Energy Storage最新文献

{"title":"Conjugate Heat and Mass Transfer in Activated-Carbon Hydrogen Storage Reactors With Liquid and Gaseous Heat-Transfer Fluids: A Numerical Study","authors":"Zoubida Haddad,&nbsp;Atef Chibani,&nbsp;Farhan Lafta Rashid,&nbsp;Moustafa Boukraa,&nbsp;Tawfiq Chekifi","doi":"10.1002/est2.70504","DOIUrl":"https://doi.org/10.1002/est2.70504","url":null,"abstract":"<div>\u0000 \u0000 <p>Hydrogen adsorption in activated-carbon beds is a promising option for near-ambient hydrogen storage, but its performance is strongly limited by heat release during charging and heat demand during discharging. This study numerically analyzes hydrogen adsorption and desorption in a vertical steel vessel packed with activated carbon and surrounded by an external heat transfer fluid (HTF) jacket. A transient conjugate numerical model is developed to solve the coupled mass, momentum, and energy balances in the porous bed, steel wall, and HTF domains. Hydrogen adsorption is described using the Dubinin–Astakhov isotherm and linear driving force kinetics. Four HTFs, namely water, thermal oil, air, and helium, are examined during adsorption under identical reactor geometry and imposed inlet conditions, while nitrogen is used instead of water during desorption to avoid possible freezing under low-temperature operation. This replacement is treated as a practical operating choice rather than as an assumption of equivalence between water and nitrogen. The results show that HTF selection strongly affects hot-spot formation, cooling and heating rates, wall heat flux, and usable storage capacity. At <i>t</i> = 400 s, water gives the lowest peak bed temperature, 376.5 K, and the highest hydrogen uptake, 22.5 mmol g⁻¹, whereas air gives the lowest uptake, 19.0 mmol g⁻¹, and air and helium produce higher peak temperatures of about 395–397 K. Compared with the air-cooled baseline, water increases the usable hydrogen uptake by 18.4%, while oil provides a 10.5% improvement. During desorption at <i>t</i> = 4400 s, oil supplies heat more effectively from the jacket to the bed, whereas gaseous HTFs promote stronger cold-core formation because of their limited sensible heat capacity. In general, liquid HTFs provide stronger thermal management than gaseous HTFs, reducing adsorption hot spots and improving hydrogen uptake. The findings provide quantitative guidance for HTF selection and external jacket design in activated-carbon hydrogen storage reactors operating near ambient conditions.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148849211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Storage Management and Techno-Economic Analysis of Standalone Hybrid Renewable Energy Systems Using Deep Reinforcement Learning","authors":"Santosh S. Raghuwanshi,&nbsp;Khaliq Ahmed,&nbsp;Shrunkhala S. Halve,&nbsp;Prashant Raghuwanshi,&nbsp;Manoj Gupta,&nbsp;Hemant Mehar,&nbsp;Kamlesh Gupta","doi":"10.1002/est2.70505","DOIUrl":"https://doi.org/10.1002/est2.70505","url":null,"abstract":"<div>\u0000 \u0000 <p>The paper presents optimal microgrid (MGs) configurations using artificial intelligence to minimize net present cost (NPC), cost of energy (COE), and optimal utilization of energy storage. It employs methodologies such as deep reinforcement learning (DRL), spoonbill swarm optimisation algorithm (SSOA), genetic algorithm (GA), and artificial neural networks (ANN) for a techno-economic-environmental-storage analysis. The study looks at different parts of MGs, such as photovoltaic (PV) systems, wind turbine generators (WTGs), biomass generators (BMGs), electric vehicles (EVs), diesel generators (DGs), and battery banks (BBs) for storage purposes. The seven different microgrid setups are tested in different weather and load conditions. The best setup, according to techno-economic analysis, has NPC (₹32 345 782), COE (₹9.23/kWh), and CE (408 348 kg/year). It has PV (210 kW), WTG (91 kW), BMG (25 kW), BB (265 kWh), EVs (22 kW), and DG (28 kW). The simulation results show that this system is the best of all the MGs in every situation. The DRL method is better for the environment and for techno-economics-storage than other methods. The DRL approach is the best for future microgrid designs. It gives energy planners and regulators ideas on how to make autonomous microgrid systems more reliable and efficient.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Durability-Oriented Energy Management for Multi-Stack Fuel Cell Hybrid Vehicles","authors":"Yisai Fan,&nbsp;Zhidong Qi,&nbsp;Zhongbo Cao,&nbsp;Jiapeng Wu","doi":"10.1002/est2.70503","DOIUrl":"https://doi.org/10.1002/est2.70503","url":null,"abstract":"<div>\u0000 \u0000 <p>Energy management strategies (EMSs) for multi-stack fuel cell systems (MFCSs) rarely co-optimize fuel economy and durability: offline optimizers cannot track real-time changes in stack state of health, and most learning-based EMSs target single-stack systems, leaving inter-stack aging consistency unaddressed. This study proposes a two-layer hierarchical EMS that jointly considers hydrogen consumption and inter-stack performance consistency. In the upper layer, a causal sliding-window Daubechies-4 wavelet scheme decomposes the power demand into low- and high-frequency components in real time without future information; the battery absorbs the high-frequency component, shielding the stacks from the rapid load fluctuations that accelerate degradation. The proposed ARP-SC-NSGA-III algorithm—improving convergence and suppressing oscillatory power commands over conventional NSGA-III through adaptive reference-point regeneration and a smoothness constraint—then yields a compromise total fuel-cell power reference that balances hydrogen consumption, SOC deviation, and preferred-range operation. In the lower layer, a trained twin delayed deep deterministic policy gradient (TD3) agent allocates the upper-layer fuel cell power demand among stacks with different aging states to reduce inter-stack degradation imbalance. Hardware-in-loop (HIL) results on the untrained HWFET and WLTP cycles show that the proposed strategy reduces SOC-corrected equivalent hydrogen consumption by up to 9.71% and mean degradation inconsistency by up to 93.84% relative to fuzzy control, and lowers hydrogen consumption by 4.55% under WLTP relative to the equivalent consumption minimization strategy (ECMS), while maintaining the battery state of charge (SOC) within ±0.05 of its target value.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148849220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Step Zinc Chloride and Potassium Hydroxide Activated Nitrogen and Oxygen Co-Doped Hierarchical Porous Biocarbon for High-Performance Supercapacitors","authors":"Amadou Belal Gueye,&nbsp;Sam John,&nbsp;Martin George Thomas,&nbsp;Modou Fall,&nbsp;Ditty Dixon,&nbsp;Viswanathan S. Saji,&nbsp;Sabu Thomas","doi":"10.1002/est2.70498","DOIUrl":"https://doi.org/10.1002/est2.70498","url":null,"abstract":"<div>\u0000 \u0000 <p>In this study, we have prepared N and O co-doped porous carbon from walnut shells and significantly improved its physico-chemical properties by a two-step chemical activation approach using ZnCl₂ and KOH. The synergistic effect of ZnCl₂ and KOH activation resulted in a well-developed hierarchical porous architecture with a high specific surface area (901 m².g⁻¹) and abundant O and N functional groups, as confirmed by XPS analysis. These features facilitated efficient ion transport and enhanced charge storage capacity. Tested in a three-electrode supercapacitor configuration using a 1 M H₂SO₄ electrolyte, the optimized carbon electrode exhibited a high specific capacitance of 520 F·g⁻¹ at 1 A·g⁻¹, and outstanding cycling stability over 5000 cycles with a capacity retention greater than 99%. This work presents a sustainable and efficient route to designing high-performance electrode materials from biowaste for next-generation energy storage devices.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148849216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Storage Solar Collectors for Continuous Thermal Energy Beyond Sunshine Hours","authors":"Omer K. Ahmed,&nbsp;Sameer Algburi","doi":"10.1002/est2.70502","DOIUrl":"https://doi.org/10.1002/est2.70502","url":null,"abstract":"<div>\u0000 \u0000 <p>The limited continuity of thermal energy production during periods without solar radiation remains one of the major challenges facing conventional solar collector systems. This has stimulated growing interest in Integrated Storage Solar Collectors (ISSCs), which combine solar energy collection and thermal storage within a single unit to enhance thermal stability and enable extended operation beyond sunshine hours. This review critically examines recent developments in ISSC technologies, with particular emphasis on thermal storage strategies for prolonged off-sunshine operation. The review covers sensible, latent, thermochemical, and hybrid thermal storage systems, together with recent advances involving phase-change materials (PCMs), porous media, nanomaterials, and intelligent thermal management techniques. Representative studies have reported that PCM-based and hybrid storage systems can extend useful heat retention from &lt; 2 h in conventional collectors to ~12 h or more under optimized operating conditions. At the same time, thermal efficiency improvements ranging from 15% to 40% have been achieved depending on the storage configuration, operating conditions, and enhancement techniques employed. The review also discusses heat-release strategies and current technical challenges, including low thermal conductivity, PCM leakage, long-term material stability, and commercialization barriers. Furthermore, it proposes a new classification framework based on heat retention duration and off-sunshine operating capability, providing standardized categories for comparing ISSCs according to their operational performance. Finally, key research gaps and future directions are identified, highlighting the potential of intelligent thermal management, hybrid storage technologies, and AI-assisted control systems for the development of next-generation ISSCs capable of delivering reliable thermal energy beyond sunshine hours.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrolyte-Dependent Charge Storage in ZnFe2O4: Insights Into Fe Mixed-Valence Electronic Structure via Near-Edge X-Ray Absorption Fine Structure (NEXAFS) and Symmetric Supercapacitor Performance","authors":"Adil Alshoaibi,&nbsp;Manas Nasit,&nbsp;Nagih M. Shaalan,&nbsp;Najla Almulhem,&nbsp;Keun Hwa Chae,&nbsp;Shalendra Kumar","doi":"10.1002/est2.70501","DOIUrl":"https://doi.org/10.1002/est2.70501","url":null,"abstract":"<div>\u0000 \u0000 <p>This study establishes a direct correlation between Fe mixed-valence electronic structure and electrolyte-dependent charge-storage behavior in ZnFe₂O₄. ZnFe₂O₄ were synthesized via a co-precipitation route and systematically investigated for their structural, electronic, and electrochemical properties. Near-edge X-ray absorption fine structure (NEXAFS) spectroscopy at the Fe L_3,2- and O K-edges revealed a partially inverse spinel structure with mixed Fe²⁺/Fe³⁺ valence states, where linear combination fitting indicated ~74.4% Fe³⁺ and ~25.6% Fe²⁺. The enhanced Fe-O hybridization arising from this mixed-valence configuration is beneficial for charge transport. Electrochemical performance of the ZnFe₂O₄ electrode was evaluated in a three-electrode configuration using cyclic voltammetry, galvanostatic charge–discharge, and electrochemical impedance spectroscopy in 1.0 M KOH and 1.0 M Na₂SO₄ electrolytes. The ZnFe₂O₄ electrode exhibited significantly superior capacitive behavior in Na₂SO₄, delivering a high specific capacitance of 692.2 F/g at 1 A/g and an energy density of 96.13 Wh/kg. Kinetic analysis revealed a mixed charge-storage mechanism dominated by surface-controlled capacitive processes. Furthermore, the electrode demonstrated excellent cyclic stability with ~91% capacitance retention after 2000 charge–discharge cycles. The enhanced electrochemical performance in Na₂SO₄ is attributed to improved ion transport, reduced interfacial resistance, and greater electrochemical stability. When employed as an electrode in a symmetric supercapacitor device, ZnFe₂O₄ delivered a maximum specific capacitance of 201.28 F/g at a current density of 0.25 A/g, along with a high energy density of 71.57 Wh/kg at a power density of 400 W/kg. Furthermore, the SSCD exhibited notable cycling stability, retaining 46.93% of its initial capacitance after 10 000 galvanostatic charge–discharge cycles at a current density of 2.5 A/g. These results highlight ZnFe₂O₄ as a promising electrode material for high-performance supercapacitor applications, particularly in neutral electrolytes.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermochemical Energy Storage Using Perovskite Oxides—A Review","authors":"Rahul R. Bhosale,&nbsp;George Thompson,&nbsp;Mohammad Mahtabi","doi":"10.1002/est2.70492","DOIUrl":"https://doi.org/10.1002/est2.70492","url":null,"abstract":"<div>\u0000 \u0000 <p>Thermochemical energy storage (TCES) based on reversible redox reactions of metal oxides has emerged as a promising solution for high-temperature energy storage in next-generation concentrating solar power (CSP) systems. Among the candidate materials, perovskite oxides (ABO_3-<i>δ</i>) are particularly attractive due to their compositional tunability, ability to sustain continuous and reversible oxygen non-stoichiometry, and structural stability under repeated high-temperature redox cycling. These characteristics enable systematic optimization of redox thermodynamics, oxygen exchange capacity, and reaction kinetics for advanced CSP applications. Accordingly, this review critically assesses perovskite oxide–based TCES materials with emphasis on redox thermodynamic behavior, oxygen exchange characteristics, kinetic performance, and system-level relevance. La-, Ba-, Sr-, and Ca-based perovskite families are systematically examined, highlighting the complementary roles of A-site and B-site substitution in controlling reduction temperature, oxygen vacancy energetics, redox extent, and cycling durability. Many cobalt- and iron-containing perovskites exhibit high oxygen exchange capacities, with reversible oxygen non-stoichiometry changes of Δ<i>δ</i> ≈ 0.25–0.50 and reduction onset temperatures as low as ~300°C–500°C, enabling rapid charging and discharging. In contrast, calcium manganite–based perovskites operate at higher temperatures (~700°C–1100°C) but demonstrate exceptional thermal robustness and high reduction enthalpies, achieving total TCES densities exceeding ~800–1000 kJ/kg through combined sensible and chemical storage. Experimental demonstrations in TGA systems, packed beds, fluidized beds, porous structures, and directly irradiated granular-flow reactors confirm feasibility beyond idealized equilibrium conditions. The review further identifies key challenges related to kinetics, heat and mass transfer, and reactor-scale integration, while outlining future opportunities for materials optimization and system-level deployment.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal, Electrical, and Economic Assessment of Multilayer Phase Change Material Heat Sinks for Photovoltaic Modules at Different Inclinations: A Numerical Analysis","authors":"Zoubida Haddad,&nbsp;Atef Chibani,&nbsp;Farhan Lafta Rashid","doi":"10.1002/est2.70499","DOIUrl":"https://doi.org/10.1002/est2.70499","url":null,"abstract":"<div>\u0000 \u0000 <p>Passive cooling using phase change materials (PCMs) can reduce photovoltaic (PV) overheating; however, its effectiveness depends on PCM properties, layer arrangement, system inclination, and material cost. This study presents a transient two-dimensional numerical investigation of nine PV–PCM heat-sink configurations, including six multilayer arrangements and three single PCM reference cases based on gallium, CaCl₂·6H₂O, and RT35HC. Five inclination angles, <i>β</i> = 0°, 30°, 45°, 75°, and 90°, are examined during a 7 h heating period under a constant equivalent heat flux of 1000 W m⁻². Simulations are performed using the enthalpy–porosity method and validated against independent experimental and numerical data. The results show that PCM selection and inclination have a greater influence on system performance than multilayer ordering. Pure gallium provides the most stable thermal regulation and the highest 7 h average electrical efficiency at all inclinations, with values ranging from 11.89% to 11.96%. Among the multilayer configurations, the best performance is obtained by Case 2 at 0° with an efficiency of 8.05%, Case 3 at 30° with 10.09%, Case 1 at 45° and 75° with 10.46% and 10.50%, respectively, and Case 6 at 90° with 10.37%. RT35HC exhibits the strongest inclination dependence, with its average electrical efficiency increasing from 0.29% at 0° and 1.10% at 30° to 11.34% at 75° and 11.33% at 90° because of enhanced buoyancy-driven heat redistribution. The enthalpy and liquid fraction results further show that stronger natural convection does not uniformly accelerate melting, as it can create both rapidly melted regions and locally trapped solid PCM. The economic analysis indicates that gallium-containing configurations become progressively less attractive as the gallium-to-RT35HC price ratio increases, whereas RT35HC provides the highest cost–performance at steep inclinations. These findings demonstrate that optimal PV–PCM design requires simultaneous consideration of thermal transport, phase-change utilization, inclination, PCM inventory, and price uncertainty.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hybrid Forecasting and Optimization Framework for Electric Vehicle Scheduling in Virtual Power Plants","authors":"Hodade Dipali Nagnath,&nbsp;A. Arunya Revathi,&nbsp;Melam Thirupathaiah,&nbsp;D. Santhakumar","doi":"10.1002/est2.70493","DOIUrl":"https://doi.org/10.1002/est2.70493","url":null,"abstract":"<div>\u0000 \u0000 <p>The present study proposes a hybrid energy management (EM) framework for vehicle-to-grid (V2G) enabled virtual power plants (VPPs), integrating Green Anaconda Optimization (GAO) with a Pyramidal Dilation Attention Convolutional Neural Network (PDACNN) for cost-efficient and adaptive scheduling. The PDACNN module forecasts renewable energy (RE) generation and load demand using multiscale feature extraction and attention mechanisms, while GAO optimizes EV charging (EVC)/discharging schedules under grid constraints. Two scenarios are evaluated: with and without IoT-enabled coordination. Simulation results show that the proposed GAO-PDACNN method reduces the total operating cost (OC) to $499 626/year, which is 1.7% lower than MOPSO, 14.2% lower than the GA, and 34.6% lower than the HPOA. Further, CO₂ emissions are lowered by 9.0 × 10⁶ tons/year, which is 53.8% less than conventional strategies using HPOA. The model also has a load cover accuracy of 92.4%, and a convergence in only 62 iterations, which is more efficient and stable than other benchmark models. This is to validate the efficiency of the framework to facilitate intelligent coordination in V2G for smart grid (SG) with higher RE penetration.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Automotive Battery Modules Using a Coupled Numerical Model With Hybrid Passive–Active Thermal Management","authors":"Tejas Kalvankar,&nbsp;G. Amba Prasad Rao","doi":"10.1002/est2.70496","DOIUrl":"https://doi.org/10.1002/est2.70496","url":null,"abstract":"<div>\u0000 \u0000 <p>The increasing deployment of lithium-ion batteries (LIBs) in electric vehicles (EVs) demands robust thermal management to ensure safety and performance, particularly, under high-current discharge and dynamic load conditions. The present study evaluated a battery pack at the system level, using both detailed finite-volume simulation and system-level dynamic modeling for an LFP battery module. Initially, a 3D thermal model was developed to evaluate the effectiveness of phase change material (PCM)-based passive battery thermal management systems (BTMS). Under 5C discharge, the 4S1P module's peak temperature dropped from 72°C to 44.8°C through progressive integration of varying PCM layer thickness from 2 to 8 mm, enhancing the varied convective heat transfer coefficient, and ultimately incorporating metal foam within the PCM matrix. To evaluate the system under real-world EV operating conditions, a Simulink model was developed using an identical module configuration and thermal parameters, incorporating a liquid cooling strategy using water as the coolant, enabling effective heat extraction across both FTP-75 and UDDS drive cycles at varying ambient temperatures from 25°C to 40°C and different Reynolds numbers (Re). Under the stringent FTP-75 drive cycle at 40°C ambient, the model demonstrated robust thermal performance, with Re = 3000 resulting in a peak temperature of 42°C, while increasing coolant flow at Re = 10 000 reduced it to 38.5°C. In comparison, the milder UDDS cycle yielded a peak of 41.8°C at Re = 3000 and 39.3°C at Re = 10 000. The present study demonstrates battery pack-to-system thermal synergy and provides a validated framework for efficient BTMS design in EVs.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"8 6","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}