Energy Storage最新文献

{"title":"Remaining Useful Life Prediction of Li-NMC Batteries Using Algorithmic Fusion and Cascading Approach","authors":"Sreejaun Thothaathiri Janaki,&nbsp;Naresh Gnanasekaran,&nbsp;Dinesh Kumar Madheswaran,&nbsp;Praveenkumar Thangavelu,&nbsp;Sivanesan Murugesan","doi":"10.1002/est2.70219","DOIUrl":"https://doi.org/10.1002/est2.70219","url":null,"abstract":"<div>\u0000 \u0000 <p>Lithium-NMC batteries in electric vehicles exhibit complex degradation mechanisms, where capacity fade, internal resistance growth, and discharge behavior evolve nonlinearly under varying operating conditions. Accurate remaining useful life prediction necessitates capturing these intricate interdependencies, which traditional models fail to generalize effectively. This study develops a robust machine-learning framework leveraging experimental cycling data under nominal and over-discharge conditions. Key parameters like voltage, discharge time, internal resistance, and state of health were chosen due to their direct correlation with electrochemical aging, resistive losses, and failure progression, ensuring high sensitivity to degradation dynamics. Support Vector Regression and Bayesian-optimized Lasso Regression were employed to model these dependencies, providing precise predictions of key battery health indicators. A hybrid framework integrating these models for remaining useful life estimation achieved <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mi>R</mi>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ {R}^2 $$</annotation>\u0000 </semantics></math>, MAE, RMSE of 0.9998, 0.093 and 0.138 respectively, significantly outperforming conventional approaches. Rigorous evaluation through K-fold cross-validation and subset stability analysis ensured generalizability across diverse operating conditions. Benchmark comparisons with state-of-the-art methods demonstrated superior predictive accuracy. By addressing critical limitations in traditional degradation modeling, this work provides a scalable, data-driven solution for real-time battery health management, enhancing the reliability and sustainability of electric vehicle applications.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606461","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":"Performance Study of Gel Polymer Electrolyte-Based EDLC With Silver-Coated Textile Substrate for Integrated PV-EDLC System","authors":"W. L. Leong,&nbsp;Grishika Arora,&nbsp;Nuur Syahidah Sabran,&nbsp;H. K. Jun","doi":"10.1002/est2.70221","DOIUrl":"https://doi.org/10.1002/est2.70221","url":null,"abstract":"<div>\u0000 \u0000 <p>A novel integrated energy storage system combining a flexible silver-coated textile-based electric double-layer capacitor (EDLC) with commercial solar photovoltaics (PV) has been successfully developed. This system, capable of bending up to 180°, demonstrates excellent mechanical flexibility, wearability, and energy performance, addressing key limitations in conventional EDLCs such as rigidity, bulkiness, and low energy density. The textile-based EDLC, fabricated using a gel polymer electrolyte (GPE), achieved a high specific capacitance of 2.89 mF cm⁻² (71.32 F kg⁻¹), along with energy and power densities of 12.5 and 13.2 mW cm⁻², respectively. Notably, the device retained 100% capacitance over short cycling bursts, confirming its stability and reliability. What distinguishes this work is the use of silver-coated textile as both a current collector and flexible substrate, offering biocompatibility, high conductivity, and excellent integration with garments. This material choice allows higher mass loading and enhanced charge storage without compromising comfort or flexibility. When integrated with a flexible solar PV, the system achieved an overall power conversion efficiency of 2.2% and demonstrated rapid charging capability, powering a simple electronic device for 30 min after just 5 s of sunlight exposure. This study presents a low-cost, lightweight, and durable solution for next-generation wearable electronics, pushing forward the development of flexible, textile-based PV-EDLC systems by overcoming the limitations of existing rigid or semi-flexible designs.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581851","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":"An Optimized Bi-LSTM Machine Learning Model for Predicting Congestion at Electric Vehicle Charging Stations","authors":"Sourav Sarkar,&nbsp;Jenson Narzary,&nbsp;Debasis Chaterjee,&nbsp;Amarjit Roy,&nbsp;Chiranjit Sain,&nbsp;Anubav Agarwal,&nbsp;F. Ahmad","doi":"10.1002/est2.70216","DOIUrl":"https://doi.org/10.1002/est2.70216","url":null,"abstract":"<div>\u0000 \u0000 <p>The proliferation of electric vehicles (EVs) has intensified the need for efficient and reliable charging infrastructure. This study introduces a bidirectional long short-term memory (Bi LSTM)-based model designed to predict and manage congestion at EV charging stations. Leveraging the advanced capabilities of Bi LSTM networks in handling sequential data, our model analyzes historical and real-time data to forecast congestion levels. The bidirectional nature of the LSTM allows for a comprehensive analysis of the data, capturing dependencies from both past and future contexts. The proposed model aims to provide real-time intimation to both users and operators, enhancing decision-making processes and optimizing the utilization of charging resources. By offering accurate predictions of congestion, the Bi LSTM-based model facilitates strategic planning for station deployment and user navigation, ultimately improving the overall efficiency of the charging infrastructure. Experimental results demonstrate the model's efficacy in accurately predicting congestion, significantly reducing wait times, and improving user satisfaction. This research underscores the potential of advanced machine learning techniques, particularly Bi LSTM networks, in addressing the dynamic challenges of EV charging station management. The implementation of such predictive models is a crucial step toward the development of a smart, efficient, and user-centric EV charging ecosystem.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581850","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 Performance Assessment of Nano-Enhanced Phase Change Material-Based Building Envelopes for Tropical Climatic Cities in India","authors":"Jagadeesan Dhayanithi,&nbsp;Tapano Kumar Hotta","doi":"10.1002/est2.70220","DOIUrl":"https://doi.org/10.1002/est2.70220","url":null,"abstract":"<div>\u0000 \u0000 <p>The manuscript aims to assess numerically the thermal performance of building envelopes (integrated with nano-enhanced phase change material) for the tropical climatic cities in India during the hottest months of May/June. A building envelope of size 5 m (Length) × 4 m (Width) × 3.5 m (Height) integrated with a 25 mm thick Rubitherm phase change material layer on its walls and roof is considered for the analysis. The numerical model is developed using the Design-Builder software by considering the dissimilar Indian climatic zones (composite, hot-dry, and warm-humid) and buildings of the different Indian cities (Delhi, Ahmedabad, and Chennai). The goal is to reduce the peak temperature in the buildings of these cities. The maximum solar intensity for these cities is found between 11 AM to 1 PM for the hottest month, May/June of the year, which is very high (22 kW) in Delhi, followed by Chennai (20 kW), and then Ahmedabad (18 kW). The phase change material stores heat during the peak hours (daytime) and releases the same during the off-peak hours (nighttime) when integrated into the building envelopes. The results show that the building temperature was reduced by 4°C, 5.8°C, and 1.2°C for Delhi, Ahmedabad, and Chennai, respectively. The heat gain reduction from conventional buildings compared to the phase change material-integrated buildings of Delhi, Ahmedabad, and Chennai is 33.47, 35.59, and 26.14 kWh/m², respectively. The thermal enhancement ratio, which captures the building performance with and without using phase change material, is calculated as 0.988, 0.982, and 0.996 for Delhi, Ahmedabad, and Chennai, respectively. This confirms the significant role of phase change material in lowering the peak loads in Indian buildings.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519715","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":"Enhancing Stability and Performance of Grid-Connected Residential PV Systems With Battery-Super Capacitor Storage Using Advanced Control Techniques","authors":"V. Pushpabala,&nbsp;C. Christober Asir Rajan","doi":"10.1002/est2.70202","DOIUrl":"https://doi.org/10.1002/est2.70202","url":null,"abstract":"<div>\u0000 \u0000 <p>The increasing integration of renewable energy technologies poses significant challenges to the power grid due to generation unpredictability. Variations in output, driven by weather uncertainties, highlight the need for effective storage solutions to maintain grid stability and reliability. This research proposes a novel approach for a grid-connected residential photovoltaic (PV) system incorporated with a hybrid energy storage system (HESS) comprising a battery bank and a super capacitor (SC) pack. The novelty of this paper lies in the innovation of the Red Panda Optimization (RPO) and Efficient Predefined Time Adaptive Neural Network (EPTANN). Hence, the method is named RPO-EPTANN. The objective of the proposed method is to enhance stability, reduce voltage overshoot, improve efficiency, and reduce the system's entire cost. The converter's control signal is optimized using the proposed RPO, and the EPTANN predicts the converter's ideal control signal. By then, the proposed approach is put into practice from the MATLAB working platform, and the findings are calculated using the existing process. The proposed strategy outperforms all current approaches in terms of Particle Swarm Optimization (PSO), Artificial Neural Networks (ANN), and Artificial Rabbits Optimization (ARO). The existing methods exhibit total system costs of 27 660$, 29 665$, and 30 025$, whereas the proposed method achieves a significantly lower cost of 24 540$. Efficiency of 85%, 75%, and 62% in the existing approaches are improved to 98% with the proposed method. These findings indicate that the proposed RPO-EPTANN method significantly reduces operational costs while enhancing overall system efficiency. This reflects a substantial advancement in performance, ensuring improved stability, reliability, and energy optimization in grid-connected residential PV systems.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482294","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 Review on Functional Materials for Hydrogen Storage","authors":"Parag Girhe,&nbsp;Divya P. Barai,&nbsp;Bharat A. Bhanvase,&nbsp;Sandip H. Gharat","doi":"10.1002/est2.70218","DOIUrl":"https://doi.org/10.1002/est2.70218","url":null,"abstract":"<div>\u0000 \u0000 <p>The need for safe, cost-effective, lightweight, and energy-efficient hydrogen storage in both mobile and stationary applications has led to the development of novel materials with functional properties. Effective hydrogen storage materials possess characteristics such as high capacity per unit mass, minimal energy loss during charging and discharging, efficient kinetics, stability against O₂, recyclability at low cost, and significant safety features. Solid-state storage has emerged as a preferred technique for hydrogen storage compared to pressurized gas and liquefaction processes, primarily due to its ability to achieve high storage capacities while maintaining safe operating conditions. Metal hydrides, such as MgH₂, exhibit a hydrogen storage capacity of up to 7.6 wt.%, while complex hydrides like LiBH₄ can store up to 18.5 wt.% hydrogen. Adsorption-based nanostructured materials, such as activated carbon and metal–organic frameworks, offer high surface areas for hydrogen uptake, with capacities reaching 5–7 wt.% at cryogenic temperatures. This review critically evaluates recent advancements in hydrogen storage materials, highlighting breakthroughs in kinetics enhancement, thermodynamic stability, and material reversibility. Compared to previous studies, this work consolidates key developments and identifies future research directions for optimizing hydrogen storage performance in real-world applications. This review provides in-depth insights into the mechanisms of functional solid material for hydrogen storage and explores the factors influencing their performance. Additionally, various applications of hydrogen storage across different sectors are discussed, highlighting the potential of these storage technologies in practical settings.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482140","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":"Carbon Sphere-Infused PET CS/PET: Enhancing Energy Storage Efficiency of Vanadium Flow Batteries and Supercapacitors","authors":"Gireeshkumar Basavaraj Chavati,&nbsp;Sharath Kumar Basavaraju,&nbsp;Arthoba Nayaka Yanjerappa,&nbsp;Malashri Boraiah Sannaobaiah,&nbsp;Handanahally Basavarajaiah Muralidhara,&nbsp;Krishna Venkatesh,&nbsp;Keshavanarayana Gopalakrishna","doi":"10.1002/est2.70217","DOIUrl":"https://doi.org/10.1002/est2.70217","url":null,"abstract":"<div>\u0000 \u0000 <p>The recycling of widely available polyethylene terephthalate (PET) into activated carbon–carbon sphere composites represents a sustainable approach for developing advanced energy storage materials. In this study, a novel carbon sphere@polyethylene terephthalate (CS/PET) active material was synthesized using a cost-effective hydrothermal process, integrating dextrose-derived oxygen-rich carbon spheres and PET-derived activated carbon. This eco-friendly composite was utilized to modify 132 cm² graphite felt electrodes for vanadium redox flow batteries (VRFBs) and served as an active material in supercapacitors. As a positive electrode electrocatalyst in VRFBs, the CS/PET-modified electrode achieved a coulombic efficiency (CE) of 88.43%, a voltage efficiency (VE) of 59.79%, and an energy efficiency (EE) of 51.92%, with excellent stability over 100 cycles. For supercapacitor applications, the CS/PET composite exhibited an impressive specific capacitance of 193 F/g at 2 A/g, delivering 100% coulombic efficiency and 92% retention over 2500 cycles. These results highlight the potential of CS/PET composites as cost-effective, clean, and high-performance materials for sustainable energy storage systems, demonstrating significant promise for meeting future energy demands while addressing global environmental challenges.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482139","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":"Correction to “Parametric Based Techno-Economic Evaluation for a Solar Thermal-PV Integrated Multi-Commodity Storage Facility”","authors":"","doi":"10.1002/est2.70215","DOIUrl":"https://doi.org/10.1002/est2.70215","url":null,"abstract":"<p> <span>Shahzaib, M.</span> <span>Moeez, A.</span> <span>Memon, A. G.</span> <span>Kumar, L.</span> “ <span>Parametric Based Techno-Economic Evaluation for a Solar Thermal- PV Integrated Multi-Commodity Storage Facility</span>,” <i>Energy Storage</i> <span>6</span>, no. <span>6</span> (2024): e70022, https://doi.org/10.1002/est2.70022.</p><p>The funding statement for this article was missing. The below funding statement has been added to the article:</p><p>Qatar University Open Access publishing facilitated by the Qatar National Library, as part of the Wiley Qatar National Library agreement.</p><p>We apologize for this error.</p>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/est2.70215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hybrid Approach for Smart Energy Management in Microgrids With Electric Vehicle Charging Using Snow Ablation Optimization and Cascade Chaotic Neural Network","authors":"R. Raja,&nbsp;K. Sureshkumar,&nbsp;Kurra Venkateswara Rao,&nbsp;N. Jayashree","doi":"10.1002/est2.70208","DOIUrl":"https://doi.org/10.1002/est2.70208","url":null,"abstract":"<div>\u0000 \u0000 <p>Integration of Renewable Energy Sources (RES) with Electric Vehicles (EVs) elucidates a crucial area in Energy Management (EM) for Microgrids (MGs). Probably the most difficult job is stochastic behavior from RES together with unpredictable EV charging demands, aspires towards grid stability, and destabilizes prompt frequency control. This article introduces a hybrid methodology designed for intelligent EM in MGs with EV charging. Proposed method integrates Snow Ablation Optimization (SAO) and Cascade Chaotic Neural Network (CCNN); therefore, it is called the SAO-CCNN technique. The aim is to improve economic performance of the MG integrated by EV charging by minimize the Operating Cost. SAO optimizes the utilization of RES and EVs, improving overall energy management. The CCNN is employed to predict the participation probability of EVs in grid support activities, thereby aiding in the accurate forecasting of energy demand. The suggested SAO-CCNN technique is implemented on MATLAB platform and evaluated against existing optimization methods, including Firefly Optimization Algorithm (FOA), Particle Swarm Optimization (PSO), Robust Optimization Algorithm (ROA), Multi Objective Optimization (MOO), and Whale Optimization Algorithm (WOA). The operating cost achieved using the proposed method is $17 184.1, demonstrating improved cost-efficiency compared to optimization methods.</p>\u0000 </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315143","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":"Correction to “Performance Analysis of a Renewable-Powered Multi-Gas Floating Storage and Regasification Facility for Ammonia Vessels With Reconversion to Hydrogen”","authors":"","doi":"10.1002/est2.70214","DOIUrl":"https://doi.org/10.1002/est2.70214","url":null,"abstract":"<p>D. Andriani, M. U. Sajid, and Y. Bicer, “Performance Analysis of a Renewable-Powered Multi-Gas Floating Storage and Regasification Facility for Ammonia Vessels With Reconversion to Hydrogen,” <i>Energy Storage</i> 6, no. 6 (2024): e70033, https://onlinelibrary.wiley.com/doi/10.1002/est2.70033.</p><p>The funding statement for this article was missing. The below funding statement has been added to the article:</p><p>Hamad Bin Khalifa University Open Access publishing facilitated by the Qatar National Library, as part of the Wiley Qatar National Library agreement.</p><p>We apologize for this error.</p>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/est2.70214","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}