Article
Chemistry, Physical
Ming-Ying Zhou, Jian-Bang Zhang, Chi-Jyun Ko, Kuo-Ching Chen
Summary: In this study, a time-saving approach for measuring the open-circuit voltage (OCV) of a battery is proposed. By using a simplified first-order RC circuit model, the OCV at each state of charge (SOC) can be computed without the need for complete voltage relaxation information. Experimental results demonstrate that this approach significantly reduces the measurement time (usually less than 6 minutes) while maintaining high accuracy (usually less than 3 mV) compared to traditional methods.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
Tedjani Mesbahi, Rocio Bendala Sugranes, Reda Bakri, Patrick Bartholomeus
Summary: The paper proposes an electro-thermal coupled model for a lithium-ion battery, accurately describing physicochemical phenomena in the battery system. By calculating power losses through temperature distribution to update electric parameters, the model achieves electric-thermal coupling. It can simulate dynamic interaction between battery behaviors and shows high performance in predicting cell surface temperature.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Tadeusz Bialon, Roman Niestroj, Wojciech Skarka, Wojciech Korski
Summary: The aim of this research is to create an accurate simulation model of a lithium-ion battery cell for the design of a traction battery in a fully electric vehicle. Discharge characteristic tests and HPPC tests were conducted to determine the cell capacity and equivalent circuit parameters. The article provides a detailed description of the testing methods and evaluates the quality and applicability of the acquired measurement data. The simulation model was successfully validated through charge-depleting cycle test.
Article
Thermodynamics
Eero Immonen, Jussi Hurri
Summary: This article compares four thermo-electric CFD models for battery thermal analysis and finds that a simple constant internal resistance heat generation model is remarkably close in accuracy to the more tedious dynamic equivalent circuit model for purely thermal considerations. Although the study focuses only on discharging, the methods and models can also be used in charging situations in the future.
APPLIED THERMAL ENGINEERING
(2021)
Article
Energy & Fuels
Shantanu R. Shinde, Yihan Song, Elham Sahraei
Summary: This study tackles the challenge of simulating heterogeneous structures like battery modules in electric vehicles. By using the RVE technique and homogenization theory, a computationally efficient and accurate model for crash simulations of battery packs was developed. Validation tests demonstrate that the homogenized model significantly reduces computational time while maintaining high precision in predicting the load-displacement response. This research provides a valuable tool for system level modeling and optimization of electric vehicle crashworthiness.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Article
Energy & Fuels
Jianfeng Wang, Yongkai Jia, Na Yang, Yanbing Lu, Mengyu Shi, Xutong Ren, Dongchen Lu
Summary: The study explores the factors affecting the accuracy of the equivalent circuit model in electric vehicle battery management systems (BMS) and designs experimental procedures to identify and optimize the model parameters. By utilizing polynomial fitting and sensitivity analysis, the study investigates the impact of three model parameters on different performance aspects under different state of charge (SOC). This study provides a foundation for battery modeling and model parameter identification, and proposes an optimization parameter as an indicator.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Shunli Wang, Yongcun Fan, Chunmei Yu, Siyu Jin, Carlos Fernandez, Daniel-Ioan Stroe
Summary: The study introduced a novel covariance matching-electrical equivalent circuit modeling method with an improved adaptive weighting factor correction and differential Kalman filtering model for characterizing the adaptive working state of lithium-ion batteries. Experimental tests showed good response of the method to battery state changes, leading to improved estimation accuracy.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Chemistry, Physical
Maximilian Bruch, Lluis Millet, Julia Kowal, Matthias Vetter
Summary: A new method for precise parameterization of an equivalent circuit model from pulse tests is presented, with the robustness of such models increased by limiting the voltage of the RC element with the highest time constant. As a result, a precise and reliable model of a lithium-ion battery cell is created, with only a minor root-mean-square error of 1.30%.
JOURNAL OF POWER SOURCES
(2021)
Article
Automation & Control Systems
Chong Hu, Haibo Liu, Yan Ji
Summary: This article aims to design an effective model and optimization method to describe and analyze the operating characteristics of the lithium-ion battery based on online measurement data. By exploiting the memory superiorities of the fractional-order, the fractional-order controlled autoregressive model is derived, which includes the electrochemical impedance spectroscopy and the n-RC equivalent circuit model. The approach designs a new gradient direction and fully utilizes the data from the lithium-ion battery by adding a suitable weighted factor. The experimental simulation result shows the performance of the proposed algorithms.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Engineering, Chemical
Sergey V. Kuchak, Sergey V. Brovanov
Summary: This paper investigates the characteristics of high-capacity lithium-iron-phosphate batteries under impulse and long-term operation modes with different discharge current levels, and proposes a modified DP model. The model is capable of calculating the activation polarization parameters for different discharge currents and estimating the state of charge of the battery.
Article
Chemistry, Physical
Marcel Esser, Gunnar Rohde, Christian Rehtanz
Summary: This paper demonstrated the development of a setup that performs impedance spectroscopy on commercial lithium-ion battery cells and packs using standard measurement equipment. The setup allows for a wider range of measurements and applications compared to commercial devices.
JOURNAL OF POWER SOURCES
(2022)
Article
Chemistry, Physical
Xin Lai, Changyong Jin, Wei Yi, Xuebing Han, Xuning Feng, Yuejiu Zheng, Minggao Ouyang
Summary: This comprehensive review investigates the mechanism and evolutionary process of internal short circuit (ISC) within lithium-ion batteries (LIBs), covering types, inducing mechanisms, evolution stages, experimental methods, detection and diagnosis techniques, prevention methods, and future prospects. The study emphasizes the importance of improving safety in LIBs through advancements in modeling, simulation, detection, and prevention of ISC.
ENERGY STORAGE MATERIALS
(2021)
Article
Chemistry, Physical
Hao Cui, Dongsheng Ren, Mengchao Yi, Sixuan Hou, Kai Yang, Hongmei Liang, Xuning Feng, Xuebing Han, Youzhi Song, Li Wang, Xiangming He
Summary: The wetting process is crucial in battery production efficiency and quality, especially for large-format or high-energy density lithium-ion batteries. This study proposes a method for in-situ monitoring of the open circuit voltage during electrolyte filling, providing valuable information about the process.
Article
Chemistry, Physical
Felix Katzer, Leonard Jahn, Markus Hahn, Michael A. Danzer
Summary: A novel model-based approach was developed to distinguish between normal and lithium deposition-affected relaxation processes during fast charging of lithium-ion batteries. This method enables the classification of charging processes based on accelerated aging, with remarkable sensitivity and automated detection of lithium deposition.
JOURNAL OF POWER SOURCES
(2021)
Article
Energy & Fuels
Yi-Feng Feng, Jia-Ni Shen, Zi-Feng Ma, Yi-Jun He
Summary: This study investigates equivalent circuit models (ECMs) with different resistance capacitance (RC) numbers and models the relationship between circuit parameters and state of charge (SOC) through polynomial functions. The results demonstrate that the ECMs with three-RC network can effectively describe the terminal voltage response of SIBs.
JOURNAL OF ENERGY STORAGE
(2021)
Review
Materials Science, Multidisciplinary
Guodong Zou, Jiawen Feng, Xue Zhao, Jinming Wang, Yangyang Wang, Weihao Yang, Mengyao Wei, Yimin Wang, Lanjie Li, Liqun Ren, Carlos Fernandez, Qiuming Peng
Summary: This article summarizes the challenges faced by rechargeable magnesium metal batteries (RMBs) in electrode applications, including surface passivation, uneven deposition/dissolution, and corrosion. It then discusses the protective measures through three-dimensional host nanostructure fabrication, Mg alloys anode design, current collector modification, artificial solid-electrolyte interphase construction, and electrolyte optimization. Finally, the future prospects and outlooks for developing other strategies to improve the performance of rechargeable Mg batteries and promote their commercial applications are also discussed.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Article
Engineering, Industrial
Shunli Wang, Yongcun Fan, Siyu Jin, Paul Takyi-Aninakwa, Carlos Fernandez
Summary: Safety assurance is crucial for lithium-ion batteries in power supply fields. The proposed improved ANA-LSTM neural network with high-robustness feature extraction and optimal parameter characterization achieves accurate RUL prediction. The collaborative multi-feature model realizes multi-scale parameter optimization and robust RUL prediction, advancing the industrial application of lithium-ion batteries.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Electrical & Electronic
Lizhou Liu, Zhaotian Yan, Bin Xu, Pengcheng Zhang, Changsong Cai, Huazhong Yang, Lu Zhang, Shunli Wang
Summary: A single-magnetic bidirectional integrated equalizer for hybrid energy storage systems is proposed in this paper. It utilizes a multi-winding transformer and voltage multiplier to balance the voltages of battery and supercapacitor strings. The proposed equalizer simplifies the balance circuit by using fewer components compared to previous circuits, while still achieving voltage balance. Experimental results validate the effectiveness of the proposed circuit in balancing the hybrid energy storage system during the operation of the DC-DC converter.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Electrochemistry
Renjun Feng, Shunli Wang, Chunmei Yu, Heng Zhou, Carlos Fernandez
Summary: An improved second-order polarized equivalent circuit (SO-PEC) modeling method is proposed to enhance the accuracy of state of charge (SOC) estimation for lithium-ion batteries under different working conditions. The algorithm incorporates recursive parameter identification and an optimized higher-order term compensation-adaptive extended Kalman filter (HTC-AEKF) to reduce the impact of noise and improve accuracy. Comparative results demonstrate significant improvements in SOC estimation accuracy under various working conditions.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2023)
Article
Electrochemistry
Chuangshi Qi, Shunli Wang, Wen Cao, Yanxin Xie, Mingdong Lei
Summary: This paper establishes a Hysteresis Characteristic-Electrical Equivalent Circuit (HC-EEC) modeling and proposes an Online Multi-Time Scale Adaptive Parameter Identification Strategy (OM-TSAPIS) to accurately identify battery model parameters, which improves the parameter identification accuracy of the HC-EEC model.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2023)
Review
Electrochemistry
Shunli Wang, Xianyi Jia, Paul Takyi-Aninakwa, Daniel-Ioan Stroe, Carlos Fernandez
Summary: This review examines the existing methods for estimating the State of Charge (SOC) of Lithium-ion batteries (LIBs) and analyzes their advantages and disadvantages. It also provides a systematic analysis of the methods for constructing LIB models, considering applicability and accuracy. Furthermore, the advantages of particle filtering (PF) over the Kalman filter (KF) series algorithm for SOC estimation are summarized, and various improved PF algorithms for LIB SOC estimation are compared and discussed. Additionally, this review offers suggestions for researchers in the battery field.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2023)
Article
Engineering, Electrical & Electronic
Lu Chen, Shunli Wang, Lei Chen, Jialu Qiao, Carlos Fernandez
Summary: A new high-precision SOC estimation method is proposed using a combination of dual Kalman filter algorithm and backpropagation neural network. This method achieves online parameter updates and SOC estimation and demonstrates accuracy, effectiveness, and temperature adaptability in complex conditions of lithium-ion batteries.
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS
(2023)
Article
Chemistry, Physical
Tao Zhu, Shunli Wang, Yongcun Fan, Heng Zhou, Yifei Zhou, Carlos Fernandez
Summary: This paper proposes a joint algorithm based on the second-order RC equivalent circuit model for the estimation of the SOC and SOE of lithium-ion batteries. The results show that the algorithm can accurately estimate the SOC and SOE under different working conditions and temperatures.
Article
Chemistry, Applied
Haotian Shi, Shunli Wang, Jianhong Liang, Paul Takyi-Aninakwa, Xiao Yang, Carlos Fernandez, Liping Wang
Summary: An efficient adaptive multi-time scale identification strategy is proposed in this paper to achieve high-fidelity modeling of complex kinetic processes inside the battery. A second-order equivalent circuit model network is constructed, and two coupled sub-filters are developed to decouple the kinetic processes based on the time-scale information. The proposed method can reduce the dispersion of parameter identification results and pave the way for adaptive state estimators and efficient embedded applications.
JOURNAL OF ENERGY CHEMISTRY
(2023)
Article
Energy & Fuels
Shunli Wang, Paul Takyi-Aninakwa, Siyu Jin, Ke Liu, Carlos Fernandez
Summary: Capacity estimation is crucial for the safe and acceptable energy delivery of lithium-ion batteries in real-time complex working conditions. An improved sliding window-long short-term memory (SW-LSTM) modeling method is proposed, which introduces multiple time-scale charging characteristic factors for high-precision and robust capacity estimation. The optimized feature information set is extracted using an optimized differential integration-moving average autoregressive (DI-MAA) model, serving as input matrices for the capacity estimation model. Experimental tests show that the proposed SW-LSTM estimation model with optimized DI-MAA-based data preprocessing achieves a maximum capacity estimation error of 3.56% and an average relative error of 0.032 under complex working conditions, providing effective safety assurance for lithium-ion batteries.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Takyi-Aninakwa Paul, Shunli Wang, Hongying Zhang, Huan Li, Xiao Yang, Carlos Fernandez
Summary: This paper proposes an adaptive strong tracking square-root extended Kalman filter (ASTSEKF) for SOC estimation of lithium-ion batteries. The ASTSEKF optimizer updates the covariance matrix and corrects the uncertainties of the EKF method using an adaptive fading factor, a weight adjustor, and a strong tracking filter. Experimental results demonstrate the effectiveness of the ASTSEKF method in improving SOC estimation.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Donglei Liu, Shunli Wang, Yongcun Fan, Yawen Liang, Carlos Fernandez, Daniel-Ioan Stroe
Summary: State estimation of lithium-ion batteries is crucial for the battery management system of electric vehicles. This study introduces a novel method called AFCFFRLS-AEKF, which effectively estimates the State of Energy (SOE) and addresses the influence of temperature. The accuracy of estimation is verified, achieving higher estimation accuracy and stronger robustness.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Yifei Zhou, Shunli Wang, Yanxing Xie, Xianfeng Shen, Carlos Fernandez
Summary: This paper presents a method for predicting the SOH and RUL of Lithium-ion battery systems based on a data-driven model using improved Grey Wolf optimization algorithm and deep extreme learning machine. The accuracy and robustness of the results were checked by analyzing and verifying the experimental data and extracting health indicators.
Article
Thermodynamics
Shunli Wang, Fan Wu, Paul Takyi-Aninakwa, Carlos Fernandez, Daniel-Ioan Stroe, Qi Huang
Summary: In this paper, an improved SF-GPR-LSTM modeling method is proposed for the estimation of remaining capacity in low-temperature power systems. The model's adaptability is verified using datasets from whole-life-cycle tests on two batteries, and it shows good estimation performance even with only 55% of the data. The proposed SF-GPR-LSTM model enables effective carrier transport synergistic optimization and provides a theoretical foundation for the estimation of battery remaining capacity at extremely low temperatures.
Proceedings Paper
Computer Science, Artificial Intelligence
Siyu Jin, Chao Wang, Shunli Wang, Xiao Yang, Daniel-Ion Store
Summary: A novel BP-DEKF model is proposed in this study to improve the real-time estimation accuracy of battery state by establishing a second-order equivalent circuit model and considering the coupling effect between SOC and SOH. A BP neural network is introduced for correction to offset the model error of EKF and improve the estimation accuracy. The method demonstrates high precision and robustness, providing a theoretical foundation for battery state monitoring.
2023 IEEE PES CONFERENCE ON INNOVATIVE SMART GRID TECHNOLOGIES, ISGT MIDDLE EAST
(2023)
