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
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
Fang Liu, Yan-peng Liu, Wei-xing Su, Chang-ping Jiao, Yang Liu
Summary: This study proposed an SOH estimation framework that can automatically correct errors caused by battery consistency, providing accurate estimation of battery health status during electric vehicle charging and discharging. By introducing an equivalent circuit based on the AR model, the complexity of the method was reduced while maintaining estimation accuracy. Comparing with traditional external feature relationship methods, this framework achieves better practicality and higher estimation accuracy in estimating lithium-ion battery SOH during discharge.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Energy & Fuels
Elisa Braco, Idoia San Martin, Pablo Sanchis, Alfredo Ursua
Summary: This study proposes a novel fast characterization method to estimate the capacity and internal resistance of second-life Li-ion batteries during the repurposing stage. The method is validated with satisfactory results and reduces testing time and energy consumption, contributing to the reduction of repurposing procedures and costs.
Article
Energy & Fuels
Fan Yang, Dongliang Shi, Kwok-ho Lam
Summary: With the popularization of electric vehicles, accurate estimation of voltage and state-of-charge (SOC) for rechargeable batteries becomes crucial. Traditional extended Kalman Filtering algorithms suffer from limitations in SOC and voltage estimations. This study proposes a modified extended Kalman filtering (MEKF) algorithm to improve the estimation accuracy of voltage and SOC through real-time parameter adjustment and error reduction.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Prashant Shrivastava, Tey Kok Soon, Mohd Yamani Idna Bin Idris, Saad Mekhilef, Syed Bahari Ramadzan Syed Adnan
Summary: In this work, a highly accurate and computationally efficient model-based battery states estimation method is proposed. It can concurrently estimate different battery states and has been validated with experimental results for accuracy and computational efficiency.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Energy & Fuels
Zhiyong Zhang, Li Jiang, Liuzhu Zhang, Caixia Huang
Summary: The proposed improved adaptive EKF (IAEKF) SOC estimation method accurately estimates SOC under complex driven conditions, and demonstrates strong robustness to the uncertainty of model parameters and the initial value of the noise covariance matrix.
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
Nan Zhou, Hong Liang, Jing Cui, Zeyu Chen, Zhiyuan Fang
Summary: This study presents an online estimation method of battery SOC based on EKF and NN, establishing a battery model and improving estimation accuracy in low SOC area with experimental results.
FRONTIERS IN ENERGY RESEARCH
(2021)
Article
Energy & Fuels
Prashant Shrivastava, Tey Kok Soon, Mohd Yamani Idna Bin Idris, Saad Mekhilef, Syed Bahari Ramadzan Syed Adnan
Summary: This study proposes a comprehensive co-estimation method for battery states, maximum available capacity, and maximum available energy, utilizing the correlation between different battery states to achieve high accuracy and reduce computational burden. The method is validated on two different chemistry battery cells under dynamic load profiles at different operating temperatures, and shows superior accuracy compared to existing methods.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Thermodynamics
A. Maheshwari, S. Nageswari
Summary: This paper focuses on the estimation of the battery's State of Charge (SOC) in a battery management system, proposing an optimization algorithm based on EKF and SFO to improve estimation accuracy and convergence speed.
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
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
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
Energy & Fuels
Ollie Hatherall, Mona Faraji Niri, Anup Barai, Yi Li, James Marco
Summary: This paper aims to improve the estimation accuracy of remaining discharge energy (RDE) by incorporating novel load prediction techniques with pattern recognition into the RDE calculation. The proposed method was tested and compared against other prediction-based methods, and it was shown to have desirable accuracy and robustness to modelling errors. The primary conclusion from this research was using pattern recognition can improve the accuracy of RDE estimation.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Fabian Meishner, Cem Unlubayir, Dirk Uwe Sauer
Summary: Wayside energy recovery systems (WERS) can increase energy efficiency in DC railway grids. Our work presents a novel concept for a direct grid-coupled, uncontrolled WERS based on a commercial lithium-ion-titanate-oxide (LTO) cell. Field measurements on two vehicles support the investigations.
Article
Energy & Fuels
Felix Hildenbrand, Dominik Ditscheid, Elias Barbers, Dirk Uwe Sauer
Summary: The anode overhang has a significant influence on the ageing trajectory of lithium-ion batteries. It affects the cell balancing by transferring active lithium between the anode overhang and the active anode. This study demonstrates that the anode overhang also influences the open-circuit voltage, leading to a persistent rise.
Article
Chemistry, Physical
Hendrik Pegel, Dominik Wycisk, Alexander Scheible, Luca Tendera, Arnulf Latz, Dirk Uwe Sauer
Summary: Various automobile manufacturers are using large-format cylindrical lithium-ion cells with innovative tab design for future vehicles. This study focuses on a cylindrical lithium-ion cell with a novel full-tab design and advanced cathode and anode materials for automotive high-performance applications. The internal heat path of the enhanced tab design is accurately modeled and validated, and the spatially-resolved physico-chemical model is extensively validated with experimental data. The validated model is used to investigate optimal fast-charging times and thermal management strategies for large-format cylindrical cells.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
Alexander Reiter, Susanne Lehner, Oliver Bohlen, Dirk Uwe Sauer
Summary: In recent years, digital twins for large-scale and investment-intensive Li-ion battery systems in marine and stationary applications have gained increasing interest. Considering electrical cell-to-cell variations (CtCVs) within the battery model of such a digital twin offers advantages in model-based optimization and predictive maintenance. However, existing approaches for the characterization and modeling of CtCVs are not suitable for large-scale systems. This paper presents a holistic tool chain consisting of a non-destructive method for in-situ determination of resistance and capacity distributions, parameterization of a multi-cell battery model, and simplification through multivariate statistical analysis.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Lucas Koltermann, Karl Konstantin Drenker, Mauricio Eduardo Celi Cortes, Kevin Jacque, Jan Figgener, Sebastian Zurmuehlen, Dirk Uwe Sauer
Summary: Large-scale battery energy storage systems (BESS) are already important in ancillary service markets worldwide, with batteries being suitable for applications with fast response times. However, the overall system response time of current BESS for future grid services has not been extensively studied. Measurements of a 6 MW BESS's inverters show that the response times can meet current standards even with older hardware, but hardware upgrades may be necessary for even faster future grid services.
JOURNAL OF ENERGY STORAGE
(2023)
Correction
Chemistry, Physical
Logan Ward, Susan Barbinec, Eric J. Dufek, David A. Howey, Venkatasubramanian Viswanathan, Muratahan Aykol, David A. C. Beck, Benjamin Blaiszik, Bor-Rong Chen, George Crabtree, Simon Clark, Valerio De Angelis, Philipp Dechent, Matthieu Dubarry, Erica E. Eggleton, Donal P. Finegan, Ian Foster, Chirranjeevi Balaji Gopal, Patrick K. Herring, Victor W. Hu, Noah H. Paulson, Yuliya Preger, Dirk Uwe-Sauer, Kandler Smith, Seth W. Snyder, Shashank Sripad, Tanvir R. Tanim, Linnette Teo
Article
Energy & Fuels
Hubert Maximilian Sistig, Dirk Uwe Sauer
Summary: Driven by global and local environmental concerns, public transport operators are transitioning to battery-powered electric buses. The total cost of ownership is the most crucial factor in choosing the electric bus concept. This paper analyzes the relationship between electrification and operational planning, focusing on vehicle scheduling and crew scheduling.
Article
Energy & Fuels
Alexander Epp, Sunny Rai, Finn van Ginneken, Andreas Varchmin, Juergen Koehler, Dirk Uwe Sauer
Summary: This article proposes a methodology for optimizing cooling plate topologies in the concept phase of battery system development, using a lumped-mass modeling approach and parameter preselection. It enables quick and efficient evaluation of different liquid cooling plate designs.
Article
Energy & Fuels
Philipp Dechent, Elias Barbers, Alexander Epp, Dominik Joest, Weihan Li, Dirk Uwe Sauer, Susanne Lehner
Summary: This paper presents a detailed correlation index of health indicators for lithium-ion batteries, which is important for cell selection and reducing cell-to-cell spread. The health indicators considered include impedance measurements at different pulse lengths, capacity values at different discharge procedures and checkups, weight, and initial voltage. The study is based on four different aging datasets, including variations in cell chemistry (NMC, LFP, NCA), cell type (round, prismatic), as well as size and designated application (consumer, automotive). A publicly available dataset is included for easy replication of the results.
Article
Electrochemistry
Katharina Lilith Quade, Dominik Joest, Dirk Uwe Sauer, Weihan Li
Summary: An accurate estimation of the residual energy, State of Energy (SoE), is crucial for battery diagnostics in electric vehicles. Existing literature lacks in-depth analysis and comparison of SoE estimation methods. This work provides a comprehensive understanding of SoE by discussing various definitions and estimation approaches. Two physically feasible definitions are proposed, and the practical challenges of SoE estimation are critically analyzed. Experimental evaluation highlights the underestimation of residual energy by the State of Charge, emphasizing the importance of accurate SoE estimation.
BATTERIES & SUPERCAPS
(2023)
Article
Energy & Fuels
Valentin Steininger, Peter Huesson, Katharina Rumpf, Dirk Uwe Sauer
Summary: This study aims to generate virtual customer driving data of mild-hybrid electric vehicles using automotive simulation models and stochastic customer driving profiles, in order to establish a simulation database for model training purposes and conduct lifetime simulations for new vehicles in the market. Mapping algorithms ensure a realistic representation of individual customer driving behavior. The results show significant differences in aging implications due to individual driving behavior and environmental conditions, with Asian customers exhibiting about 33% higher aging rate per driven kilometer compared to European customers during a 10-year simulation.
Article
Chemistry, Physical
David Wasylowski, Sven Neubauer, Matthias Faber, Heinrich Ditler, Morian Sonnet, Alexander Bloemeke, Philipp Dechent, Alexander Gitis, Dirk Uwe Sauer
Summary: This work presents a scalable and in-situ method for imaging the structural state of battery cells. By using ultrasound waves and processing the reflected wave instead of the transmitted one, depth information for later signal parts is obtained from time-of-flight data. An algorithm is developed to analyze the reflected ultrasound wave and calculate individual reflections from material interfaces within the electrode stack. The generated images show clear correlation with optical images and indicate the presence of lithium-plating.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
Sebastian Klick, Gereon Stahl, Dirk Uwe Sauer
Summary: This paper investigates the influence of electrolyte volume on the degradation of lithium-ion batteries and finds that cells with higher amounts of electrolyte degrade substantially slower. Based on electrical tests, a theory explaining the volume-dependent rise of resistance and capacity decay is proposed.
Article
Electrochemistry
Lucas Koltermann, Kevin Jacque, Jan Figgener, Sebastian Zurmuehlen, Dirk Uwe Sauer
Summary: Large-scale battery storage systems have become popular for grid services, leading to increased competition in the market. An intelligent energy management system (EMS) is necessary for these systems, including a power distribution algorithm (SPDA) to control battery units. Field tests on a 6 MW/7.5 MWh system validated the SPDA's ability to exploit individual technological strengths and reduce cyclic aging by shifting energy throughput.
BATTERIES & SUPERCAPS
(2023)
Article
Electrochemistry
Hendrik Pegel, Stefan Schaeffler, Andreas Jossen, Dirk Uwe Sauer
Summary: This study extensively characterizes the thermal runaway and thermal propagation characteristics of large-format tabless cylindrical cells with aluminum housing and laser welded endcaps. The results provide insights into the challenges and safety measures associated with the use of aluminum housing in these cells.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2023)
Article
Automation & Control Systems
Carmen Bisogni, Lucia Cimmino, Michele Nappi, Toni Pannese, Chiara Pero
Summary: This paper presents a gait-based emotion recognition method that does not rely on facial cues, achieving competitive performance on small and unbalanced datasets. The proposed approach utilizes advanced deep learning architecture and achieves high recognition and accuracy rates.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Soung Sub Lee
Summary: This study proposed a satellite constellation method that utilizes machine learning and customized repeating ground track orbits to optimize satellite revisit performance for each target.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Jian Wang, Xiuying Zhan, Yuping Yan, Guosheng Zhao
Summary: This paper proposes a method of user recruitment and adaptation degree improvement via community collaboration to solve the task allocation problem in sparse mobile crowdsensing. By matching social relationships and perception task characteristics, the entire perceptual map can be accurately inferred.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yuhang Gai, Bing Wang, Jiwen Zhang, Dan Wu, Ken Chen
Summary: This paper investigates how to reconfigure existing compliance controllers for new assembly objects with different geometric features. By using the proposed Equivalent Theory of Compliance Law (ETCL) and Weighted Dimensional Policy Distillation (WDPD) method, the learning cost can be reduced and better control performance can be achieved.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Zhihao Xu, Zhiqiang Lv, Benjia Chu, Zhaoyu Sheng, Jianbo Li
Summary: Predicting future urban health status is crucial for identifying urban diseases and planning cities. By applying an improved meta-analysis approach and considering the complexity of cities as systems, this study selects eight urban factors and explores suitable prediction methods for these factors.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yulong Ye, Qiuzhen Lin, Ka-Chun Wong, Jianqiang Li, Zhong Ming, Carlos A. Coello Coello
Summary: This paper proposes a localized decomposition evolutionary algorithm (LDEA) to tackle imbalanced multi-objective optimization problems (MOPs). LDEA assigns a local region for each subproblem using a localized decomposition method and restricts the solution update within the region to maintain diversity. It also speeds up convergence by evolving only the best-associated solution in each subproblem while balancing the population's diversity.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Longxin Zhang, Jingsheng Chen, Jianguo Chen, Zhicheng Wen, Xusheng Zhou
Summary: This study proposes a lightweight PCB image defect detection network (LDD-Net) that achieves high accuracy by designing a novel lightweight feature extraction network, multi-scale aggregation network, and lightweight decoupling head. Experimental results show that LDD-Net outperforms state-of-the-art models in terms of accuracy, computation, and detection speed, making it suitable for edge systems or resource-constrained embedded devices.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Kemal Ucak, Gulay Oke Gunel
Summary: This paper introduces a novel adaptive stable backstepping controller based on support vector regression for nonlinear dynamical systems. The controller utilizes SVR to identify the dynamics of the nonlinear system and integrates stable BSC behavior. The experimental results demonstrate successful control performance for both nonlinear systems.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Dexuan Zou, Mengdi Li, Haibin Ouyang
Summary: In this study, a photovoltaic thermal collector is integrated into a combined cooling, heating, and power system to reduce primary energy consumption, operation cost, and carbon dioxide emission. By applying a novel genetic algorithm and constraint handling approach, it is found that the CCHP scenarios with PV/T are more efficient and achieve the lowest energy consumption.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Abhinav Pandey, Litton Bhandari, Vidit Gaur
Summary: This research proposes a novel model-agnostic framework based on genetic algorithms to identify and optimize the set of coefficients of the constitutive equations of engineering materials. The framework demonstrates solution convergence, scalability, and high explainability for a wide range of engineering materials. The experimental validation shows that the proposed framework outperforms commercially available software in terms of optimization efficiency.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Zahra Ramezanpoor, Adel Ghazikhani, Ghasem Sadeghi Bajestani
Summary: Time series analysis is a method used to analyze phenomena with temporal measurements. Visibility graphs are a technique for representing and analyzing time series, particularly when dealing with rotations in the polar plane. This research proposes a visibility graph algorithm that efficiently handles biological time series with rotation in the polar plane. Experimental results demonstrate the effectiveness of the proposed algorithm in both synthetic and real world time series.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
ChunLi Li, Qintai Hu, Shuping Zhao, Jigang Wu, Jianbin Xiong
Summary: Efficient and accurate diagnosis of rotating machinery in the petrochemical industry is crucial. However, the nonlinear and non-stationary vibration signals generated in harsh environments pose challenges in distinguishing fault signals from normal ones. This paper proposes a BP-Incremental Broad Learning System (BP-INBLS) model to address these challenges. The effectiveness of the proposed method in fault diagnosis is demonstrated through validation and comparative analysis with a published method.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Fatemeh Chahkoutahi, Mehdi Khashei
Summary: The classification rate is the most important factor in selecting an appropriate classification approach. In this paper, the influence of different cost/loss functions on the classification rate of different classifiers is compared, and empirical results show that cost/loss functions significantly affect the classification rate.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Jicong Duan, Xibei Yang, Shang Gao, Hualong Yu
Summary: The study proposes a novel partition-based imbalanced multi-label learning algorithm, MLHC, which divides the original label space into disconnected subspaces using hierarchical clustering. It successfully tackles the class imbalance problem in multi-label data and outperforms other class imbalance multi-label learning algorithms.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Review
Automation & Control Systems
Qing Qin, Yuanyuan Chen
Summary: This paper offers a comprehensive review of retinal vessel automatic segmentation research, including both traditional methods and deep learning methods. In particular, supervised learning methods are summarized and analyzed based on CNN, GAN, and UNet. The advantages and disadvantages of existing segmentation methods are also outlined.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
