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The State of Charge Estimating Methods for Battery: A Review

Wen-Yeau Chang
2013 ISRN Applied Mathematics  
Based on the assessment of SOC estimation methods, the future development direction of SOC estimation is proposed.  ...  This paper gives a literature survey on the categories and mathematical methods of SOC estimation.  ...  Acknowledgment The author would like to express his gratitude to the National Science Council of ROC for the financial support under Grant no. NSC 101-2221-E-129-005.  ... 
doi:10.1155/2013/953792 fatcat:x4isxiedmzdkpb6mw4uwlp6cbu

A Novel Data-Driven Estimation Method for State-of-Charge Estimation of Li-Ion Batteries

Suwei Zhai, Wenyun Li, Cheng Wang, Yundi Chu
2022 Energies  
In this paper, a new data-driven method named the probabilistic threshold compensation fuzzy neural network (PTCFNN) is proposed to estimate the SOC of Li-ion batteries.  ...  With the increasing proportion of Li-ion batteries in energy structures, studies on the estimation of the state of charge (SOC) of Li-ion batteries, which can effectively ensure the safety and stability  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/en15093115 fatcat:vveaxvqt4na77jlefeyoh5xccy

ANN based Battery Health Monitoring - A Comprehensive Review

Sai Vasudeva Bhagavatula, Venkata Rupesh Bharadwaj Yellamraju, Karthik Chandra Eltem, Phaneendra Babu Bobba, Naveenkumar Marati, S. Tummala, S. Kosaraju, P. Bobba, S. Singh
2020 E3S Web of Conferences  
The errors in each technique are different from the other as the constraints in one method are rectified using the other method to get the least error percentage and get the nearest estimate of the SoC  ...  Advancements in Artificial Neural Networks and Machine Learning, a growing field in recent years has bought many changes in estimating these parameters.  ...  Similar to SoC FNN also determines the estimated SoH of a lithium ion cell [8] . a model has been introduced based on EIS and neural networks for the monitoring of SoH and can predict the degradation  ... 
doi:10.1051/e3sconf/202018401068 fatcat:dqs44th3sfd2pnz7vdkfq6xlle

Estimation of the SOC of energy-storage lithium batteries based on the voltage increment

Bo Zhao, Juan Hu, Shouping Xu, Jiangzhao Wang, Yanqing Zhu, Li Zhang, Chaofei Gao
2020 IEEE Access  
SOC estimation input feature selection based on the MEA-BP network Different from SOC estimation algorithms based on a physical model, a neural network can directly estimate SOC.  ...  [13] proposed an accurate estimation method for SOC based on the combination of long-short-term memory (LSTM) and a recurrent neural network.  ... 
doi:10.1109/access.2020.3031327 fatcat:zaoqq2kmx5boxeq4d6ezjlbgmi

A Novel Ultracapacitor State-of-Charge Fusion Estimation Method for Electric Vehicles Considering Temperature Uncertainty

Chun Wang, Chaocheng Fang, Aihua Tang, Bo Huang, Zhigang Zhang
2022 Energies  
In addition, the SOC estimation error of the proposed NARX-AEKF fusion estimation method based on the variable temperature model remains within 2.055%.  ...  Finally, the variable temperature model and robustness of the proposed SOC fusion estimation method are verified by experiments.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/en15124309 doaj:bc3876a1310b407fbe25e1015f2ed7a7 fatcat:fqprgxzmqzghtcq62l7332tvje

State-of-Charge Estimation of Lithium-ion Batteries Using Composite Multi-Dimensional Features and a Neural Network

jianhua li, mingsheng liu
2019 IET Power Electronics  
A novel method that uses composite multi-dimensional features data to estimate the state of charge (SOC) of a battery is presented to address the shortcomings of using single-dimensional feature data.  ...  Moreover, the time series neural network can overcome the shortcomings of traditional estimation methods.  ...  Section 3 presents the second-order RC battery equivalent model and the online OCV identified method based on FFRLS. Section 4 introduces the structure of the neural network.  ... 
doi:10.1049/iet-pel.2018.6144 fatcat:o2uionshqrcilmwxenbsmnxcqm

A novel method for SOC estimation of Li-ion batteries using a hybrid machine learning technique

2020 Turkish Journal of Electrical Engineering and Computer Sciences  
There are different SOC estimation methods in the literature that 10 promises high accuracy such as model-based estimations, adaptive filter based estimations, and a combination of these 11 systems.  ...  Based on discharge test data, XGBoost is used to estimate SOC under dynamic operating 17 conditions and the estimation is reached 98.81% coefficient of determination.  ...  Machine learning systems based on xgBoost and MLP neural network applied in satellite lithium-ion battery sets impedance estimation.  ... 
doi:10.3906/elk-1912-42 fatcat:kpf366atxnbvpbnwlw7tf5vlo4

Research on Open-Circuit Fault Protection and Positioning Isolation of Constant Current Remote Supply System in Cabled Underwater Information Network

Zheng Zhang, Xuejun Zhou, Xichen Wang, Yankai Wang
2018 2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC)  
Moreover, the estimation of the battery SOC was completed based on the Amper-Hour integral method.  ...  Pan [20] proposed a novel open-circuit voltage model based on cubic-Hermite interpolation to update the state estimation.  ...  Conflicts of Interest: The authors declare no conflict of interest. Batteries 2018, 4, 69  ... 
doi:10.1109/itoec.2018.8740472 fatcat:zgugebdvtvdzxe62a22m5vobny

State Estimation of Lithium Battery Based on Least Squares Support Vector Machine

Jiabo Li, Min Ye, Shengjie Jiao, Dawei Shi, Xinxin Xu
2019 DEStech Transactions on Environment Energy and Earth Science  
In order to improve the accuracy of battery SOC, this paper presents a novel least squares support vector machine(LSSVM) framework based on machine learning.  ...  Put the current, voltage and temperature at the current moment and the SOC estimated at the previous time are used as input vectors of the model to estimate the SOC at the current time.  ...  Acknowledgement This work is supported by the National Natural Science Foundation of China (No. 51805041).  ... 
doi:10.12783/dteees/iceee2019/31818 fatcat:jrtkputdsbgzddp22g66go6ihq

State of Charge Estimation of Lithium-ion Batteries Using LSTM and NARX Neural Networks

A. Meng-Wei, Min Ye, Jia Bo-Li, A. Qiao-Wang, Xin Xin-Xu
2020 IEEE Access  
To accurately estimate the SOC of lithium-ion batteries, this article presents a novel machine-learning method to address the risk of gradient explosion and gradient decent using the dynamic nonlinear  ...  These jumpahead connections provide a shorter path for the propagation of gradient information, therefore reducing long-term dependence on the recurrent neural network.  ...  This method is based on a large amount of experimental offline data, and the characteristics of current, voltage and temperature are trained to establish a mapping model of the SOC, including neural network  ... 
doi:10.1109/access.2020.3031340 fatcat:7lzohrrwpfakpo3flnnlei77ou

Lithium-ion Batteries State of Charge Prediction of Electric Vehicles Using RNNs-CNNs Neural Networks

Fen Zhao, Yinguo Li, Xinheng Wang, Ling Bai, Tailin Liu
2020 IEEE Access  
In order to improve battery data representation, a recursive neural networks (RNNs)-based method is proposed.  ...  Based on the reliable vector representation and sufficient feature extraction, the proposed method can provide improved SOC prediction performance.  ...  To be more specific, a RBF neural network-based nonlinear observer is designed to estimate LIBs SOC.  ... 
doi:10.1109/access.2020.2996225 fatcat:mhged4w3ynhcjc6cv7rv2tmv4i

A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network

Deyu Cui, Bizhong Xia, Ruifeng Zhang, Zhen Sun, Zizhou Lao, Wei Wang, Wei Sun, Yongzhi Lai, Mingwang Wang
2018 Energies  
In this paper, a hybrid wavelet neural network (WNN) model combining the discrete wavelet transform (DWT) method and adaptive WNN is proposed to estimate the SOC of lithium-ion batteries.  ...  Artificial neural networks (ANNs) methods are not based on the detailed knowledge of the battery model (e.g., the back-propagation neural network (BPNN) [27, 28] , support vector machine (SVM) network,  ...  Acknowledgments: This work was supported by the Economic, Trade, and Information Commission Shenzhen of Shenzhen Municipality Strategic Emerging Industries and Future Industrial Development "Innovation  ... 
doi:10.3390/en11040995 fatcat:uin7miely5airneyvfkli47uki

A Review on Battery Modelling Techniques

S. Tamilselvi, S. Gunasundari, N. Karuppiah, Abdul Razak RK, S. Madhusudan, Vikas Madhav Nagarajan, T. Sathish, Mohammed Zubair M. Shamim, C. Ahamed Saleel, Asif Afzal
2021 Sustainability  
., rely on the energy stored within the device to operate. The increased penetration rate of the battery system requires accurate modelling of charging profiles to optimise performance.  ...  The growing demand for electrical energy and the impact of global warming leads to a paradigm shift in the power sector. This has led to the increased usage of renewable energy sources.  ...  A novel hybrid method by fusion of back propagation neural network and improved the ampere hour counting method is proposed for SoC estimation of lithium-ion battery [45] .  ... 
doi:10.3390/su131810042 fatcat:bhnzlfivuvgcvkdh3zixihsroe

State-of-Charge Estimation of Lithium-Ion Battery Pack Based on Improved RBF Neural Networks

Li Zhang, Min Zheng, Dajun Du, Yihuan Li, Minrui Fei, Yuanjun Guo, Kang Li, Jing Na
2020 Complexity  
Simulation results show that generalization error of SOC estimation using the novel RBF neural network model is less than half of that using other methods.  ...  Finally, a conventional RBF neural network model, an improved RBF neural model using the two stage method, and a least squares support vector machine (LSSVM) model are also used to estimate the battery  ...  Section 1 introduces the input selection based on the FRA method. In Section 2, the application of improved RBF neural network for SOC estimation of battery pack is introduced in detail.  ... 
doi:10.1155/2020/8840240 fatcat:kpdahol7fzdcfmwhe37gz7jhzm

State of Charge Estimation for Lithium-Ion Batteries Using Simple Recurrent Units and Unscented Kalman Filter

Zhaowei Zhang, Zhaowei Zhang, Xinghao Zhang, Xinghao Zhang, Zhiwei He, Zhiwei He, Chunxiang Zhu, Chunxiang Zhu, Wenlong Song, Mingyu Gao, Mingyu Gao, Yining Song
2022 Frontiers in Energy Research  
In this article, we propose an improved recurrent neural network model to estimate lithium-ion battery state of charge.  ...  Accurate estimation of the state of charge plays a very important role in ensuring the safe and effective operation of battery lithium-ion batteries and is one of the most important state parameters.  ...  A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network.  ... 
doi:10.3389/fenrg.2022.938467 doaj:aec2071690c14b9eb7e3102dfc331955 fatcat:35ktqsskmjasjajjs2ka3zlhqi
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