Article
Thermodynamics
E. Jiaqiang, Bin Zhang, Yan Zeng, Ming Wen, Kexiang Wei, Zhonghua Huang, Jingwei Chen, Hao Zhu, Yuanwang Deng
Summary: This paper investigates the essence of inconsistency in lithium-ion batteries as State-Of-Charge (SOC) inconsistency, proposing a method to describe battery inconsistency using SOC disparity and studying the equalization control strategy. Through simulations and experiments, it is shown that active equalization significantly improves cell inconsistency and enhances energy utilization in the battery pack during charging and discharging processes. The proposed SOC estimation method meets accuracy requirements, and the equalization strategies effectively minimize SOC and voltage disparities among battery cells.
Article
Thermodynamics
Limei Wang, Jingjing Sun, Yingfeng Cai, Yubo Lian, Mengjie Jin, Xiuliang Zhao, Ruochen Wang, Long Chen, Jun Chen
Summary: This paper proposes a method to construct a complete OCV-SOC curve at different temperatures based on cloud data. It also establishes an OCV-SOC model suitable for different temperatures using an improved electrode potential model. Additionally, a method to construct a complete OCV-SOC curve from the charge segment based on the thermodynamic ideal material characteristics is proposed.
Article
Engineering, Chemical
Huixin Tian, Jianhua Chen
Summary: Accurate estimation of SOC is crucial for vehicle management systems. This paper introduces an attention-based CONV-LSTM module for SOC prediction, based on CNN and LSTM networks, which shows promising results in experiments.
Article
Energy & Fuels
Haisheng Guo, Xudong Han, Run Yang, Jinjin Shi
Summary: This paper proposes a multi-scale estimation algorithm that combines fractional order adaptive extended Kalman filter and variable forgetting factor recursive least square to solve the problem of SoC estimation in lithium-ion battery management system. Experimental results show that the proposed method achieves high accuracy and robustness.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Environmental
Douglas Pedersen, Michael Lybbert, Roseanne Warren
Summary: Life cycle analysis (LCA) is a method for assessing the environmental impacts of a product, and it can be used to minimize these impacts by improving the design or use of the product. This study explores the potential benefits of active cooling on lithium-ion battery life cycle environmental impacts. The results show that active cooling can significantly reduce environmental impacts when coupled with thicker electrodes, and it can reduce impacts in various categories such as global warming potential and energy use.
RESOURCES CONSERVATION AND RECYCLING
(2022)
Article
Thermodynamics
Lin Chen, Wentao Yu, Guoyang Cheng, Jierui Wang
Summary: This paper focuses on the SOC estimation of lithium batteries using a fractional-order adaptive square-root cubature Kalman filter (FO-ASRCKF). A fractional-order model (FOM) of the battery is established using fractional-order derivative theory. An improved adaptive genetic algorithm is applied for accurate identification of the multi-parameter model. The proposed FO-ASRCKF algorithm based on FOM and adaptive rules outperforms other filters in terms of SOC estimation accuracy and robustness.
Article
Engineering, Electrical & Electronic
Ruohan Guo, Weixiang Shen
Summary: This paper proposes a model fusion method for online state of charge and state of power co-estimation of lithium-ion batteries in electric vehicles. By utilizing particle swarm optimization-genetic algorithm and dual extended Kalman filter algorithm, the estimation of battery SOC and analysis of SOP are improved significantly.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Energy & Fuels
J. Yeregui, L. Oca, I. Lopetegi, E. Garayalde, M. Aizpurua, U. Iraola
Summary: This paper presents a sequential model based on Physic Based Models (PBM) and Artificial Intelligence Models (AI) focused on the estimation of the State of Charge (SoC). By selecting the most relevant variables, reducing computational cost and improving performance. The model has been experimentally validated to outperform alternative solutions with laboratory tests and low computational cost.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Chemistry, Physical
Yeliang Wei, Yinzhong Yan, Chao Zhang, Kangpei Meng, Chao Xu
Summary: In this paper, a new signal feature based on ultrasonic resonance phenomenon is proposed for state of charge (SOC) estimation of batteries. This feature, characterized by the initial rise time (IRT), is calculated using an algorithm based on temporal moment and adaptive moving root mean square. Experimental results show that the proposed IRT feature is highly correlated to the SOC status with satisfying accuracy, monotonicity and linearity. The IRT feature has the additional advantage to be calculated by only a single data acquisition channel, providing a more convenient mean of battery status estimation.
JOURNAL OF POWER SOURCES
(2023)
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
Energy & Fuels
Mehmet Korkmaz
Summary: Accurate state-of-charge (SoC) estimation is crucial for the efficient management and protection of Li-Ion batteries, especially in electrified vehicles. However, the complexity of electrochemical reactions and environmental variables make accurate SoC estimation challenging. Traditional methods suffer from limitations, while data-driven approaches have gained popularity for building models based on battery parameters. This study aims to comprehensively compare ML methods and evaluate the effectiveness of different filters for outlier removal in improving SoC estimation.
JOURNAL OF ENERGY STORAGE
(2023)
Review
Green & Sustainable Science & Technology
Jiahui Zhao, Yong Zhu, Bin Zhang, Mingyi Liu, Jianxing Wang, Chenghao Liu, Xiaowei Hao
Summary: The accurate estimation of the state of charge (SOC), the state of health (SOH) and the prediction of remaining useful life (RUL) of lithium-ion batteries is essential for battery management. Researchers have conducted extensive research on battery state evaluation and RUL prediction methods, proposing various approaches. This paper introduces the definitions and existing estimation methods for SOC and SOH, presents the definition of RUL and compares different approaches. Lastly, it summarizes the challenges in lithium-ion battery state estimation and RUL prediction and proposes future directions for development.
Article
Energy & Fuels
Julius Schmitt, Mathias Rehm, Alexander Karger, Andreas Jossen
Summary: This study demonstrates a method of using reconstructed open circuit voltage (OCV) curves to analyze the partial charging curves of a commercial lithium-ion cell, providing valuable information about degradation modes and remaining cell capacity. Accurate OCV reconstruction and degradation mode estimation can be achieved when a state of charge (SOC) window between 20% and 70% is available. The method is also applicable to charging curves at higher current rates by considering an additional overpotential.
JOURNAL OF ENERGY STORAGE
(2023)
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
Energy & Fuels
Xiaodong Xu, Shengjin Tang, Huahua Ren, Xuebing Han, Yu Wu, Languang Lu, Xuning Feng, Chuanqiang Yu, Jian Xie, Minggao Ouyang, Wei Liu, Yuejun Yan
Summary: This paper presents a novel joint state estimation method for lithium-ion batteries based on a hybrid model. The method accurately estimates the state of charge, state of health, state of power, and state of energy, and it has been verified to have high accuracy and strong robustness through experiments.
JOURNAL OF ENERGY STORAGE
(2022)
