Article
Automation & Control Systems
Chong Hu, Haibo Liu, Yan Ji
Summary: This article aims to design an effective model and optimization method to describe and analyze the operating characteristics of the lithium-ion battery based on online measurement data. By exploiting the memory superiorities of the fractional-order, the fractional-order controlled autoregressive model is derived, which includes the electrochemical impedance spectroscopy and the n-RC equivalent circuit model. The approach designs a new gradient direction and fully utilizes the data from the lithium-ion battery by adding a suitable weighted factor. The experimental simulation result shows the performance of the proposed algorithms.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Chemistry, Physical
Yuejiu Zheng, Zhihe Shi, Dongxu Guo, Haifeng Dai, Xuebing Han
Summary: In this paper, a low-frequency domain equivalent circuit model (LECM) based on the principle of electrochemical impedance spectroscopy (EIS) is proposed to simplify elements in the high-frequency region, identifying model parameters using only the low-frequency region of the EIS. It addresses the issue of traditional ECM dependence on time-domain working conditions.
JOURNAL OF POWER SOURCES
(2021)
Article
Engineering, Multidisciplinary
Chun Chang, Shaojin Wang, Chen Tao, Jiuchun Jiang, Yan Jiang, Lujun Wang
Summary: Electrochemical impedance spectroscopy (EIS) is a non-invasive and information-rich measurement method for battery state analysis. Traditional equivalent circuit models (CECMs) may suffer from fitting failure and error, leading to poor estimation accuracy. In this study, a mid-frequency and low-frequency domain equivalent circuit model (MLECM) based on fusion SEI film resistance and charge transfer resistance is proposed, which achieves better parameter fitting and accuracy compared to CECMs. Furthermore, a power battery state of health (SOH) estimation method based on the improved model is introduced, demonstrating high estimation accuracy and low computational load.
Article
Energy & Fuels
Bor-Rong Chen, Yugandhar R. R. Police, Meng Li, Paramesh R. R. Chinnam, Tanvir R. R. Tanim, Eric J. J. Dufek
Summary: This article presents a quick and user-friendly data analysis algorithm as an alternative to equivalent circuit modeling (ECM) for interpreting electrochemical impedance spectroscopy (EIS) data and gaining physical insights into battery aging mechanisms. The results show that the quick-fitting approach is suitable for analyzing a series of EIS data acquired during battery cycling and identifying the underlying aging mechanisms.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Chemistry, Physical
Alan G. Li, Karthik Mayilvahanan, Alan C. West, Matthias Preindl
Summary: The DNRC model utilizes a novel physics-based diffusion component and N resistor-capacitor pairs to accurately characterize internal resistance and diffusion overpotentials of batteries in the time domain. Experimental validation shows an average absolute percent error of only 0.3% under different charge-discharge states, providing a new basis for real-time estimation and degradation reduction or diagnosis in battery management systems.
JOURNAL OF POWER SOURCES
(2021)
Article
Chemistry, Physical
Tao Li, Dingyi Wang, Haoran Wang
Summary: A new analytical method is proposed to acquire the electrochemical impedance spectra of lithium-ion batteries (LIBs) from charge/discharge curves. The method allows for fast examination in manufacturing factories and provides internal temperature monitoring and online states estimation in the battery management system (BMS). The results obtained from this method agree well with the conventional electrochemical impedance spectroscopy (EIS) method, indicating its accuracy and reliability.
JOURNAL OF POWER SOURCES
(2022)
Article
Energy & Fuels
Dezhi Li, Dongfang Yang, Liwei Li, Licheng Wang, Kai Wang
Summary: This paper proposes two methods for estimating the state of health of lithium-ion batteries, one based on an equivalent circuit model and the other based on a data-driven algorithm using convolutional neural networks and bidirectional long short-term memory. Experimental results show that both methods significantly improve the accuracy and precision of state of health estimation.
Article
Electrochemistry
Kamala Kumari Duru, Praneash Venkatachalam, Chanakya Karra, Asha Anish Madhavan, Sangaraju Sambasivam, Sujith Kalluri
Summary: In this paper, an advanced approach using the Cuckoo Search optimization Algorithm (CSA) is presented for the estimation of battery model parameters in Lithium-Ion Batteries (LIB) for Electric Vehicle (EV) applications. Experimental data is utilized to determine the parameters and their correlation with OCV and SOC. The results demonstrate that the suggested approach is efficient and resilient for parameter estimation in LIBs.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2022)
Article
Chemistry, Physical
Ming-Ying Zhou, Jian-Bang Zhang, Chi-Jyun Ko, Kuo-Ching Chen
Summary: In this study, a time-saving approach for measuring the open-circuit voltage (OCV) of a battery is proposed. By using a simplified first-order RC circuit model, the OCV at each state of charge (SOC) can be computed without the need for complete voltage relaxation information. Experimental results demonstrate that this approach significantly reduces the measurement time (usually less than 6 minutes) while maintaining high accuracy (usually less than 3 mV) compared to traditional methods.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
Lin Wang, Xiaowei Zhao, Zhongwei Deng, Lin Yang
Summary: This paper focuses on the accurate estimation of State of Charge (SoC) for electric vehicles and hybrid electric vehicles. A new model updating strategy based on electrochemical impedance spectroscopy (EIS) is proposed, which effectively enhances the SoC estimation accuracy by modifying model parameters and capacity according to the change rate of ohmic impedance.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Liping Chen, Xinyuan Bao, Antonio M. Lopes, Changcheng Xu, Xiaobo Wu, Huifang Kong, Suoliang Ge, Jie Huang
Summary: This paper proposes a new approach that integrates the equivalent circuit model (ECM) and data-driven methods for estimating the state of health (SOH) of lithium-ion batteries (LIBs). By identifying the internal resistance of the ECM using an optimization algorithm and using an optimized neural network to predict the SOH, the proposed method demonstrates fast convergence, high accuracy, and good generalization capability.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Mathematics, Applied
Liping Chen, Wenliang Guo, Antonio M. Lopes, Ranchao Wu, Penghua Li, Lisheng Yin
Summary: This paper presents a new method for estimating the state-of-charge (SOC) of lithium-ion batteries (LIBs) using incommensurate fractional-order (FO) observer. The method includes constructing a FO RC equivalent circuit model, identifying the model parameters using an adaptive FO particle swarm optimization algorithm, and designing an order-dependent incommensurate FO observer for SOC estimation. The proposed SOC observer is validated using real-time experimental data of LIBs.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Chemistry, Applied
Rui Xiong, Jinpeng Tian, Weixiang Shen, Jiahuan Lu, Fengchun Sun
Summary: This study proposes a convolutional neural network (CNN) based method for accurate battery capacity estimation using only raw impedance spectra as input. An input reconstruction module is designed to effectively utilize impedance spectra without corresponding capacities, reducing the cost of collecting training data. The proposed method outperforms supervised benchmarks, even with fewer samples with measured capacities, and can reduce the root mean square error by up to 50.66%.
JOURNAL OF ENERGY CHEMISTRY
(2023)
Article
Chemistry, Analytical
Yoshitaka Inui, Satoshi Hirayama, Tadashi Tanaka
Summary: This article examines a time domain measurement technique using a preset equivalent circuit model to measure the electro-chemical impedance spectrum of a lithium-ion battery. It focuses on excluding the apparent impedances from open circuit voltage change in the low frequency range. The article discusses the experimental study to determine the suitable applied signal conditions, measures impedance spectra under various conditions, and investigates the characteristics of the solid state diffusion processes of lithium in the corresponding low frequency range.
JOURNAL OF ELECTROANALYTICAL CHEMISTRY
(2023)
Review
Energy & Fuels
Ming Zhang, Yanshuo Liu, Dezhi Li, Xiaoli Cui, Licheng Wang, Liwei Li, Kai Wang
Summary: With the increasing application scope and scale of lithium-ion batteries, real-time and accurate monitoring of its state of health plays an important role in ensuring the healthy and stable operation of an energy storage system. Recently, electrochemical impedance spectroscopy has been developed to estimate the state of health quickly and accurately online by measuring battery impedance in a wide frequency range. This paper summarizes the latest impedance spectroscopy measurement technology and its application in estimating the health state of lithium-ion batteries, filling the gap in this aspect and contributing to the further development of this technology.
Article
Energy & Fuels
Arpit Maheshwari, Nikolaos G. Paterakis, Massimo Santarelli, Madeleine Gibescu
Article
Energy & Fuels
Nikolaos Wassiliadis, Manuel Ank, Leo Wildfeuer, Michael K. Kick, Markus Lienkamp
Summary: This article evaluates the impact of ECR on battery cell behavior through high charging rate experiments, finding that high ECRs could have negative effects on battery cells and influence conclusions drawn from cycle life tests.
Article
Energy & Fuels
Leo Wildfeuer, Nikolaos Wassiliadis, Alexander Karger, Fabian Bauer, Markus Lienkamp
Summary: In this study, a commercially available lithium-ion cell was analyzed through tear-down analysis and computed tomography scans. The electrochemical properties of the anode and cathode were examined using mini pouch half cells, and detailed insights into the kinetics of the cell were obtained. A comprehensive open-source dataset of the investigated cell was provided, fostering research in advanced models and algorithms for lithium-ion batteries.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Alexander Karger, Leo Wildfeuer, Deniz Ayguel, Arpit Maheshwari, Jan P. Singer, Andreas Jossen
Summary: This study investigates the modeling methods for capacity fade in lithium-ion batteries during dynamic cyclic aging tests. The results show that the CAP-method accurately models the capacity fade when considering dynamic conditions, while the CCT-method is more accurate in modeling capacity gradient when there is a large difference between actual and reference charge-throughput. The CAP-method assumes path independence through history independence, and the relatively low capacity fade error suggests that capacity fade behaves path-independently in the dynamic cyclic aging tests.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Chemistry, Physical
Leo Wildfeuer, Alexander Karger, Deniz Ayguel, Nikolaos Wassiliadis, Andreas Jossen, Markus Lienkamp
Summary: In this study, the aging behavior of commercial lithium-ion cells with silicon-doped graphite anodes and nickel-rich NCA cathodes is analyzed. The cells are aged under different calendar and cycle aging conditions. The study reveals that the check-up procedure significantly increases the aging observed after a certain period of time, indicating that the lifetime of lithium-ion batteries may have been underestimated in previous studies. The influence of temperature, state of charge (SOC), and depth-of-discharge on both calendar and cycle aging is also investigated.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
Julius Schmitt, Mathias Rehm, Alexander Karger, Andreas Jossen
Summary: This study demonstrates a method of using reconstructed open circuit voltage (OCV) curves to analyze the partial charging curves of a commercial lithium-ion cell, providing valuable information about degradation modes and remaining cell capacity. Accurate OCV reconstruction and degradation mode estimation can be achieved when a state of charge (SOC) window between 20% and 70% is available. The method is also applicable to charging curves at higher current rates by considering an additional overpotential.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Electrochemistry
Leo Wildfeuer, Philipp Gieler, Alexander Karger
Summary: This research proposes a method to combine time-domain and frequency-domain measurement data for parameterization of RC elements by exploiting the full potential of the distribution of relaxation times (DRT). This approach not only overcomes the limitations of traditional algorithms, but also directly determines the parameters of RC elements.
Article
Energy & Fuels
Leo Wildfeuer, Markus Lienkamp
Summary: Parameter variations of lithium-ion batteries can reduce battery pack performance, with impedance changes potentially linked to imperfect measurement setup. Experimental findings suggest that parameter variations are greatly influenced by temporal and spatial temperature inhomogeneities, and compensating for these effects can significantly reduce resistance variation.
Article
Electrochemistry
Tanja Gewald, Adrian Candussio, Leo Wildfeuer, Dirk Lehmkuhl, Alexander Hahn, Markus Lienkamp
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)