting fraction transport (0.47), and maximum overall efficiency (58.61%). Case 3 exhibits a temperature improvement of 3.36 K in comparison to the worst-performing setup at 150° (Case 5) values with increases of 1.72% in electrical efficiency, 23.2% in thermal efficiency, 34.3% in melting fraction, and an 18.8% improvement in overall efficiency. Past studies have looked at the geometry of the fins, while this current study looks at the orientation of the fins. The study confirms that the 90° fin angle (which is least obstructive to vertical thermal transfer) is ideal to optimize the PV-PCM systems' efficiency under the current boundary conditions.

目前的工作是研究通过相变材料(PCM)系统的效率来增加光伏板的方法,增加铝鳍和不同的倾斜角度。在ANSYS Fluent中采用焓孔法对PCM熔化行为进行了二维数值模拟。本研究以5个倾斜角度(30°,60°,90°,120°和150°)的PCMs病例(鳍面积和尺寸相同)为研究对象。结果与文献值吻合较好。PV倾角对PCM的传导散热和自然对流比影响显著。案例3(90°倾角)在所有配置中表现最佳:最低PV温度(318.2 K),最高电效率(11.83%),最大热效率(46.7%),最大熔融分数输运(0.47)和最大总效率(58.61%)。与最差的150°(案例5)温度相比,案例3的温度提高了3.36 K,电效率提高了1.72%,热效率提高了23.2%,熔化分数提高了34.3%,总效率提高了18.8%。过去的研究关注的是鳍的几何形状,而目前的研究关注的是鳍的方向。研究证实,在当前的边界条件下,90°翅片角(对垂直传热的阻碍最小)是优化PV-PCM系统效率的理想选择。
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引用次数: 0
Slags as Thermal Energy Storage Media for Concentrated Solar Power and Renewable Energy Integration 炉渣作为聚光太阳能和可再生能源集成的蓄热介质
Pub Date : 2025-10-28 DOI: 10.1002/est2.70274
Michael Enemuo, Ngozi Enemuo, Arash Dahi Taleghani, Olumide Ogunmodimu

The growing demand for low-cost, high-performance thermal energy storage (TES) materials has prompted interest in repurposing metallurgical slags in concentrated solar power (CSP) systems. This review critically evaluates the potential of various steel, copper, and aluminum slags as high-temperature TES media in packed-bed configurations. Emphasis is placed on the thermophysical properties of steel slags, for example, with reported thermal conductivities ranging from 1.6 to 1.9 W/m K and specific heat capacities of up to 1.5 J/g K, making them competitive with conventional materials, such as molten salts. The review also explores numerical modeling approaches such as the Schumann model, local thermal non-equilibrium (LTNE), and continuous solid-phase frameworks to capture heat transfer behavior in slag-based TES systems. Additionally, system-level integration strategies, particularly direct and indirect packed-bed designs, are compared to conventional two-tank molten salt systems in terms of performance, cost, and environmental benefits. Notably, steel slags offer thermal stability above 1000°C, economic savings of up to 40% over commercial fillers, and significant CO2 reductions through circular material reuse. Case studies and simulations validate slag's long-term performance and scalability in CSP and industrial waste heat recovery applications. The review identifies research gaps in slag characterization, compatibility with heat transfer fluids, and modeling fidelity. This work contributes a comprehensive roadmap for advancing slag-based TES technologies, providing insights for research in designing next-generation, cost-effective CSP systems.

对低成本、高性能热储能(TES)材料的需求不断增长,促使人们对在聚光太阳能(CSP)系统中重新利用冶金渣产生了兴趣。这篇综述批判性地评估了各种钢、铜和铝渣在填充床配置中作为高温TES介质的潜力。重点放在钢渣的热物理性质上,例如,据报道,钢渣的导热系数在1.6至1.9 W/m K之间,比热容高达1.5 J/g K,使其与传统材料(如熔盐)竞争。本文还探讨了数值模拟方法,如Schumann模型、局部热不平衡(LTNE)和连续固相框架,以捕捉基于炉渣的TES系统的传热行为。此外,系统级集成策略,特别是直接和间接填充床设计,在性能、成本和环境效益方面与传统的双罐熔盐系统进行了比较。值得注意的是,钢渣具有1000°C以上的热稳定性,比商业填料节省高达40%的经济效益,并通过循环材料再利用显著减少二氧化碳排放。案例研究和模拟验证了炉渣在CSP和工业废热回收应用中的长期性能和可扩展性。该综述确定了在炉渣表征、与传热流体的相容性和建模保真度方面的研究空白。这项工作为推进基于炉渣的TES技术提供了一个全面的路线图,为设计下一代具有成本效益的CSP系统的研究提供了见解。
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引用次数: 0
A Novel Approach for Enhancing OCV Estimation Accuracy in EV Lithium-Ion Battery Cell Employing Adaptive Segmentation With Polynomial Fitting 基于多项式拟合的自适应分割提高电动汽车锂离子电池OCV估计精度的新方法
Pub Date : 2025-10-28 DOI: 10.1002/est2.70282
Leelakumar Murugesan, Senthilkumar Subramaniam, Pravin Murugesan

In the domain of electric vehicles (EVs) and portable electronics, lithium-ion batteries constitute a vital power source, necessitating precise state estimation within Battery Management Systems (BMS) to determine the State of Charge (SOC), State of Health (SOH), and terminal voltage. Electrical equivalent circuit models (ECMs) calibrated using temperature-dependent Open Circuit Voltage (OCV) profiles and dynamic experimental data are extensively utilized to characterize the nonlinear electrochemical dynamics of the cell. Consequently, a simple and accurate method of OCV estimation is required for real-time implementation in the BMS. Hence, this study introduces an adaptive segmentation approach employing a piecewise linearization method with first-order polynomial fitting for static OCV estimation, thereby facilitating improved segmentation points of the OCV–SOC curve and enhancing estimation accuracy. The OCV estimation accuracy across various operating temperatures is evaluated by comparing it with existing methodologies and examining its impact on dynamic terminal voltage. The Root Mean Square Error (RMSE) value of the proposed method was compared with other methods, including data-driven methods, model-based, high-order polynomials, and Gaussian regression, irrespective of operating temperature. Experimental validation of the proposed methodology was performed using MATLAB Simulation. The performance of the approach was assessed by RMSE and R2 estimation metrics, demonstrating an improvement in the OCV-SOC error across all temperature ranges compared with other well-established methods. Furthermore, the RMSE value of the terminal voltage and behaviors of model parameters using this method are comparable to those of the existing model-based approach.

在电动汽车(ev)和便携式电子产品领域,锂离子电池是至关重要的电源,需要在电池管理系统(BMS)中进行精确的状态估计,以确定充电状态(SOC)、健康状态(SOH)和终端电压。利用温度相关的开路电压(OCV)曲线和动态实验数据校准的等效电路模型(ecm)被广泛用于表征电池的非线性电化学动力学。因此,为了在BMS中实时实现,需要一种简单准确的OCV估计方法。因此,本研究提出了一种采用分段线性化方法和一阶多项式拟合的自适应分割方法用于静态OCV估计,从而改进了OCV - soc曲线的分割点,提高了估计精度。通过与现有方法的比较,并考察其对动态端电压的影响,评估了不同工作温度下OCV估计的准确性。在不考虑工作温度的情况下,将该方法的均方根误差(RMSE)值与数据驱动方法、基于模型的方法、高阶多项式方法和高斯回归方法进行了比较。利用MATLAB仿真对所提出的方法进行了实验验证。通过RMSE和R2估计指标评估了该方法的性能,与其他成熟的方法相比,该方法在所有温度范围内的OCV-SOC误差都有所改善。此外,该方法的终端电压和模型参数行为的RMSE值与现有的基于模型的方法相当。
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引用次数: 0
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Energy Storage
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