Article
Automation & Control Systems
Zhijia Huang, Luis D. Couto, Chitra Dangwal, Shujie Xiao, Wei Lv, Dong Zhang, Scott J. Moura
Summary: Lithium-sulfur (Li-S) batteries have the potential to overcome the limitations of conventional Li-ion batteries with their high theoretical specific energy density. This study proposes a model and observer design approach for state estimation of Li-S batteries, using experimental data for parameter identification and an extended Kalman filter for state estimation.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Energy & Fuels
Xin Lai, Yunfeng Huang, Xuebing Han, Huanghui Gu, Yuejiu Zheng
Summary: A novel SOE estimation method using PF and EKF algorithms is proposed in this study, which is able to improve accuracy and robustness by identifying battery model parameters at different temperatures. Experimental results show that the maximum error of the proposed algorithm is less than 3% under dynamic conditions and can quickly converge to its reference trajectory even with large initial errors in SOE and total available energy.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Peng Nian, Zhang Shuzhi, Zhang Xiongwen
Summary: An improved adaptive extended Kalman filter (IAEKF) is proposed for co-estimation of battery capacity and SOC, with enhanced temperature adaptability through polynomial relationships and forgetting factor. Verification results demonstrate high accuracy and anti-interference capability of the algorithm in FUDS testing.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Xuan Zheng, Zhuqian Zhang
Summary: In this paper, an improved thermal model for lithium batteries is proposed, and the model parameters are identified using the least-squares method. The results show that temperature is an important factor in the model, and the proposed SOC estimation method has better capability in handling temperature variation.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Maoshu Xu, E. Zhang, Sheng Wang, Yi Shen, Binchen Zou, Haomiao Li, Yiming Wan, Kangli Wang, Kai Jiang
Summary: This study proposes an ultrasonic model-based method for battery state of charge (SoC) estimation, which shows high accuracy and robustness under dynamic load profiles. Experimental results demonstrate that the ultrasonic model accurately estimates the SoC of the battery compared to the traditional voltage model.
Article
Automation & Control Systems
Yang Li, Binyu Xiong, Don Mahinda Vilathgamuwa, Zhongbao Wei, Changjun Xie, Changfu Zou
Summary: This article proposes a novel model-based estimator for the distributed electrochemical states of lithium-ion batteries. A reduced-order battery model is obtained through systematic simplifications of a high-order electrochemical-thermal coupled model, capturing local state dynamics inside the battery. The constrained ensemble Kalman filter (EnKF) based on a physics-based equivalent circuit model is designed to detect internal variables and address slow convergence issues.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Thermodynamics
Linchao Duan, Xugang Zhang, Zhigang Jiang, Qingshan Gong, Yan Wang, Xiuyi Ao
Summary: This paper proposes a second-order adaptive extended Kalman filter (AEKF) for accurately estimating the state of charge (SOC) of a lithium-ion battery. By analyzing the correlation between sliding window length (SWL) and algorithm errors, a reasonable SWL parameter value is obtained to ensure higher accuracy in SOC estimation when the working condition changes while keeping SWL unchanged. Experimental results demonstrate that the proposed second-order AEKF excels in terms of estimation accuracy and robustness.
Article
Energy & Fuels
Yuanmao Ye, Zhenpeng Li, Jingxiong Lin, Xiaolin Wang
Summary: This paper proposes a new model-based SOC estimation method for lithium-ion batteries, which integrates parameter identification and state estimation into one closed-loop algorithm. The algorithm utilizes extended stochastic gradient algorithm and adaptive extended Kalman filter for parameter identification and state estimation respectively. Experimental results demonstrate the good performance of the proposed method in terms of estimation accuracy and robustness under different test conditions, making it more suitable for online SOC estimation of lithium-ion batteries.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Himadri Sekhar Bhattacharyya, Amalendu Bikash Choudhury, Chandan Kumar Chanda
Summary: This paper focuses on the battery management system (BMS) and the calculation of state of charge (SOC) in lithium-ion batteries. By using the electrical equivalent circuit model (EECM) and algorithms such as extended Kalman filter (EKF) and dual extended Kalman filter (DEKF), a fairly accurate estimate of SOC can be obtained. The impact of voltage and current sensor bias on SOC is also investigated, and the effectiveness of the algorithms is validated under different conditions.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Energy & Fuels
Mostafa Al-Gabalawy, Nesreen S. Hosny, James A. Dawson, Ahmed Omar
Summary: A study developed a SOC estimation algorithm using extended Kalman filter (EKF) and found that the dual EKF algorithm provided the most accurate estimation for battery parameters through comparative analysis.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Materials Science, Multidisciplinary
Jialu Song, Hujin Xie, Yongmin Zhong, Jiankun Li, Chengfan Gu, Kup-Sze Choi
Summary: The paper introduces a new reduced-order nonlinear Kalman filter to emulate nonlinear behaviors of biological deformable tissues for accurate simulation of tissue physical deformation in real time. The approach reduces the order of the nonlinear state-space equation to decrease computational cost, constructing an extended Kalman filter to calculate tissue physical deformation behaviors online. Simulation results and comparison analysis verify the effectiveness of the proposed method.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2022)
Article
Chemistry, Physical
F. F. Oehler, K. Nuernberger, J. Sturm, A. Jossen
Summary: Accurate knowledge of the current state of lithium-ion battery cells is crucial for enhanced operational management of battery electric vehicles. This study demonstrates the fast and robust performance of online state estimation using an efficient implementation of a popular pseudo-two-dimensional electrochemical model and a nonlinear filtering algorithm.
JOURNAL OF POWER SOURCES
(2022)
Article
Engineering, Electrical & Electronic
Zhongwei Deng, Xiaosong Hu, Xianke Lin, Le Xu, Jiacheng Li, Wenchao Guo
Summary: The study applied model reduction methods to obtain a reduced-order model for all-solid-state batteries, allowing for fast calculation of internal electrochemical information and achieving higher performance and a better tradeoff.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2021)
Article
Energy & Fuels
Minseok Song, Song-Yul Choe
Summary: The study conducted a sensitivity analysis of a reduced-order electrochemical-thermal model to investigate the influence of physical parameters on heat generation rate of lithium-ion batteries. Parameters were clustered into three groups and identified based on dominant ranges of state of charge, leading to convergence within an optimal solution. The model with identified parameters was validated against experimental data, showing good agreement.
Article
Automation & Control Systems
Yang Li, Zhongbao Wei, Binyu Xiong, D. Mahinda Vilathgamuwa
Summary: This article proposes a computationally efficient state estimation method for lithium-ion batteries based on a degradation-conscious high-fidelity electrochemical-thermal model. The algorithm uses an ensemble-based state estimator with the singular evolutive interpolated Kalman filter (SEIKF) to ease the computational burden caused by the nonlinear nature of the battery model. Unlike existing schemes, the proposed algorithm ensures mass conservation without additional constraints, simplifying the tuning process and improving convergence speed. The proposed scheme addresses model uncertainty and measurement errors through adaptive adjustment of the SEIKF's error covariance matrices. Comparisons with well-established nonlinear estimation techniques show that the adaptive ensemble-based Li-ion battery state estimator provides excellent performance in terms of accuracy, computational speed, and robustness.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Guodong Fan, Xiaoyu Li, Marcello Canova
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2018)
Article
Environmental Sciences
Jiazhong Qian, Qiaoying Chu, Ruigang Zhang, Yong Liu, Wenhua Wan
Article
Chemistry, Physical
Guodong Fan
JOURNAL OF POWER SOURCES
(2020)
Article
Energy & Fuels
Dun Wu, MeiChen Wang, Guangqing Hu, Ruigang Zhang, Zhendong Yang, Shuqin Li
Summary: The study found that the surface soil and dust around the industrial site are lower than the national standard (GB 15618-2008), with high concentration of Cr in the raw ore being a potential pollution source. The potential ecological hazard coefficient of the four heavy metals in the study area basically followed the order of Cd>As>Pb>Cr.
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
(2021)
Article
Electrochemistry
Dongliang Lu, M. Scott Trimboli, Guodong Fan, Ruigang Zhang, Gregory L. Plett
Summary: This paper discusses five methods to estimate the electrode OCP relationships for lithium-ion battery cells, utilizing a physics-based thermodynamic model to overcome data missing and inaccessible lithium issues. These methods are also applied to estimate the full-cell OCV function and determine the operating boundaries of the electrodes.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2021)
Article
Electrochemistry
Dongliang Lu, M. Scott Trimboli, Guodong Fan, Ruigang Zhang, Gregory L. Plett
Summary: This paper discusses physics-based electrochemical models of lithium-ion cells and compares five different approaches to solving the electrode open-circuit potential relationships through experimental data. These methods are able to accommodate different cell chemistries and be utilized in real-time battery management systems.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2021)
Article
Electrochemistry
Dongliang Lu, M. Scott Trimboli, Guodong Fan, Ruigang Zhang, Gregory L. Plett
Summary: Battery-management systems rely on mathematical models to estimate battery states. Physics-based models offer advantages over empirical models, but determining parameter values can be challenging. This paper proposes a method to identify a subset of physics-based model parameter values without the need for cell teardown, making it accessible for battery labs and applications.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2021)
Article
Environmental Sciences
Lei Ma, Chao Zhang, Siyuan Liu, Qiankun Luo, Ruigang Zhang, Jiazhong Qian
Summary: In this study, the sensitivity analysis of the factors affecting the removal efficiency of permeable reactive barrier (PRB) was conducted. Through simulation experiments and numerical simulations, the influence of different factors on PRB removal efficiency was analyzed. The results showed that the sensitivity ranking of factors varied in different permeability and dispersity conditions, and the study also identified some key factors that affect the removal efficiency.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Xuebo Hu, Ruigang Zhang, Bing Xia, Rongrong Ying, Zhewei Hu, Xu Tao, Hao Yu, Fabao Xiao, Qiaoying Chu, Hongfeng Chen, Jiazhong Qian
Summary: Pyrolysis temperature has a significant impact on the properties of biochar, which in turn affects the adsorption of heavy metal ions. Comparing biochars from the pyrolysis of maize straw and wheat straw, it was found that the biochar produced at 400 degrees C from maize straw showed the best physical and chemical properties, as well as a higher adsorption rate and capacity. The adsorption mechanisms involve surface precipitation of carbonates and phosphates, as well as complexation with oxygenated functional groups and delocalized pi electrons.
Article
Energy & Fuels
Guodong Fan, Xi Zhang
Summary: In this work, a new battery capacity estimation approach using relaxation voltage data is proposed. A correlation is identified between the relaxation voltage and battery capacity, and a convolutional neural network model is developed to estimate capacity for batteries with different degradation paths. The model shows high predictive power with a low average test error of 1.8%. The method also has the potential to work for batteries with different chemistries.
Article
Chemistry, Physical
Guodong Fan, Dongliang Lu, M. Scott Trimboli, Gregory L. Plett, Chong Zhu, Xi Zhang
Summary: In this paper, a nondestructive aging diagnostics methodology is proposed to identify aging-related parameters of a physics-based battery model from the beginning-of-life (BOL) to end-of-life (EOL). The proposed method is applied and validated on 7 cells at 4 test conditions, considering different cycling conditions, cell-to-cell variations, and calendar aging. The results show that the degradation rates of the cells are impacted by different patterns in the changes of aging parameters and the method can capture subtle cell-to-cell variations in battery degradation.
JOURNAL OF POWER SOURCES
(2023)
Article
Environmental Sciences
Ruigang Zhang, Xiaoxiang Huan, Jiazhong Qian, Yueqing Xing
Summary: The spatial distribution characteristics of macropores have a significant impact on water infiltration. The number and uniformity of macropores play a major role in soil permeability and preferential flow, while the pore size has minimal effect on water transport. Additionally, the effects of macropore number and position vary under different conditions.
Article
Environmental Sciences
Jufeng Zhang, Fengfeng Yang, Ruigang Zhang, Jiangyi He, Yadong Xie, Zaiquan Miao, Jianjiang Zhang
Summary: Gas geology is an important factor in mine safety production. This study analyzed the gas content and coal seam structure of Weijiadi Mine through experiments and concluded that there are certain distribution patterns of gas content in different coal seams and that geological structures have an impact on gas content.
FRESENIUS ENVIRONMENTAL BULLETIN
(2022)
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.