Article
Thermodynamics
Mohsen Rezaei
Summary: A novel concept called possibilistic stochastic multi-attribute decision-making (PSMADM) is proposed in this study to address uncertainties in the field of energy policy. The approach is used to rank Iran's biodiesel development policies, with the results indicating that supporting the private sector for more participation in biodiesel development is the best alternative. The study also introduces a new scenario planning method for designing biodiesel scenarios, and utilizes fuzzy SWARA and fuzzy EDAS methods to solve different MCDM models.
Article
Computer Science, Information Systems
Jiang Deng, Jianming Zhan, Wei-Zhi Wu
Summary: This paper introduces the application of three-way decision (3WD) in a multi-scale decision information system (MS-DIS) to solve multi-attribute decision-making problems using fuzzy membership functions and distance-based cost measurement. The effectiveness of the proposed method is demonstrated through a specific numerical example and experimental analysis.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
M. Alipour-Vaezi, R. Tavakkoli-Moghaddam, Z. Mohammadnazari
Summary: This study focuses on the scheduling problem for television advertisements using multi-attribute decision making and multi-objective mathematical models. The effectiveness of different categories of advertisements in different timeslots is evaluated using a hybrid MADM method. A multi-objective mathematical model is then used to maximize the display effectiveness of advertisements by maximizing total income. Several dispatching rules are used to examine advertisement scheduling. The proposed methodology is validated using three test problems and shown to provide optimal solutions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Construction & Building Technology
Chujun Zong, Manuel Margesin, Johannes Staudt, Fatma Deghim, Werner Lang
Summary: This paper proposes a multi-objective stochastic optimization framework for decision-making in the early design phase of building facade design under uncertainty. The framework aims to narrow down the material choices and provide robust solutions. Through a case study, the effectiveness of the framework was validated. The results indicate that insulation and outer wall cladding are the most important parameters in building facade design.
BUILDING AND ENVIRONMENT
(2022)
Review
Computer Science, Artificial Intelligence
Amneh Alamleh, O. S. Albahri, A. A. Zaidan, A. H. Alamoodi, A. S. Albahri, B. B. Zaidan, Sarah Qahtan, Amelia Ritahani Binti Ismail, R. Q. Malik, M. J. Baqer, Ali Najm Jasim, Mohammed S. Al-Samarraay
Summary: Intrusion detection systems (IDSs) utilize advanced security techniques to detect malicious activities on hosts and/or networks. Multi-attribute decision-making (MADM) is a commonly used decision support approach for selecting the most optimal solution from available alternatives. This study conducts a systematic review to organize the research landscape of IDS and MADM, providing valuable reference for researchers.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Computer Science, Artificial Intelligence
Feng Wang
Summary: The study proposes a preference degree-based algorithm to rank triangular fuzzy numbers, addressing the issues of ranking TFNs and selecting the best alternative in complex multi-attribute group decision making. By utilizing the utility ratings of alternatives and a control parameter, the attribute weights are determined, offering a new method to solve the triangular fuzzy MAGDM problem.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Na Wei, Feng Yang, Kunming Lu, Jiancang Xie, Shaofei Zhang
Summary: This study proposed a multi-objective optimization and multi-attribute decision-making method for reservoir operation, using the NSGA-II-SEABODE algorithm to obtain decision-making schemes. The case study on the Huangjinxia Reservoir showed that the method can promote efficient utilization of water resources and improve the comprehensive benefits of reservoirs.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Mohammed Al-Samarraay, Omar Al-Zuhairi, A. H. Alamoodi, O. S. Albahri, Muhammet Deveci, O. R. Alobaidi, A. S. Albahri, Gang Kou
Summary: Semiconductor materials are crucial for optoelectronics and power devices, but evaluating and selecting them is a multi-attribute decision-making problem. This study proposes an integrated fuzzy multi-measurement decision-making model (IFMMDMM) for evaluating and selecting optimization techniques for semi-polar III-V semiconductor materials.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Zhi-Gang Zhang, Xiao Hu, Zhao-Ting Liu, Lu-Tao Zhao
Summary: The dynamic expert credibility model (DECM) proposed in this study aims to address the issue of weight calculation affected by expert credibility. Through model validation, DECM significantly improves the effectiveness of attribute weights and effectively eliminates the impact of expert credibility on decision-making results.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Bapi Dutta, Son Duy Dao, Luis Martinez, Mark Goh
Summary: This study investigates strategic manipulation of weight information in a TOPSIS MADM method under two scenarios and formulates the problem as a mixed integer non-linear programming (MINLP) problem. A genetic algorithm based solution procedure is developed to solve this highly constrained problem.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2021)
Article
Engineering, Multidisciplinary
Jirong Jiang, Min Ren, Jiqiang Wang
Summary: This paper proposes a method based on TOPSIS and weighted parameter to deal with multi-attribute decision-making problems with interval numbers. The method transforms the interval number matrix into exact number matrices and uses entropy weight to determine the weights. TOPSIS is then used to determine the order, and the average value of the ranking number is used to reflect the actual situation better. The proposed method is demonstrated to be feasible, practical, stable, and effective.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Information Systems
Wenjie Wang, Jianming Zhan, Chao Zhang
Summary: Multi-attribute decision making (MADM) is a crucial part of modern decision sciences, with three-way decisions (3WD) being able to reduce decision risks and improve accuracy compared to traditional two-way decisions (2WD). This paper presents a new 3WD-MADM model based on probabilistic dominance relations, and validates its effectiveness through comparative and experimental analyses.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Zhike Li, Yong Wang
Summary: This article introduces a method to optimize the performance of the Ceph cloud storage system based on SDN technology. By considering node heterogeneity, network state, and node load, load balancing is improved, and the performance of read and write operations is enhanced. Experimental results show that the optimized algorithms can significantly improve performance.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Construction & Building Technology
Zhen Han, Xiaoqian Li, Jiaqi Sun, Mo Wang, Gang Liu
Summary: Building performance design is crucial for sustainable urban development, involving conflicting performance criteria such as energy consumption and daylighting. This study proposes a multi-criteria decision-making method based on sensitivity analysis and analytic hierarchy process, enabling real-time interactive optimization of building performance. Application of the method to a case study in China demonstrates improved performance and increased design efficiency for architects. This method enhances decision-making in building sustainable design and supports the improvement of building performance and urban sustainability.
ENERGY AND BUILDINGS
(2023)
Article
Mathematics
Fan Jia, Yujie Wang, Yiting Su
Summary: As an important branch of modern decision-making theory, multi-attribute decision-making (MADM) plays a crucial role in various fields. The classic MADM methods can offer alternatives ranking, but decision-makers need to subjectively evaluate the level based on the ranking, which may lead to potential individual losses. In this paper, a dynamic hybrid multi-attribute three-way decision (MA3WD) model is proposed to address this issue.
Article
Computer Science, Cybernetics
Elham Samadpour, Rouzbeh Ghousi, Ahmad Makui
Summary: This study aims to address the routing and scheduling problem of health workers in home health care management system, successfully reducing costs and improving efficiency through the development of a mixed-integer linear programming model. The study fills the gap of previous research that often focuses on issues involving only one group of health professionals, by considering situations involving multiple groups of health professionals.
Article
Operations Research & Management Science
Mehdi Alizadeh, Mir Saman Pishvaee, Hamed Jahani, Mohammad Mahdi Paydar, Ahmad Makui
Summary: In this study, a viable healthcare network design for a pandemic is developed using a multi-stage stochastic approach. The proposed multi-level network includes health centers, computed tomography scan centers, hospitals, and clinics, and aims to maximize patient recovery probability, minimize network costs, and reduce the Coronavirus death rate. An investigation of a real case study in Iran demonstrates the model's applicability and provides a comparison between healthcare supply chain network design in a pandemic and a normal situation.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Kimia Parandeh, Abed Bagheri, Shahram Jadid
Summary: Nowadays, grid-connected renewable energy resources are widely used in the electricity market. To provide household consumers with photovoltaic (PV) systems, bilateral interfaces are required for energy and data exchange. Day-ahead dynamic pricing is an effective method for integrating renewable energy resources with smart grids and ensuring social welfare. Different metering mechanisms such as feed-in tariffs, net metering, and net purchase and sale play important roles in power grid operation planning. In this paper, optimal condition decomposition method is used to analyze the day-ahead dynamic pricing of grid-connected residential renewable energy resources under different metering mechanisms and carbon emission taxes. The results show that net metering and net purchase and sale mechanisms can significantly reduce total load while feed-in tariff mechanism increases social welfare without load reduction.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Energy & Fuels
Ali Jani, Shahram Jadid
Summary: This paper focuses on the day-ahead and real-time transactive energy markets in the multi-microgrid system. The main purpose is to obtain an optimal schedule for the energy management of microgrids in energy markets. The proposed approach is modeled in a time frame including offline and online classes using a bi-level optimization structure. The first stage considers the day-ahead scheduling of the multi-microgrid system using game theory, where a retail market is established for transactive energy exchange between the microgrids and the microgrid community on an hourly time scale. The second stage focuses on managing the fluctuations of renewables and electricity demand on a shorter time scale and forming a real-time market in the multi-microgrid. The purpose of the second stage implementation is real-time dispatch to minimize the imbalance cost of the microgrids and the microgrid community. The simulation results show that in a cooperative space between neighboring microgrids, the total operating cost is reduced by $61.26. Moreover, this cost reduction reaches $44.05 by moving the battery energy storage systems to the level of microgrids.
Article
Energy & Fuels
Mahsa Babagheibi, Shahram Jadid, Ahad Kazemi
Summary: This paper proposes a robust model of a local flexibility market to incentivize microgrids (MGs) to provide flexibility services to relieve line congestion. The proposed market model is based on a request and response structure, adopting a modified ADMM method for negotiations. It is considered a complementary market for bilateral energy trading of MGs and a distribution system for a fairer environment. The distributed market frameworks ensure data privacy and a low computational burden.
Article
Energy & Fuels
Hamid Karimi, Shahram Jadid
Summary: This paper proposes a stochastic framework for the operation scheduling of integrated renewable-based energy microgrid systems. The proposed model presents comprehensive scheduling that simultaneously considers total generation costs, generation flexibility, and demand-side flexibility. The framework consists of three layers, with each layer targeting specific aspects of the operation management. The application of the proposed framework to a general energy system structure shows significant improvements in electrical and thermal generating flexibility.
Article
Engineering, Electrical & Electronic
Ali Sahebi, Shahram Jadid
Summary: Local energy market formation and the design of new market structures are essential due to changes in power absorption and injection caused by Multi-Energy Micro-Grids (MEMG) and combined heat and power units (CHP). Improving energy trading models can enhance the accuracy of trading schedules and system operating conditions. Robust optimization considers upstream market uncertainty and helps Distribution System Operators (DSO) trade energy with MEMGs, leading to improved energy trading in the local market. Simulation results show that real-time market uncertainty increases DSO operating costs by 16.34%, while strengthening the local energy market increases MEMGs' income by up to 44.4%. The IEEE 33-bus test system with four connected MEMGs is used for simulation.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Hamid Karimi, Shahram Jadid, Saeed Hasanzadeh
Summary: This paper proposes a techno-economic-environmental energy scheduling framework for a multi-energy microgrid system, which couples the electrical, heating, cooling, and water sections to enhance flexibility and reliability. The framework consists of three layers that focus on cost-effective operation management, environmental issues, and independence optimization. Through optimization, the independence of the multi-energy microgrid system and power losses have been significantly improved.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2023)
Article
Engineering, Electrical & Electronic
Hamid Karimi, Mahdieh Monemi Bidgoli, Shahram Jadid
Summary: This paper proposes an economic-environmental scheme for integrating the electrical, water, thermal, and cooling sections of a multi-energy system, aiming to increase efficiency and synergy in modern distribution grids. The use of industrial desalination units to provide potable water is considered, with a preference for groundwater resources due to high energy consumption. However, overuse of groundwater resources leads to various problems, such as climate changes and a lack of adequate water and food supply. Therefore, a multi-objective decision-making scheme is proposed to minimize operating costs and groundwater usage. Furthermore, thermal and electrical demand-side management, along with dispatchable and energy storage systems, are employed to address the intermittent behavior of renewable generation. The optimization results demonstrate that the proposed model reduces groundwater extraction by 26.8% with only a 1.12% increase in operating cost.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Automation & Control Systems
Mahdi Shademan, Hamid Karimi, Shahram Jadid
Summary: This paper presents a method to solve an optimization problem in the electricity distribution system using reinforcement learning and deep neural networks to protect the privacy of microgrids and improve the efficiency of the solution.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Cybernetics
Mohammad Hossein Dehghani Sadrabadi, Ahmad Makui, Rouzbeh Ghousi, Armin Jabbarzadeh
Summary: This study discusses the importance of establishing supply chain resilience and employing business continuity planning to deal with disruptions in order to manage the vulnerability of the supply chain. It proposes a multi-objective optimization model, using business continuity management and organizational resilience, to respond to multiple interrelated disruptions. The study finds that interactions between disruptions significantly increase the supply chain's vulnerability and suggests several effective resilience strategies.
Article
Materials Science, Characterization & Testing
Ali Solouki, Mohammad Reza Mohammad Aliha, Ahmad Makui, Naghdali Choupani
Summary: Additive manufacturing (AM) using 3D printing techniques has gained attention in prototyping and industrial production. This research investigates the impact resistance of 3D-printed components and finds that the type of notch significantly affects the impact energy.
Article
Operations Research & Management Science
Alireza Paeizi, Ahmad Makui, Mir Saman Pishvaee
Summary: Food waste and its proper management pose significant challenges in supply chain network management. This study proposes a comprehensive inventory-routing model that considers the value fluctuation of products over time and uses a multi-stage stochastic programming approach. By incorporating the randomness of market demands and the impacts of each period on the next, the model enables chain stores to make informed decisions in inventory management and distribution, resulting in cost savings.
RAIRO-OPERATIONS RESEARCH
(2023)
Article
Construction & Building Technology
Mahsa Babagheibi, Ali Sahebi, Shahram Jadid, Ahad Kazemi
Summary: According to the development of CHP and HP, energy scheduling of thermal and electrical systems became more dependent on each other. New designs of Integrated Heat and Power Markets (IHPM) are proposed to use the complementary capabilities of multi-energy systems such as Energy Hubs. The proposed market structure based on the ADMM improves social welfare value and reduces operating costs.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Energy & Fuels
Hamid Karimi, Shahram Jadid
Summary: This paper proposes a day-ahead stochastic operation planning method for hybrid renewable/non-renewable multi-microgrid systems. A multi-objective tri-stage decision-making framework is utilized to optimize the operating cost, generation flexibility, and demand-side flexibility simultaneously. The proposed model considers uncertainty, cooperation, and flexibility to enhance the efficiency and capability of the multi-microgrid system.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Energy & Fuels
M. Ahmadifar, K. Benfriha, M. Shirinbayan, A. Aoussat, J. Fitoussi
Summary: This study investigates the impact of innovative polymer-metal interface treatment on the reliability and robustness of hydrogen storage technology. A scaled-down demonstrator was fabricated using rotomolding to examine the mechanical characteristics, damage, and fatigue behaviors of the metal-polymer interface. The findings reveal that sandblasting treatment enhances the resilience of the interface.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
A. A. Kandil, Mohamed M. Awad, Gamal I. Sultan, Mohamed S. Salem
Summary: This paper proposes a novel hybrid system that splits solar radiation into visible and thermal components using a beam splitter and integrates a phase change material (PCM) packed bed with a PV cell. Experimental and theoretical analyses show that the hybrid configuration significantly increases the net power output of the system compared to using a PV system alone.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Jinchao Li, Ya Xiao, Shiqiang Lu
Summary: The combination of energy storage and microgrids is crucial in addressing the uncertainty of distributed wind and solar resources. This article proposes a multi microgrid interaction system with electric-hydrogen hybrid energy storage, which optimizes the system's capacity configuration to improve its economy and reliability.
JOURNAL OF ENERGY STORAGE
(2024)
Review
Energy & Fuels
Shri Hari S. Pai, Sarvesh Kumar Pandey, E. James Jebaseelan Samuel, Jin Uk Jang, Arpan Kumar Nayak, HyukSu Han
Summary: This review discusses the structure-property relationship of nickel oxide nanostructures as excellent supercapacitive materials and provides an overview of various preparation methods and strategies to enhance specific capacitance. It comprehensively analyzes the current status, challenges, and future prospects of nickel oxide electrode materials for energy storage devices.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Xiaowei Wu, Xin Dong, Ziqin Liu, Xinyi Wang, Pu Hu, Chaoqun Shang
Summary: The growth of Li dendrites in lithium metal batteries is effectively controlled by constructing a three-dimensional framework on the surface of Li using Ni(OH)2 nanosheets modified Prussian blue tubes. This method provides a homogenous Li+ flux and sufficient space to accommodate the volume change of Li, resulting in suppressed dendrite growth and improved cycling performance.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Yan-Jie Liao, Yi-Yen Hsieh, Yi-Chun Yang, Hsing-Yu Tuan
Summary: We present two-dimensional AgInP2Se6 (AIPSe) bimetallic phosphorus trichalcogenides nanosheets as anodes for advanced alkali metal ion batteries (AMIBs). The introduction of bimetallic components enhances the electronic/ionic conductivity and optimizes the redox dynamics, resulting in superior electrochemical performance. The AIPSe@G anodes achieve high specific capacity, excellent cycle stability, and rate capability in both lithium-ion (LIBs) and potassium-ion batteries (PIBs). The comprehensive full cell tests further demonstrate the stability of AIPSe@G anodes under diverse current regimes.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Chenghu Wu, Weiwei Li, Tong Qian, Xuehua Xie, Jian Wang, Wenhu Tang, Xianfu Gong
Summary: In the context of increasing global environmental pollution and constant increase of carbon emission, hydrogen production from surplus renewable energy and hydrogen transportation using existing natural gas pipelines are effective means to mitigate renewable energy fluctuation, build a decarbonized gas network, and achieve the goal of carbon peak and carbon neutral in China. This paper proposes a quasi-steady-state modeling method of a hydrogen blended integrated electricity-gas system (HBIEGS) considering gas linepack and a sequential second-order cone programming (S-SOCP) method to solve the developed model. The results show that the proposed method improves computational efficiency by 91% compared with a general nonlinear solver.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Jingcen Zhang, Zhi Guo, Yazheng Zhu, Haifeng Zhang, Mengjie Yan, Dong Liu, Junjie Hao
Summary: In this study, a new type of sensible heat storage material was prepared using low-cost steel slag as the main component, providing an effective way of recycling steel slag. By analyzing the effects of different pretreatment steel slag content and sintering temperatures on the organization and properties of heat storage materials, the study found that the steel slag heat storage material exhibited excellent performance and stability under certain conditions.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
D. Carrillo-Pena, G. Pelaz, R. Mateos, A. Escapa
Summary: Methanogenic biocathodes have the potential to convert CO2 and electricity into methane, making them suitable for long-term electrical energy storage. They can also function as biological supercapacitors for short-term energy storage, although this aspect has received less attention. In this study, carbon-felt-based MB modified with graphene oxide were investigated for their electrical charge storage capabilities. Results showed that the potential of the electrode during discharging plays a significant role in determining the charge storage capacity.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Marco Gambini, Federica Guarnaccia, Michele Manno, Michela Vellini
Summary: This paper presents an analytical assessment of the energy-power relationship for different material-based hydrogen storage systems. It explores the impact of power demand on the amount of discharged hydrogen and the utilization factor. The results show that metal hydrides have higher specific power compared to liquid organic hydrogen carriers. The study provides insights into the discharge duration and energy utilization of hydrogen storage systems.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Shujahadeen B. Aziz, Rebar T. Abdulwahid, Pshko A. Mohammed, Srood O. Rashid, Ari A. Abdalrahman, Wrya O. Karim, Bandar A. Al-Asbahi, Abdullah A. A. Ahmed, M. F. Z. Kadir
Summary: This study investigates a novel biodegradable green polymer electrolyte for energy storage. Results show that the sample with added glycerol has the highest conductivity. The primary conduction species in the electrolyte are ions. Testing confirms that the sample can withstand a voltage suitable for practical applications.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Binit Kumar, Abhishek Awasthi, C. Suresh, Yongseok Jeon
Summary: This study presents a new numerical model for effective thermal conductivity that overcomes the limitations of previous models. The model can be applied to various shapes and phase change materials, using the same constants. By incorporating the natural convection effect, the model accurately calculates the thermal conductivity. The results of the study demonstrate the effectiveness of the model for different shapes and a wide range of alkanes.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Supak Pattaweepaiboon, Wisit Hirunpinyopas, Pawin Iamprasertkun, Katechanok Pimphor, Supacharee Roddecha, Dirayanti Dirayanti, Adisak Boonchun, Weekit Sirisaksoontorn
Summary: In this study, electrode powder from spent zinc-carbon/alkaline batteries was upcycled into LiMn2O4 cathode and carbon anode for rechargeable lithium-ion batteries. The results show that the upcycled LiMn2O4 exhibits improved electrochemical performance, with higher discharge capacity compared to pristine LiMn2O4. Additionally, the recovered carbon materials show superior cycling performance. This research provides great potential for upcycling waste battery electrodes to high-value cathode and anode materials for lithium-ion battery applications.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Pan Yang, H. D. Yang, X. B. Meng, C. R. Song, T. L. He, J. Y. Cai, Y. Y. Xie, K. K. Xu
Summary: This paper introduces a novel multi-task learning data-driven model called GBLS Booster for accurately assessing the state of health (SOH) and remaining useful life (RUL) of lithium batteries. The model combines the strengths of GBLS and the CNN-Transformers algorithm-based Booster, and the Tree-structured Parzen Estimator (TPE) algorithm is used for optimization. The study devises 10 healthy indicators (HIs) derived from readily available sensor data to capture variations in battery SOH. The random forest method (RF) is employed for feature refinement and data dimension reduction, while the complete empirical mode decomposition (CEEMDAN) method and the Pearson correlation coefficient are used for noise reduction and data point elimination in RUL prediction. The proposed model demonstrates exceptional accuracy, robustness, and generalization capabilities.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
M. Arrinda, M. Oyarbide, L. Lizaso, U. Osa, H. Macicior, H. J. Grande
Summary: This paper proposes a robust aging model generation methodology for lithium-ion batteries with any kind of lab-level aging data availability. The methodology involves four phases and ensures the robustness of the aging model through a verification process.
JOURNAL OF ENERGY STORAGE
(2024)
