Article
Energy & Fuels
Ivo Horstkoetter, Philipp Gesner, Kerstin Hadler, Bernard Baeker
Summary: Understanding the degradation processes of lithium-ion cells is a current and pressing challenge, influenced by various operating conditions. Experimentation has shown that the discharge dynamics of a load profile significantly impact battery degradation, with higher current gradients resulting in larger degradation rates. This linear relationship between current gradient and degradation rate highlights the importance of considering dynamic influences in battery aging studies.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Jie Lv, Wenji Song, Ziping Feng, Yongliang Li, Yulong Ding
Summary: Deviations between batteries in series increase with the number of cycles and can impact battery pack lifetime, cost, and security. Equalization methods are important for reducing these differences, with active equalization showing better results in reducing battery capacity differences while hybrid equalization is more effective in reducing overall battery differences. Active equalization is suitable for short period charge and discharge, while hybrid equalization is more conducive to regular maintenance of the battery pack.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Chemistry, Physical
Conner Fear, Mukul Parmananda, Venkatesh Kabra, Rachel Carter, Corey T. Love, Partha P. Mukherjee
Summary: This study highlights the challenges of lithium plating and thermal inhomogeneity during rapid charging, emphasizing the impact of in-plane and inter-electrode thermal gradients on charging performance and cell degradation.
ENERGY STORAGE MATERIALS
(2021)
Article
Chemistry, Physical
Fujin Wang, Zhibin Zhao, Jiaxin Ren, Zhi Zhai, Shibin Wang, Xuefeng Chen
Summary: In this study, a transferable RUL prediction method for lithium-ion batteries is proposed. An Encoding Net is constructed to extract global degradation tendency information and cycle-consistency learning is used to align the battery degradation data. Based on aligned features, a new RUL prediction method is established. Experimental results show that the proposed method achieves high prediction accuracy and provides a new perspective for RUL prediction.
JOURNAL OF POWER SOURCES
(2022)
Article
Energy & Fuels
Jorn M. Reniers, David A. Howey
Summary: Large-scale grid-connected lithium-ion batteries are increasingly being deployed to support renewable energy roll-out. However, the impact of system design choices and ancillary system controls on long-term degradation and efficiency of these systems has rarely been considered. This study provides detailed simulation results on a 1 MWh grid battery system, showing that the variation in degradation rate of individual cells dominates the system behaviour over the lifetime. The importance of careful thermal management system control is also demonstrated, improving overall efficiency and total usable energy over time.
Article
Chemistry, Physical
Jorn M. Reniers, Grietus Mulder, David A. Howey
Summary: Lithium-ion batteries are increasingly used in liberalized electricity systems driven by economic optimization. A physics-based degradation model can decrease battery degradation and increase revenue. The approach increases battery lifetime in terms of years and cycles, while also improving revenue potential.
JOURNAL OF POWER SOURCES
(2021)
Article
Computer Science, Interdisciplinary Applications
Simone Barcellona, Luigi Piegari
Summary: A proposed integrated electro-thermal model can predict the thermal behavior of a battery cell based on its current and ambient conditions. The model was tuned and validated with experimental results, showing sufficient precision to predict battery temperature with acceptable accuracy considering its low complexity.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2021)
Article
Mathematics
Nikita V. Martyushev, Boris V. Malozyomov, Svetlana N. Sorokova, Egor A. Efremenkov, Mengxu Qi
Summary: This paper developed a simulation model to determine the range of an electric vehicle by studying the energy consumption through different driving cycles. It was found that the NEDC and JC08 cycles have similar developed speeds in urban conditions, but due to higher speeds, the NEDC cycle can cover a greater distance in equal time compared to JC08. However, the NEDC cycle has low dynamics, which is not suitable for actual urban operation.
Article
Energy & Fuels
Runjie Yang, Guoqing Yu, Zegang Wu, Tingting Lu, Tao Hu, Fengqin Liu, Hongliang Zhao
Summary: This study examines the performance of aged aluminum oxide ceramic-coated polyethylene separators (PE-Al2O3 separators) used in lithium-ion batteries. The cycling process of the batteries leads to the accumulation of degradation products on the separator surface, resulting in decreased porosity, ionic conductivity, and increased internal resistance. The mechanical properties of the separator deteriorate with higher current rates and the number of cycles. After 200 cycles at 1.5C, the tensile strength of the aged separator decreases by approximately 6.70%. The aging process also causes a decrease in wettability and an increase in the contact angle with the electrolyte.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Chemistry, Physical
Bo Keun Park, Yeon Kyeong Jeong, So Yeon Yang, Soyeon Kwon, Jin Hyeok Yang, Yong Min Kim, Ki Jae Kim
Summary: The study reveals that the nylon film of Al-Pouch is damaged by electrolyte contamination, leading to cracking and peeling, which exposes the underlying aluminum film and causes severe corrosion. This corrosion allows high levels of moisture to penetrate pouch-type LiBs, significantly impacting their long-term cycle life and reliability.
JOURNAL OF POWER SOURCES
(2021)
Article
Computer Science, Information Systems
Simone Barcellona, Silvia Colnago, Paolo Montrasio, Luigi Piegari
Summary: Lithium-ion batteries are attractive for electric vehicles but sensitive to temperature. Thermal management systems are needed to mitigate temperature issues. This paper proposes an integrated electro-thermal model to estimate the thermal behavior of each battery cell in a battery pack.
Article
Chemistry, Physical
Tanvir R. Tanim, Zhenzhen Yang, Andrew M. Colclasure, Parameswara R. Chinnam, Paul Gasper, Yulin Lin, Lei Yu, Peter J. Weddle, Jianguo Wen, Eric J. Dufek, Ira Bloom, Kandler Smith, Charles C. Dickerson, Michael C. Evans, Yifen Tsai, Alison R. Dunlop, Stephen E. Trask, Bryant J. Polzin, Andrew N. Jansen
Summary: The study found that while cathode issues are minimal in early cycling of extreme fast charging, they begin to accelerate in later life with distinct cracking identified as a fatigue mechanism. The bulk structure of cathodes remains intact, but there is particle surface reconstruction observed, which has a less pronounced effect on cathode aging compared to cracking.
ENERGY STORAGE MATERIALS
(2021)
Article
Chemistry, Physical
Weihan Li, Jue Chen, Katharina Quade, Daniel Luder, Jingyu Gong, Dirk Uwe Sauer
Summary: This paper proposes a framework for diagnosing the degradation of lithium-ion batteries by integrating field data, impedance-based modeling, and artificial intelligence. It achieves accurate and robust estimation of both capacity and power fade, as well as degradation mode analysis.
ENERGY STORAGE MATERIALS
(2022)
Article
Multidisciplinary Sciences
Youjun Han, Hongyuan Yuan, Ying Shao, Jin Li, Xuejie Huang
Summary: This study proposes a capacity prediction and process parameter optimization model for lithium-ion battery by combining the BP and PSO algorithms, aiming to solve the difficulty of determining critical control factors and threshold of control parameters in the battery manufacturing process. The BP method is used to establish a nonlinear mapping relationship between process data and grading capacity as the capacity consistency prediction model. By using the prediction model as a fitness function and combining with the PSO algorithm, an optimization model of process parameters is established. The results show that the BP method has an accurate capacity consistency prediction effect and the optimized process parameters significantly improve the capacity consistency of lithium-ion batteries. These results serve as an engineering application method to guide the selection and confirmation of process parameters at the battery design stage.
ADVANCED THEORY AND SIMULATIONS
(2023)
Article
Acoustics
Sunghyun Jie, Joonhee Kang, Seunghun Baek, Byeongyong Lee
Summary: This study investigates the influence of ultrasound on lithium-ion batteries (LIBs) and finds that ultrasound can improve charge transfer, enhance cycling stability and charging rate, and facilitate the formation of inorganic-rich solid electrolyte interphase (SEI) layer. This novel combination of ultrasound and LIBs presents a promising pathway for achieving high-performance batteries.
ULTRASONICS SONOCHEMISTRY
(2023)
Article
Chemistry, Inorganic & Nuclear
Changyan Sun, Xiao Miao, Lijun Zhang, Wenjun Li, Zhidong Chang
INORGANICA CHIMICA ACTA
(2018)
Article
Engineering, Multidisciplinary
Xia Xintao, Chang Zhen, Zhang Lijun, Yang Xiaowei
MATHEMATICAL PROBLEMS IN ENGINEERING
(2018)
Article
Chemistry, Analytical
Lijun Zhang, Changyan Sun
Article
Computer Science, Information Systems
Lijun Zhang, Zhongqiang Mu, Changyan Sun
Review
Computer Science, Information Systems
Zachary Bosire Omariba, Lijun Zhang, Dongbai Sun
Article
Energy & Fuels
Lijun Zhang, Kai Liu, Yufeng Wang, Zachary Bosire Omariba
Article
Energy & Fuels
Lijun Zhang, Zhongqiang Mu, Xiangyu Gao
Article
Computer Science, Artificial Intelligence
Zhiguo Liang, Lijun Zhang, Xizhe Wang
Summary: A novel clustering fault diagnosis method for steam turbines based on t-distribution stochastic neighborhood embedding (t-SNE) and extreme gradient boosting (XGBoost) is proposed in this paper. The method can identify faults in advance, reduce losses for thermal plants, and achieve an overall accuracy of 97% and an early warning of at least two hours in advance. Experimental results show that this method can effectively evaluate the condition and provide fault warning for power plant equipment.
Article
Electrochemistry
Lijun Zhang, Tuo Ji, Shihao Yu, Guanchen Liu
Summary: The deterioration of lithium-ion battery health leads to reduced performance, capacity, and lifespan, as well as decreased driving range and safety risks for electric vehicles. This paper proposes a mechanism and factors for battery degradation to address the limitations of traditional battery management systems in accurately managing and predicting health conditions. It establishes a long short-term memory (LSTM) model to predict battery capacity degradation, detecting and extracting patterns from time series. Experimental results from NASA and CALCE battery life datasets demonstrate the accurate prediction of available capacity and remaining useful life (RUL) using the LSTM model.
Article
Computer Science, Information Systems
Pinghu Xu, Lijun Zhang
Summary: This paper proposes a fault diagnosis method for rolling bearings based on the 1D-vision transformer (1D-ViT) encoder structure, which applies the vision transformer (ViT) model to the fault diagnosis area. The end-to-end fault diagnosis can be achieved by inputting the original one-dimensional acquired data without additional time-frequency domain conversion. The 1D-ViT model has demonstrated significant advantages in fault diagnosis accuracy, time complexity, space complexity, and noise-resistance performance compared to common classification models.
Article
Engineering, Electrical & Electronic
Guanchen Liu, Lijun Zhang
Summary: A three-dimensional electrochemical-thermal flow coupling model for lithium-ion batteries was established using COMSOL Multiphysics software, exploring the thermal characteristics of lithium-ion batteries for electric vehicles and discovering factors affecting the temperature rise rate.
WORLD ELECTRIC VEHICLE JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Zachary Bosire Omariba, Lijun Zhang, Hanwen Kang, Dongbai Sun
WORLD ELECTRIC VEHICLE JOURNAL
(2020)
Review
Computer Science, Information Systems
Zachary Bosire Omariba, Lijun Zhang, Dongbai Sun
Article
Computer Science, Information Systems
Lijun Zhang, Kai Liu, Jian Liu
Article
Computer Science, Artificial Intelligence
Lijun Zhang, Junyu Tao
