Article
Energy & Fuels
Kaixuan Zhang, Cheng Chen, Yanzhou Duan, Yu Fang, Ruixin Yang
Summary: This paper proposes a new method to describe the relation between OCV and SOC, simplifying the mapping between temperature, aging, OCV, and SOC into a temperature-independent three-dimensional mapping. The newly-defined capacity and OCV-SOC curve are independent of battery temperature and have been verified with a large number of test data. A cooperative estimation method for model parameters and state based on the DEKF algorithm is developed, and the results show that the proposed method can accurately estimate battery SOC with an error within 3% after fast convergence.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Xiong Feng, Junxiong Chen, Zhongwei Zhang, Shuwen Miao, Qiao Zhu
Summary: This paper presents a novel neural network structure called CWRNN, which effectively addresses long-term dependencies, reduces training and computation costs, and is validated under different temperature conditions.
Article
Engineering, Electrical & Electronic
Wooyong Kim, Pyeong-Yeon Lee, Jonghoon Kim, Kyung-Soo Kim
Summary: This study presents a robust SOC estimation scheme for lithium-ion batteries in commercialized electric vehicles, providing considerable accuracy under different operational conditions and aging levels. The proposed method effectively deals with model uncertainty and parameter variation, with comprehensive analysis conducted on battery cells and electrified vehicles.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Energy & Fuels
Tae -Won Noh, Dong Hwan Kim, Byoung Kuk Lee
Summary: In this study, a novel online state-of-health (SOH) estimation algorithm for electric vehicles (EVs) is proposed based on the compression ratio of open circuit voltage (OCV)-to-charged capacity curve. The proposed algorithm estimates the degraded capacity at every sampling time during the driving operation through a first-order low-pass filter, which does not require complex mathematical tools and numerous offline data.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Automation & Control Systems
Tiancheng Ouyang, Peihang Xu, Jie Lu, Xiaoyi Hu, Benlong Liu, Nan Chen
Summary: This article proposes a multithread dynamic optimization method for accurate estimation of state-of-charge (SOC) and state-of-health (SOH) of power batteries. The method utilizes a fractional-order model and an unscented Kalman filter for SOC estimation, and proposes Gaussian linear models based on parameters of six commonly used open-circuit-voltage models for SOH estimation. Experimental results confirm the effectiveness of the proposed method in improving estimation accuracy.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Green & Sustainable Science & Technology
Tao Zhang, Ningyuan Guo, Xiaoxia Sun, Jie Fan, Naifeng Yang, Junjie Song, Yuan Zou
Summary: This paper proposes a systematic co-estimation framework for lithium-ion batteries in electric vehicles, using various algorithms and model parameter estimation to achieve accurate SOC and SOP estimation, ultimately realizing online state estimation. Experiments demonstrate the effectiveness and accuracy of this framework in different aging states.
Review
Energy & Fuels
Pedro H. Camargos, Pedro H. J. dos Santos, Igor R. dos Santos, Gabriel S. Ribeiro, Ricardo E. Caetano
Summary: This article discusses various lithium-ion battery technologies, including nickel cobalt aluminum, nickel manganese cobalt, lithium iron phosphate, and lithium titanate. It also compares niobium batteries, indicating niobium as a promising metal for use in lithium-ion batteries.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Review
Energy & Fuels
Yuefeng Liu, Yingjie He, Haodong Bian, Wei Guo, Xiaoyan Zhang
Summary: With the rapid growth in productivity, the demand for fossil fuels has increased, leading to research and development of new energy sources. Electric vehicles powered by lithium-ion batteries have become the mainstream in the automotive industry. Battery management systems are important for ensuring the safety and reliability of electric vehicle operation. Deep neural networks have been widely used in the field of battery state estimation, and this review classifies recent estimation methods based on deep learning and discusses future directions.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Multidisciplinary Sciences
Rajakumar Sakile, Umesh Kumar Sinha
Summary: This paper proposes an adaptive joint algorithm approach to calculate online parameters and accurate state of charge for electric vehicle batteries. The approach shows better results in forecasting battery health and remaining useful life, significantly improving the accuracy of the system.
ADVANCED THEORY AND SIMULATIONS
(2022)
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
Energy & Fuels
Friedrich von Buelow, Markus Wassermann, Tobias Meisen
Summary: This study surpasses existing battery state of health (SOH) forecasting methods by using battery pack data from real-world vehicle operation. The results show that a state-of-the-art SOH forecasting method based on histogram features works not only on laboratory battery cell data, but also on real-world battery system data.
JOURNAL OF ENERGY STORAGE
(2023)
Review
Energy & Fuels
Friedrich von Buelow, Tobias Meisen
Summary: The ageing of Lithium-ion batteries depends on their operation during charging, discharging, and rest phases, and can be forecasted to determine the state of health (SOH) of the battery. This SOH forecasting is valuable for fleet managers of battery electric vehicle (BEV) fleets to plan vehicle replacement and optimize operational strategies. However, there are limitations in the applicability and comparability of existing models due to different data sets, metrics, output values, and forecast horizons.
JOURNAL OF ENERGY STORAGE
(2023)
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
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
Romain Mathieu, Olivier Briat, Philippe Gyan, Jean-Michel Vinassa
Summary: This article focuses on numerically optimizing fast charging protocols and their impact on battery cycle life. Experimental results show that optimized protocols can significantly reduce charging time and/or degradation while maintaining long cycle life.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Automation & Control Systems
Minfan Fu, Zefan Tang, Chengbin Ma
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2019)
Article
Thermodynamics
Xuesong Li, Hujie Pan, Xue Dong, David Hung, Min Xu
PROCEEDINGS OF THE COMBUSTION INSTITUTE
(2019)
Article
Thermodynamics
Xue Dong, Jie Yang, David L. S. Hung, Xuesong Li, Min Xu
PROCEEDINGS OF THE COMBUSTION INSTITUTE
(2019)
Article
Energy & Fuels
Jie Yang, Xue Dong, Qiang Wu, Min Xu
Article
Energy & Fuels
Hujie Pan, Di Xiao, David Hung, Min Xu, Xuesong Li
Article
Energy & Fuels
Shengqi Wu, Shangze Yang, Margaret Wooldridge, Min Xu
Article
Engineering, Mechanical
Xuesong Li, Tianyun Li, Min Xu
EXPERIMENTS IN FLUIDS
(2019)
Article
Thermodynamics
Xuesong Li, Di Xiao, Scott E. Parrish, Ronald O. Grover, David L. S. Hung, Min Xu
INTERNATIONAL JOURNAL OF ENGINE RESEARCH
(2020)
Article
Thermodynamics
Di Xiao, Ichikawa Yukihiko, Xuesong Li, David Hung, Keiya Nishida, Min Xu
INTERNATIONAL JOURNAL OF ENGINE RESEARCH
(2020)
Article
Engineering, Multidisciplinary
Jingjing Cao, Zhen Ma, Xuesong Li, Min Xu
MEASUREMENT SCIENCE AND TECHNOLOGY
(2019)
Article
Engineering, Mechanical
Shangze Yang, Zhen Ma, Shengqi Wu, Xuesong Li, Min Xu
EXPERIMENTS IN FLUIDS
(2019)
Article
Energy & Fuels
Shangze Yang, Xuesong Li, David L. S. Hung, Masataka Arai, Min Xu
Article
Thermodynamics
Yi Gao, Shengqi Wu, Xue Dong, Xuesong Li, Min Xu
APPLIED THERMAL ENGINEERING
(2019)
Review
Energy & Fuels
Shangze Yang, Zhen Ma, Xuesong Li, David L. S. Hung, Min Xu
Article
Energy & Fuels
Xuesong Li, Shangze Yang, Tianyun Li, David L. S. Hung, Min Xu