Article
Energy & Fuels
Guan-Jhu Chen, Yi-Hua Liu, Yu-Shan Cheng, Hung-Yu Pai
Summary: A model predictive control-based charging algorithm is proposed in this paper, which can simultaneously consider charging time and charging temperature. Compared with the widely employed constant current-constant voltage charging method, the proposed technique can improve the charging time and the average temperature.
Article
Engineering, Electrical & Electronic
Jianwen Meng, Meiling Yue, Demba Diallo
Summary: This paper presents a nonlinear extension of MPC charge control structure for lithium-ion batteries based on a commonly used equivalent circuit model (ECM). The proposed structure adopts extended Kalman filter (EKF) for battery state estimation and reuses the Jacobian matrix obtained through first-order Taylor approximation in EKF in MPC formulation. Numerical validation shows that this method can effectively handle the nonlinear battery charging control problem and respect the battery's electrical constraints.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Xu Jin, Yehu Han, Zhengfeng Zhang, Yawei Chen, Jianming Li, Tingting Yang, Xiaoqi Wang, Wanxia Li, Xiao Han, Zelin Wang, Xiaodan Liu, Hang Jiao, Xiaoxing Ke, Manling Sui, Ruiguo Cao, Genqiang Zhang, Yongfu Tang, Pengfei Yan, Shuhong Jiao
Summary: This study reports on the exceptional fast charge/discharge performance and long-term stability of a mesoporous single-crystalline lithium titanate (MSC-LTO) microrod in lithium-ion batteries (LIBs). The microrods exhibit high rate capability and minimal structure degradation, providing a new approach for developing fast-charging materials for LIBs.
ADVANCED MATERIALS
(2022)
Review
Chemistry, Physical
Manuel Weiss, Raffael Ruess, Johannes Kasnatscheew, Yehonatan Levartovsky, Natasha Ronith Levy, Philip Minnmann, Lukas Stolz, Thomas Waldmann, Margret Wohlfahrt-Mehrens, Doron Aurbach, Martin Winter, Yair Ein-Eli, Jurgen Janek
Summary: Fast charging is essential for the economic success of electric vehicles, with lithium-ion batteries facing limitations due to the transport of lithium ions within the electrodes. Understanding these limitations is crucial for optimizing material properties for fast-charging applications.
ADVANCED ENERGY MATERIALS
(2021)
Editorial Material
Green & Sustainable Science & Technology
Christian Bauer, Simon Burkhardt, Neil P. Dasgupta, Linda Ager-Wick Ellingsen, Linda L. Gaines, Han Hao, Roland Hischier, Liangbing Hu, Yunhui Huang, Jurgen Janek, Chengdu Liang, Hong Li, Ju Li, Yangxing Li, Yi-Chun Lu, Wei Luo, Linda F. Nazar, Elsa A. Olivetti, Jens F. Peters, Jennifer L. M. Rupp, Marcel Weil, Jay F. Whitacre, Shengming Xu
Summary: Rechargeable batteries are expected to experience exponential growth in the next decade, thanks to the wider adoption of electric vehicles. An international expert panel has proposed a feasible pathway towards sustainable batteries, emphasizing the importance of vision, innovation, and practice.
NATURE SUSTAINABILITY
(2022)
Article
Energy & Fuels
Praveen Nambisan, Pankaj Saha, Munmun Khanra
Summary: In this work, a real-time optimal fast charging protocol is implemented using Pontryagin's Minimum Principle (PMP) to solve the optimal control framework balancing between charging time and ohmic heat generation. The control concepts of costate jump conditions are modified and extensive offline optimization results are used to examine the real-time optimal fast charging protocol under varying operating constraints. The effect of different boundary conditions on charging profile and sensitive parameters, as well as comparison with a standard CCCV charging algorithm, is investigated. Finally, the comparison between a typical optimal fast charging profile and a standard 2C CCCV protocol is experimentally examined.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Engineering, Electrical & Electronic
Heze You, Haifeng Dai, Lizhen Li, Xuezhe Wei, Guangshuai Han
Summary: This paper utilizes an advanced multi-factors coupling aging model and bi-objective PSO algorithm to derive the optimal low-temperature charging strategy for Lithium-ion batteries, considering both battery health and charging time objectives. The strategy achieves a desirable balance between charging speed and battery health under low-temperature charging conditions.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Chemistry, Physical
Sida Zhou, Xinhua Liu, Yang Hua, Xinan Zhou, Shichun Yang
Summary: This article introduces a coupled hybrid adaptive particle swarm optimization-hybrid simulated annealing algorithm for precise parameter identification, which is validated on three different types of batteries and shows excellent consistency between simulation results and experimental data.
JOURNAL OF POWER SOURCES
(2021)
Article
Energy & Fuels
Ran Li, Xue Wei, Hui Sun, Hao Sun, Xiaoyu Zhang
Summary: This paper proposes an optimized charging strategy for lithium-ion batteries based on an improved electric-thermal coupling model. Experimental results show that the proposed method can reduce the maximum temperature and charging time, providing a theoretical basis for safe charging of battery systems.
Article
Materials Science, Multidisciplinary
Meimei Yuan, Hongjun Liu, Fen Ran
Summary: This article highlights the key kinetically limiting factors in the fast-charging process from the perspective of cathodic materials and describes the currently reported fast-charging cathode materials with improved rapid ions diffusion capability and fast reaction kinetics. It discusses a series of strategies, including nanostructure, doping, and multiple-system, while emphasizing the importance of pseudocapacitive contribution in constructing fast-charging lithium-ion batteries and sodium-ion batteries.
Article
Electrochemistry
Yeon Tae Jeong, Hong Rim Shin, Jinhong Lee, Myung-Hyun Ryu, Sinho Choi, Hansung Kim, Kyu-Nam Jung, Jong-Won Lee
Summary: In recent years, significant efforts have been made to find a fast-charging method for lithium-ion batteries (LIBs), which can be widely used in electric vehicles. The research focuses on suppressing lithium (Li) plating on the graphite anode, as it causes capacity deterioration and safety issues under fast-charging conditions. This study presents mechanistic insights into pulse-current-based fast-charging, which effectively inhibits Li plating on the anode by redistributing Li+ species at the electrolyte/anode interface periodically.
ELECTROCHIMICA ACTA
(2023)
Article
Chemistry, Multidisciplinary
Xinyang Yue, Jing Zhang, Yongteng Dong, Yuanmao Chen, Zhangqin Shi, Xuejiao Xu, Xunlu Li, Zheng Liang
Summary: To address the issue of lithium (Li) plating on graphite anodes during fast charging, Li plating regulation and morphology control are proposed. A Li plating-reversible graphite anode is achieved through a localized high-concentration electrolyte (LHCE), resulting in high reversibility and stability. The stable LiF-rich solid electrolyte interphase (SEI) enables a higher average Coulombic efficiency (99.9%) and reversibility of Li plating (99.95%). A self-made LiNi0.5Mn0.3Co0.2O2 | graphite pouch cell exhibits a competitive capacity retention of 84.4% even at high current (7.2 A) after 150 cycles, demonstrating the potential for high-performance fast-charging batteries.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Chemistry, Physical
Masakazu Mukaida, Kazuhiro Kirihara, Teruo Ebihara, Qingshuo Wei
Summary: In this study, a gram-scale polymer-based thermoelectric module has been designed and fabricated by laminating ultrathin half-dried PEDOT/PSS films with Ni foils. The device exhibits a power density of 72 mW/cm2 at 100°C under natural cooling conditions and can fully charge a commercial Li-ion battery within 2 days. It shows excellent stability for over 2 months under continuous operation conditions. This work highlights the potential of organic thermoelectric devices for energy harvesting.
MATERIALS TODAY ENERGY
(2023)
Article
Chemistry, Physical
Weihan Li, Iskender Demir, Decheng Cao, Dominik Joest, Florian Ringbeck, Mark Junker, Dirk Uwe Sauer
Summary: This study develops a data-driven parameter identification framework for electrochemical models of lithium-ion batteries in real-world operations using artificial intelligence. The framework improves the accuracy of parameter identification and overcomes the overfitting problem caused by limited battery data.
ENERGY STORAGE MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Juan An, Hongyu Zhang, Lu Qi, Guoxing Li, Yuliang Li
Summary: This paper proposes a self-expanding lithium-ion transport channel method to construct a fast-charging anode for high-performance Li-ion batteries. By enabling self-reversible conversion of chemical bonds during cycling, the method reduces the energy barrier of Li-ion transport and allows fast Li-ion diffusion, effectively addressing issues like severe voltage polarization and Li metal plating.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)
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
Chemistry, Physical
Nan Qin, Liming Jin, Guangguang Xing, Qiang Wu, Junsheng Zheng, Cunman Zhang, Zonghai Chen, Jim P. Zheng
Summary: Developing high-capacity electrodes requires accurate evaluation of electrochemical behaviors under increasing current density. The polarization at the lithium counter electrode has become a barrier for accurate evaluation of battery electrodes. In this study, the impact of the lithium counter electrode was minimized by decoupling the electrochemical behavior of high-capacity electrodes using a single-channel three-electrode vehicle. The accurate evaluations revealed excellent rate capability and stable cycling performance of the high-capacity graphite electrode.
ADVANCED ENERGY MATERIALS
(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)
Article
Engineering, Electrical & Electronic
Hongyan Yuan, Zhendong Sun, Yujie Wang, Zonghai Chen
Summary: This study proposes a deep reinforcement learning controller (FO-DDPG) based on fusion optimization and a control optimization strategy based on net power optimization to address the coordination problem in the flow control of air and hydrogen in a proton exchange membrane fuel cell system. The experimental results demonstrate that the undecoupled FO-DDPG algorithm has a faster dynamic response and more stable static performance compared to other control algorithms.
WORLD ELECTRIC VEHICLE JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Yujie Wang, Wenhuan Li, Zeyan Liu, Ling Li
Summary: Due to continuous high traction power impact, many safety risks can occur during driving, such as aging mechanism activation, rapid deterioration of battery performance, and even thermal runaway. Hybrid energy storage, which combines batteries and ultracapacitors, is an effective solution. The energy management strategy, especially one based on reinforcement learning, plays a crucial role in optimizing efficiency and effectively managing energy in hybrid energy storage systems.
WORLD ELECTRIC VEHICLE JOURNAL
(2023)
Article
Electrochemistry
Ruilong Xu, Yujie Wang, Zonghai Chen
Summary: This paper proposes a data-driven approach for battery aging mechanism analysis and degradation pathway prediction. The dominant aging modes and critical aging factors affecting battery capacity decay are determined through statistical analysis methods. A data-driven multi-factor coupled battery aging mechanism prediction model is developed using the Transformer network and regression-based data enhancement. Experimental results show that the proposed approach achieves satisfactory performances under different aging conditions.
Article
Thermodynamics
Mince Li, Yujie Wang, Pengli Yu, Zhendong Sun, Zonghai Chen
Summary: An online adaptive energy management strategy is proposed in this paper for fuel cell hybrid vehicles to minimize hydrogen consumption and adjust the strategy according to driving conditions. Driving pattern recognition is achieved through an improved k-means clustering approach, and separate machine learning models are trained for each driving pattern to obtain energy management regression learners. Comparison experiments are conducted to determine the optimal machine learning model and input parameters. The effectiveness of the proposed energy management strategy is evaluated using two compound test driving cycles. The results show that the proposed method achieves the lowest fuel consumption compared to other algorithms, reducing hydrogen consumption by up to 5.66% when compared to commonly used methods.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Chemistry, Physical
Xiang Xiao, Li Wang, Jiantao Li, Bo Zhang, Qiao Hu, Jinli Liu, Yingqiang Wu, Jinhui Gao, Yanbin Chen, Shunlin Song, Xuequan Zhang, Zonghai Chen, Xiangming He
Summary: This study traced the structural evolution during solid-state synthesis using an in situ technique, focusing on the lithiation reaction and migration of transition metal ions. It was found that the sintering process is regulated by the competition between decomposition and lithiation reactions, which can be controlled by temperature. To maintain the layered ordering of transition metal ions throughout the synthesis process, it is desired to control the melting point and affinity of the Li sources to the cathode precursors, which simplifies the manufacturing process and improves the quality of the cathode material.
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
Yujie Wang, Xingchen Zhang, Kaiquan Li, Guanghui Zhao, Zonghai Chen
Summary: The safety of lithium-ion batteries is essential for their application and development. Research on lithium-ion battery management has been a popular topic for many years, covering various scientific and engineering issues. This paper reviews the current research progress in lithium-ion battery management systems, including battery modeling, state estimation, health prognosis, charging strategy, fault diagnosis, and thermal management methods, and provides insights and suggestions for future control and management of lithium-ion batteries.
Article
Engineering, Electrical & Electronic
Meng Xu, Shiqi Lin, Jikai Wang, Zonghai Chen
Summary: This article proposes a LiDAR SLAM system that improves the performance in complex and diverse scenarios by grouping consistent and stable geometry features for better expression of environmental properties. Stable geometry feature extraction, effective feature constraint classification, and accurate loop closure detection are implemented. Quantitative and qualitative experiments demonstrate the adaptability, accuracy, and repeatability of the method.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Chemistry, Multidisciplinary
Xiang Xiao, Li Wang, Yingqiang Wu, Youzhi Song, Zonghai Chen, Xiangming He
Summary: 'Green ambition towards sustainability' is a hot research topic of the 21st century. Lithium-ion batteries (LIBs) play a significant role in the energy revolution, but their production and disposal raise concerns about the supply of raw materials and waste management. Cathode regeneration and upcycling technologies offer solutions to repair and reuse degraded cathode materials, promoting a circular economy and upgrading battery chemistry.
ENERGY & ENVIRONMENTAL SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Shiqi Lin, Jikai Wang, Meng Xu, Hao Zhao, Zonghai Chen
Summary: In this article, a new RGB-D object-level SLAM method is proposed, which utilizes projection constraints between dense object models and their instance masks. The method addresses the challenges of modeling unstructured objects and quantifying reprojection errors. A covisibility graph is constructed to maintain a real-time local map, and a multiview bundle adjustment formulation is proposed to optimize the local map components. Experimental results demonstrate the competitive performance of the proposed method.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Thermodynamics
Xu Chen, Mince Li, Zonghai Chen
Summary: This paper proposes a meta rule-based energy management strategy (EMS) that replaces driving pattern recognition (DPR). The meta rule determines the parameters of the energy management rule. Simulation results show that the meta rule-based EMS is effective in reducing battery throughput and suitable for real-time systems.
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.