Article
Energy & Fuels
Shun-Li Wang, Xin Xiong, Chuan-Yun Zou, Lei Chen, Cong Jiang, Yan-Xin Xie, Daniel-Ioan Stroe
Summary: The traditional CC method is no longer suitable for complex working conditions, and the improved method can achieve accurate SOC estimation by considering various influencing factors. Experimental results show that the improved CC method can effectively deal with complex working conditions, and the comprehensive estimation accuracy of SOC is within 3.6%.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Energy & Fuels
Jie Gao, Liangheng Zhang, Yan Lyu, Fan Shi, Bin Wu, Cunfu He
Summary: This study presents an analytical acoustic model to investigate the interaction between the state of charge (SOC) of lithium-ion battery and the propagation characteristics of ultrasonic guided waves. The model considers the multi-layered porous structure of the battery and uses the Biot theory and transfer matrix method to construct a theoretical model. The results show a strong correlation between the shifts in the group velocity of guided wave A0 mode and the SOC of the battery, and the proposed method is validated by experimental data.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Nanoscience & Nanotechnology
Chunli Liu, Dezhi Li, Licheng Wang, Liwei Li, Kai Wang
Summary: In this study, a temporal convolutional network is used to predict the remaining useful life of supercapacitors. The model's stability and accuracy were verified by using residual blocks, early stopping technology, and the Adam algorithm for optimization. The simulation demonstrated the robustness and accuracy of the model in predicting the remaining useful life of supercapacitors.
Article
Chemistry, Physical
Jinpeng Tian, Cheng Chen, Weixiang Shen, Fengchun Sun, Rui Xiong
Summary: Accurate state of charge (SOC) is crucial for the reliable operations of lithium-ion batteries. Deep learning technique has recently emerged as a promising solution for accurate SOC estimation, especially in the era of battery big data. This article reviews the deep learning-based SOC estimation framework and the recent applications of deep learning in SOC estimation, focusing on the model structure. It also discusses advanced applications like transfer learning and the combination of deep learning with other methods. Finally, it examines the challenges and future opportunities in data collection, model development, and real-world applications in this area.
ENERGY STORAGE MATERIALS
(2023)
Review
Computer Science, Information Systems
Mohamed Elmahallawy, Tarek Elfouly, Ali Alouani, Ahmed M. M. Massoud
Summary: This paper presents various models for Li-ion batteries, discusses the factors that cause battery degradation and become unsafe, reviews estimation and prediction techniques for Li-ion battery state of health (SOH) and remaining useful life (RUL), and provides recommendations for improving Li-ion battery lifetime estimation. It is a valuable source of information for researchers in the battery community to enhance EV battery safety.
Article
Energy & Fuels
R. J. Copley, D. Cumming, Y. Wu, R. S. Dwyer-Joyce
Summary: This study evaluates the qualities contained within an ultrasound signal response by investigating the behavior of ultrasonic waves passing through the components of a layered battery structure, providing a new method for battery state monitoring. Data analysis has identified the data comparison combination with the strongest correlation to battery charge state, guiding decisions for future use of ultrasound battery monitoring. A smart peak selection method ensures optimized measurements of battery charge state regardless of the nature of the ultrasound response.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Peng Yu, Shunli Wang, Chunmei Yu, Weihao Shi, Bowen Li
Summary: This study investigates the hysteresis behavior of ternary lithium batteries and establishes a hysteresis model to accurately characterize the OCV-SOC relationship. The model is validated using experimental data, showing a maximum error of 0.0170 V and an absolute average error of 0.0063 V. The results demonstrate that the model can accurately capture the battery hysteresis effect and has positive implications for battery condition estimation and safety management.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Jie Chen, Xinyu Rui, Hungjen Hsu, Languang Lu, Caiping Zhang, Dongsheng Ren, Li Wang, Xiangming He, Xuning Feng, Minggao Ouyang
Summary: In this paper, the thermal runaway behaviors of LiNi0.6Mn0.2Co0.2O2/graphite lithium-ion batteries under different states of charge are studied. A novel method is proposed to identify the kinetics parameters of the exothermic reactions during the thermal runaway process. A lumped thermal runaway model is established and fits well with the experimental results.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Thermodynamics
Jialu Qiao, Shunli Wang, Chunmei Yu, Xiao Yang, Carlos Fernandez
Summary: In this research, a novel dynamic migration model is proposed to better describe the dynamic characteristics of lithium-ion batteries under different aging states by adjusting battery parameters in realtime. A novel chaotic firefly-particle filtering method is proposed, which uses the behavior of fireflies in nature to simulate particle optimization and find a new optimal solution through chaotic mapping. Compared with traditional particle filtering algorithm, the proposed algorithm improves the state-of-charge and state-of-health estimation accuracy by 1.48% and 0.38% respectively under Hybrid Pulse Power Characterization condition, and by 0.67% and 0.63% respectively under Beijing bus dynamic stress test condition. The proposed battery model and algorithm are of great significance in improving the condition monitoring quality of the battery management system.
Article
Thermodynamics
Shanshan Guo, Liang Ma
Summary: This study investigates the performance of four state-of-the-art deep learning algorithms in state-of-charge estimation, evaluating their accuracy, robustness, and efficiency using experimental data.
Article
Energy & Fuels
Lingfeng Fan, Ping Wang, Ze Cheng
Summary: This paper introduces a remaining capacity prediction technique for lithium-ion batteries based on partial charging curve and health feature fusion, with a battery aging model established by Gaussian process regression. The reliability and accuracy of the proposed method are validated on six battery data sets from NASA and the University of Oxford.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Engineering, Mechanical
Junchuan Shi, Alexis Rivera, Dazhong Wu
Summary: This paper proposes a physics-informed machine learning method for accurate modeling and prediction of the remaining useful life (RUL) of Lithium-ion batteries. The method considers the impact of battery health and operating conditions on battery aging and combines a calendar and cycle aging model with an LSTM layer for modeling and prediction. Experimental results demonstrate that the proposed method can accurately model and predict the degradation behavior and RUL of Lithium-ion batteries under different operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Chemistry, Physical
Jinpeng Tian, Rui Xiong, Jiahuan Lu, Cheng Chen, Weixiang Shen
Summary: Accurate estimation of state of charge (SOC) is vital for the reliable operations of lithium-ion batteries. This study proposes a solution that incorporates domain knowledge into deep learning-based SOC estimation, resulting in improved accuracy. By decoupling voltage and current sequences, and fusing SOC estimation results from deep neural networks (DNNs) with short-term Ampere-hour predictions, the proposed method achieves significant reduction in estimation errors.
ENERGY STORAGE MATERIALS
(2022)
Article
Chemistry, Physical
Kangpei Meng, Xiaoping Chen, Wen Zhang, Wesley Chang, Jun Xu
Summary: Recently, non-invasive ultrasonic-based detection has been proven to be an accurate and efficient tool for estimating the state-of-charge (SOC) and state-of-health (SOH) of lithium-ion batteries. However, the current non-invasive methods are highly sensitive to experimental setups and conditions, resulting in unpredictable and unstable results. A new approach using quantified change of ultrasonic damping has been discovered to correlate with the SOC of batteries, providing a more fundamental understanding of wave propagation.
JOURNAL OF POWER SOURCES
(2022)
Article
Energy & Fuels
Zhongbao Wei, Jian Hu, Yang Li, Hongwen He, Weihan Li, Dirk Uwe Sauer
Summary: This paper proposes a hierarchical soft measurement framework for accurate estimation of SOC and load current in electric vehicles, even without using current measurements. Simulation and experimental results show that the framework can achieve high-fidelity co-estimation even in scenarios of noise corruption and current sensor malfunction.
Article
Materials Science, Multidisciplinary
Zhiming Liang, Tianyi Li, Holden Chi, Joseph Ziegelbauer, Kai Sun, Ming Wang, Wei Zhang, Tuo Liu, Yang-Tse Cheng, Zonghai Chen, Xiaohong Gayden, Chunmei Ban
Summary: This work presents a new manufacturing method using a nonthermal plasma to create inter-particle binding without using any polymeric binding materials, enabling solvent-free manufacturing electrodes with any electrochemistry of choice. The cold-plasma-coating technique enables fabricating electrodes with thickness (>200 mu m), high mass loading (>30 mg cm(-2)), high peel strength, and the ability to print lithium-ion batteries in an arbitrary geometry.
ENERGY & ENVIRONMENTAL MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Jikai Wang, Meng Xu, Guangpu Zhao, Zonghai Chen
Summary: In this article, a novel 3-D LiDAR SLAM method is proposed, which combines feature-based fast scan matching, distribution-based keyframe matching, and loop closure. The proposed mechanisms effectively improve the performance of the LiDAR SLAM system and demonstrate competitive performance compared to state-of-the-art methods. The source code will be made open to serve as a new baseline for the robotic community.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Artificial Intelligence
Hao Zhao, Jikai Wang, Zonghai Chen, Shiqi Lin, Peng Bao
Summary: The paper proposes a novel data augmentation scheme called SRK-Augment, which utilizes self-deformation data and class activation map to achieve region-level removal and improve the generalization of deep learning models.
NEURAL PROCESSING LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Mince Li, Li Wang, Yujie Wang, Xu Chen, Zonghai Chen
Summary: This article proposes a co-estimation framework for the state-of-charge (SoC) and remaining discharging time (RDT) of the hybrid energy storage system (HESS) based on fractional-order theory. The framework includes the establishment of fractional-order models (FOMs) using electrochemical impedance spectroscopy (EIS), parameter identification using grey wolf optimizer (GWO), SoC estimation using fractional extended Kalman filter (FEKF), and validation using experimental data. The results show high precision and fast convergence rate of the proposed co-estimation method under typical working conditions.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Review
Chemistry, Multidisciplinary
Longfei Han, Li Wang, Zonghai Chen, Yongchun Kan, Yuan Hu, Hao Zhang, Xiangming He
Summary: Lithium-ion batteries, known for their portability, high energy density, and reusability, are widely used but they can leak, burn, or explode under extreme conditions. Researchers propose using solid electrolytes to improve the safety of lithium-ion batteries, but even polymer electrolytes can decompose and burn. Furthermore, the uneven charge distribution on the lithium metal anode leads to the formation of lithium dendrites, causing potential short circuits and thermal runaway. This review summarizes the thermal runaway mechanism, discusses battery abuse test standards, reviews recent works on high-safety polymer electrolytes, and considers solution strategies for lithium anode problems in polymer batteries, aiming to prospect the development of safe polymer solid lithium batteries.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Hao Zhao, Jikai Wang, Zonghai Chen, Shiqi Lin, Peng Bao, Meng Xu
Summary: Data augmentation effectively reduces overfitting in CNN-based models, especially with limited datasets. This paper proposes a novel data augmentation scheme called Interpretability-Mask (IM), which leverages the interpretability of the classifier to identify discriminative regions and preserve label consistency. By constructing a set-based representation using superpixel segmentation and the LIME operator, the IM scheme synthesizes region-level augmented samples while maintaining consistency with the original labels. Extensive experiments demonstrate the effectiveness and generality of the proposed method, achieving significant improvements in classification performance.
SIGNAL IMAGE AND VIDEO PROCESSING
(2023)
Article
Energy & Fuels
Li Wang, Zonghai Chen, Yan Liu, Yuan Li, Hao Zhang, Xiangming He
Summary: The safety concerns of lithium-ion batteries (LIBs) have hindered their widespread application in electric vehicles and stationary energy storage. Solid-state lithium batteries with nonflammable electrolytes have been proposed as a potential solution for better safety. However, the safety of solid-state lithium metal batteries (SS-LMBs) remains uncertain. This review summarizes recent investigations on the safety concerns of SS-LMBs and provides a systematic analysis and discussion.
Article
Automation & Control Systems
Yujie Wang, Kaiquan Li, Pei Peng, Zonghai Chen
Summary: In this study, multiple candidate health indicators are extracted from the peaks and valleys of the partial incremental capacity curves and screened first. The deep belief network is fine-tuned using particle swarm optimization and compared with three classical deep networks in terms of error and time consumption. Three datasets of LiFePO4 cells under different discharge depths are used to verify the proposed framework. The experimental results show that the presented framework is feasible and the prediction error can be minimized to less than 2%.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Zhenkun Zhu, Jikai Wang, Meng Xu, Zonghai Chen
Summary: Image matching task and SLAM systems both rely on feature points for pixel association. This article proposes a training strategy based on the operating mode of SLAM systems, which enables the feature extraction network to better adapt to SLAM for pose estimation and mapping. The proposed method shows improved performance on both the matching task and integrated SLAM system, and can be easily applied to other image matching networks, narrowing the gaps between matching tasks and SLAM systems.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Energy & Fuels
Ruilong Xu, Yujie Wang, Zonghai Chen
Summary: This paper proposes a hybrid battery health prediction method that combines Transformer and online correction models. It accurately predicts the battery health by establishing a nonlinear relationship between measured data and capacity decline. By considering multi-scale health features and reducing feature dimensions, this method achieves optimal prediction performance for batteries under different aging conditions.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Xin Xiong, Yujie Wang, Kaiquan Li, Zonghai Chen
Summary: This paper proposes a method for state of health (SOH) estimation using random charging data. The missing charging data is accurately reconstructed by the Gaussian Process Regression (GPR) model. The Long-Short-Term Memory (LSTM) estimation model is used to select the charging time sequence as input, avoiding complex feature extraction. Experimental results show high accuracy in laboratory and real-world datasets.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Zhendong Sun, Yujie Wang, Zonghai Chen
Summary: This paper proposes a coordination model predictive control strategy based on velocity prediction to improve the efficiency of fuel cell systems. The impact of load current, temperature, and oxygen excess ratio on efficiency is analyzed to obtain the optimal control reference. The future velocity information is predicted using the long short term memory algorithm and integrated into the disturbance sequences.
Article
Engineering, Civil
Peng Bao, Zonghai Chen, Jikai Wang, Deyun Dai, Hao Zhao
Summary: Accurate trajectory prediction is crucial for reliable autonomous driving. This paper proposes a divergence measurement method and a lifelong vehicle trajectory prediction framework based on generative replay. The framework includes a conditional generation model and a vehicle trajectory prediction model, which can adapt to changing traffic circumstances and alleviate catastrophic forgetting.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Chemistry, Physical
Tianyu Chen, Zhibin Lu, Guangjin Zeng, Yongmin Xie, Jie Xiao, Zhifeng Xu
Summary: The study introduces a high-performance LSGM electrolyte-supported tubular DC-SOFC stack for portable applications, which shows great potential in developing into high-performing, efficient, and environmentally friendly portable power sources for distributed applications.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Wenbin Tong, Yili Chen, Shijie Gong, Shaokun Zhu, Jie Tian, Jiaqian Qin, Wenyong Chen, Shuanghong Chen
Summary: In this study, a three-dimensional porous NiO interface layer with enhanced anode dynamics is fabricated, forming a Schottky contact with the zinc substrate, allowing rapid and uniform zinc plating both inside and below the interface layer. The resulting NiO@Zn exhibits exceptional stability and high capacity retention.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Yafeng Bai, Kaidi Li, Liying Wang, Yang Gao, Xuesong Li, Xijia Yang, Wei Lu
Summary: In this study, a flexible zinc ion supercapacitor with gel electrolytes, porous alpha-MnO2@reduced graphene oxide cathode, and activated carbon/carbon cloth anode was developed. The device exhibits excellent electrochemical performance and stability, even at low temperatures, with a high cycle retention rate after 5000 cycles.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Anmol Jnawali, Matt D. R. Kok, Francesco Iacoviello, Daniel J. L. Brett, Paul R. Shearing
Summary: This article presents the results of a systematic study on the electrochemical performance and mechanical changes in two types of commercial batteries with different anode chemistry. The study reveals that the swelling of anode layers in batteries with silicon-based components causes deformations in the jelly roll structure, but the presence of a small percentage of silicon does not significantly impact the cycling performance of the cells within the relevant state-of-health range for electric vehicles (EVs). The research suggests that there is room for improving the cell capacities by increasing the silicon loading in composite anodes to meet the increasing demands on EVs.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Yohandys A. Zulueta, My Phuong Pham-Ho, Minh Tho Nguyen
Summary: Advanced atomistic simulations were used to study ion transport in the Na- and K-doped lithium disilicate Li2Si2O5. The results showed that Na and K doping significantly enhanced Li ion diffusion and conduction in the material.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Zongying Han, Hui Dong, Yanru Yang, Hao Yu, Zhibin Yang
Summary: An efficient phase inversion-impregnation approach is developed to fabricate BaO-decorated Ni8 mol% YSZ anode-supported tubular solid oxide fuel cells (SOFCs) with anti-coking properties. BaO nanoislands are successfully introduced inside the Ni-YSZ anode, leading to higher peak power densities and improved stability in methane fuel. Density functional theory calculations suggest that the loading of BaO nanoislands facilitates carbon elimination by capturing and dissociating H2O molecules to generate OH.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Suresh Mamidi, Dan Na, Baeksang Yoon, Henu Sharma, Anil D. Pathak, Kisor Kumar Sahu, Dae Young Lee, Cheul-Ro Lee, Inseok Seo
Summary: Li-CO2 batteries, which utilize CO2 and have a high energy density, are hindered in practical applications due to slow kinetics and safety hazards. This study introduces a stable and highly conductive ceramic-based solid electrolyte and a metal-organic framework catalyst to improve the safety and performance of Li-CO2 batteries. The optimized Li-CO2 cell shows outstanding specific capacity and cycle life, and the post-cycling analysis reveals the degradation mechanism of the electrodes. First-principles calculations based on density functional theory are also performed to understand the interactions between the catalyst and the host electrode. This research demonstrates the potential of MOF cathode catalyst for stable operation in Li-CO2 batteries.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Ganghua Xiang, Zhihuan Qiu, Huilong Fei, Zhigang Liu, Shuangfeng Yin, Yuen Wu
Summary: In this study, a CeFeOx-supported Pt single atoms and subnanometric clusters catalyst was developed, which exhibits enhanced catalytic activity and stability for the preferential oxidation of CO in H2-rich stream through synergistic effect.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Dimitrios Chatzogiannakis, Marcus Fehse, Maria Angeles Cabanero, Natalia Romano, Ashley Black, Damien Saurel, M. Rosa Palacin, Montse Casas-Cabanas
Summary: By coupling electrochemical testing to operando synchrotron based X-ray absorption and powder diffraction experiments, blended positive electrodes consisting of LiMn2O4 spinel (LMO) and layered LiNi0.5Mn0.3Co0.2O2 (NMC) were studied to understand their redox mechanism. It was found that blending NMC with LMO can enhance energy density at high rates, with the blend containing 25% LMO showing the best performance. Testing with a special electrochemical setup revealed that the effective current load on each blend component can vary significantly from the nominal rate and also changes with SoC. Operando studies allowed monitoring of the oxidation state evolution and changes in crystal structure, in line with the expected behavior of individual components considering their electrochemical current loads.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Chiara Cementon, Daniel Dewar, Thrinathreddy Ramireddy, Michael Brennan, Alexey M. Glushenkov
Summary: This Perspective discusses the specific power and power density of lithium-ion capacitors, highlighting the fact that their power characteristics are often underestimated. Through analysis, it is found that lithium-ion capacitors can usually achieve power densities superior to electrochemical supercapacitors, making them excellent alternatives to supercapacitors.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Weihao Wang, Hao Yu, Li Ma, Youquan Zhang, Yuejiao Chen, Libao Chen, Guichao Kuang, Liangjun Zhou, Weifeng Wei
Summary: This study achieved an improved electrolyte with excellent low-temperature and high-voltage performance by regulating the Li+ solvation structure and highly concentrating it. The electrolyte exhibited outstanding oxidation potential and high ionic conductivity under low temperature and high voltage conditions, providing a promising approach for the practical application of high-voltage LIBs.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Martin Bures, Dan Gotz, Jiri Charvat, Milos Svoboda, Jaromir Pocedic, Juraj Kosek, Alexandr Zubov, Petr Mazur
Summary: Vanadium redox flow battery is a promising energy storage solution with long-term durability, non-flammability, and high overall efficiency. Researchers have developed a mathematical model to simulate the charge-discharge cycling of the battery, and found that hydraulic connection of electrolyte tanks is the most effective strategy to reduce capacity losses, achieving a 69% reduction.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
M. Rodriguez-Gomez, J. Campo, A. Orera, F. de La Fuente, J. Valenciano, H. Fricke, D. S. Hussey, Y. Chen, D. Yu, K. An, A. Larrea
Summary: In this study, we analysed the operando performance of industrial lead cells using neutron diffraction experiments. The experiments revealed the evolution of different phases in the positive electrode, showed significant inhomogeneity of phase distribution inside the electrode, and estimated the energy efficiency of the cells.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Jiawei Liu, Chenpeng Wang, Yue Yao, Hao Ye, Yinglong Liu, Yingli Liu, Xiaoru Xu, Zhicong Chen, Huazheng Yang, Gang Wu, Libin Lei, Chao Wang, Bo Liang
Summary: The study focuses on utilizing double conductive Ni-pads as anode collectors in micro-tubular solid oxide fuel cells. The simulation results show excellent performance and stability of DCNPs, and also highlight the potential applications in various fields.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Yang Wang, Kangjie Zhou, Lang Cui, Jiabing Mei, Shengnan Li, Le Li, Wei Fan, Longsheng Zhang, Tianxi Liu
Summary: This study presents a polyimide sandwiched separator (s-PIF) for improving the cycling stability of Li-metal batteries. The s-PIF separator exhibits superior mechanical property, electrolyte adsorption/retention and ion conductivity, and enables dendrite-free Li plating/stripping process.
JOURNAL OF POWER SOURCES
(2024)
