My bibliography
Save this item
A method for state-of-charge estimation of lithium-ion batteries based on PSO-LSTM
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Simone Barcellona & Lorenzo Codecasa & Silvia Colnago & Luigi Piegari, 2023. "Calendar Aging Effect on the Open Circuit Voltage of Lithium-Ion Battery," Energies, MDPI, vol. 16(13), pages 1-16, June.
- Li, Zongxiang & Li, Liwei & Chen, Jing & Wang, Dongqing, 2024. "A multi-head attention mechanism aided hybrid network for identifying batteries’ state of charge," Energy, Elsevier, vol. 286(C).
- Cui, Zhenhua & Kang, Le & Li, Liwei & Wang, Licheng & Wang, Kai, 2022. "A combined state-of-charge estimation method for lithium-ion battery using an improved BGRU network and UKF," Energy, Elsevier, vol. 259(C).
- Biao Yang & Yinshuang Wang & Yuedong Zhan, 2022. "Lithium Battery State-of-Charge Estimation Based on a Bayesian Optimization Bidirectional Long Short-Term Memory Neural Network," Energies, MDPI, vol. 15(13), pages 1-18, June.
- Oyewole, Isaiah & Chehade, Abdallah & Kim, Youngki, 2022. "A controllable deep transfer learning network with multiple domain adaptation for battery state-of-charge estimation," Applied Energy, Elsevier, vol. 312(C).
- Liu, Mengmeng & Xu, Jun & Jiang, Yihui & Mei, Xuesong, 2023. "Multi-dimensional features based data-driven state of charge estimation method for LiFePO4 batteries," Energy, Elsevier, vol. 274(C).
- Chen, Dong & Zhang, Wenjie & Du, Xiaoze & Xu, Lei & Wei, Huimin, 2024. "Dynamic optimization method for cleaning cycle of condenser of nuclear power plant," Energy, Elsevier, vol. 294(C).
- Cui, Zhenhua & Kang, Le & Li, Liwei & Wang, Licheng & Wang, Kai, 2022. "A hybrid neural network model with improved input for state of charge estimation of lithium-ion battery at low temperatures," Renewable Energy, Elsevier, vol. 198(C), pages 1328-1340.
- Chai, Xuqing & Li, Shihao & Liang, Fengwei, 2024. "A novel battery SOC estimation method based on random search optimized LSTM neural network," Energy, Elsevier, vol. 306(C).
- Shasha Yang & Anjie Jin & Wen Nie & Cong Liu & Yu Li, 2022. "Research on SSA-LSTM-Based Slope Monitoring and Early Warning Model," Sustainability, MDPI, vol. 14(16), pages 1-16, August.
- Chen, Junxiong & Zhang, Yu & Wu, Ji & Cheng, Weisong & Zhu, Qiao, 2023. "SOC estimation for lithium-ion battery using the LSTM-RNN with extended input and constrained output," Energy, Elsevier, vol. 262(PA).
- Gu, Xinyu & See, K.W. & Li, Penghua & Shan, Kangheng & Wang, Yunpeng & Zhao, Liang & Lim, Kai Chin & Zhang, Neng, 2023. "A novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model," Energy, Elsevier, vol. 262(PB).
- Jiahui Zhao & Yong Zhu & Bin Zhang & Mingyi Liu & Jianxing Wang & Chenghao Liu & Xiaowei Hao, 2023. "Review of State Estimation and Remaining Useful Life Prediction Methods for Lithium–Ion Batteries," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
- Bastida, Hector & De la Cruz-Loredo, Ivan & Saikia, Pranaynil & Ugalde-Loo, Carlos E., 2024. "Discrete-time state-of-charge estimator for latent heat thermal energy storage units based on a recurrent neural network," Applied Energy, Elsevier, vol. 371(C).
- Yang, Kuo & Tang, Yugui & Zhang, Shujing & Zhang, Zhen, 2022. "A deep learning approach to state of charge estimation of lithium-ion batteries based on dual-stage attention mechanism," Energy, Elsevier, vol. 244(PB).
- Zafar, Muhammad Hamza & Khan, Noman Mujeeb & Houran, Mohamad Abou & Mansoor, Majad & Akhtar, Naureen & Sanfilippo, Filippo, 2024. "A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature," Energy, Elsevier, vol. 292(C).
- Jichao Hong & Fengwei Liang & Xun Gong & Xiaoming Xu & Quanqing Yu, 2022. "Accurate State of Charge Estimation for Real-World Battery Systems Using a Novel Grid Search and Cross Validated Optimised LSTM Neural Network," Energies, MDPI, vol. 15(24), pages 1-14, December.
- Yu, Hanqing & Zhang, Lisheng & Wang, Wentao & Li, Shen & Chen, Siyan & Yang, Shichun & Li, Junfu & Liu, Xinhua, 2023. "State of charge estimation method by using a simplified electrochemical model in deep learning framework for lithium-ion batteries," Energy, Elsevier, vol. 278(C).
- Zhang, Chengzhong & Zhao, Hongyu & Wang, Liye & Liao, Chenglin & Wang, Lifang, 2024. "A comparative study on state-of-charge estimation for lithium-rich manganese-based battery based on Bayesian filtering and machine learning methods," Energy, Elsevier, vol. 306(C).
- Zhang, Kai & Bai, Dongxin & Li, Yong & Song, Ke & Zheng, Bailin & Yang, Fuqian, 2024. "Robust state-of-charge estimator for lithium-ion batteries enabled by a physics-driven dual-stage attention mechanism," Applied Energy, Elsevier, vol. 359(C).
- Tang, Aihua & Huang, Yukun & Liu, Shangmei & Yu, Quanqing & Shen, Weixiang & Xiong, Rui, 2023. "A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models," Applied Energy, Elsevier, vol. 348(C).
- Ruan, Guanqiang & Liu, Zixi & Cheng, Jinrun & Hu, Xing & Chen, Song & Liu, Shiwen & Guo, Yong & Yang, Kuo, 2024. "A deep learning model for predicting the state of energy in lithium-ion batteries based on magnetic field effects," Energy, Elsevier, vol. 304(C).
- Bian, Chong & Duan, Zhiyu & Hao, Yaqian & Yang, Shunkun & Feng, Junlan, 2024. "Exploring large language model for generic and robust state-of-charge estimation of Li-ion batteries: A mixed prompt learning method," Energy, Elsevier, vol. 302(C).
- Stefano Leonori & Luca Baldini & Antonello Rizzi & Fabio Massimo Frattale Mascioli, 2021. "A Physically Inspired Equivalent Neural Network Circuit Model for SoC Estimation of Electrochemical Cells," Energies, MDPI, vol. 14(21), pages 1-29, November.
- Li, Yang & Wang, Shunli & Chen, Lei & Qi, Chuangshi & Fernandez, Carlos, 2023. "Multiple layer kernel extreme learning machine modeling and eugenics genetic sparrow search algorithm for the state of health estimation of lithium-ion batteries," Energy, Elsevier, vol. 282(C).
- Siyi Tao & Bo Jiang & Xuezhe Wei & Haifeng Dai, 2023. "A Systematic and Comparative Study of Distinct Recurrent Neural Networks for Lithium-Ion Battery State-of-Charge Estimation in Electric Vehicles," Energies, MDPI, vol. 16(4), pages 1-17, February.
- Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiao & Fernandez, Carlos, 2023. "A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures," Energy, Elsevier, vol. 273(C).
- Zhang, Ying & Li, Yan-Fu, 2022. "Prognostics and health management of Lithium-ion battery using deep learning methods: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
- Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Li, Huan & Xu, Wenhua & Fernandez, Carlos, 2022. "An optimized relevant long short-term memory-squared gain extended Kalman filter for the state of charge estimation of lithium-ion batteries," Energy, Elsevier, vol. 260(C).
- Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiaoyong & Fernandez, Carlos, 2022. "An optimized long short-term memory-weighted fading extended Kalman filtering model with wide temperature adaptation for the state of charge estimation of lithium-ion batteries," Applied Energy, Elsevier, vol. 326(C).
- Simone Barcellona & Lorenzo Codecasa & Silvia Colnago & Luigi Piegari, 2024. "Open-Circuit Voltage Variation in LiCoO 2 Battery Cycled in Different States of Charge Regions," Energies, MDPI, vol. 17(10), pages 1-17, May.
- Zeng, Qingshun & Shi, Changfeng & Zhu, Wenjun & Zhi, Jiaqi & Na, Xiaohong, 2023. "Sequential data-driven carbon peaking path simulation research of the Yangtze River Delta urban agglomeration based on semantic mining and heuristic algorithm optimization," Energy, Elsevier, vol. 285(C).
- Zhang, Meng & Kang, Guoqing & Wu, Lifeng & Guan, Yong, 2022. "A method for capacity prediction of lithium-ion batteries under small sample conditions," Energy, Elsevier, vol. 238(PC).
- Jiang, Bo & Tao, Siyi & Wang, Xueyuan & Zhu, Jiangong & Wei, Xuezhe & Dai, Haifeng, 2023. "Mechanics-based state of charge estimation for lithium-ion pouch battery using deep learning technique," Energy, Elsevier, vol. 278(PA).
- Molla Shahadat Hossain Lipu & Tahia F. Karim & Shaheer Ansari & Md. Sazal Miah & Md. Siddikur Rahman & Sheikh T. Meraj & Rajvikram Madurai Elavarasan & Raghavendra Rajan Vijayaraghavan, 2022. "Intelligent SOX Estimation for Automotive Battery Management Systems: State-of-the-Art Deep Learning Approaches, Open Issues, and Future Research Opportunities," Energies, MDPI, vol. 16(1), pages 1-31, December.
- Korkmaz, Mehmet, 2024. "A novel approach for improving the performance of deep learning-based state of charge estimation of lithium-ion batteries: Choosy SoC Estimator (ChoSoCE)," Energy, Elsevier, vol. 294(C).
- Wang, Jianfeng & Zuo, Zhiwen & Wei, Yili & Jia, Yongkai & Chen, Bowei & Li, Yuhan & Yang, Na, 2024. "State of charge estimation of lithium-ion battery based on GA-LSTM and improved IAKF," Applied Energy, Elsevier, vol. 368(C).
- Olabi, A.G. & Wilberforce, Tabbi & Sayed, Enas Taha & Abo-Khalil, Ahmed G. & Maghrabie, Hussein M. & Elsaid, Khaled & Abdelkareem, Mohammad Ali, 2022. "Battery energy storage systems and SWOT (strengths, weakness, opportunities, and threats) analysis of batteries in power transmission," Energy, Elsevier, vol. 254(PA).
- He, Lin & Hu, Xingwen & Yin, Guangwei & Wang, Guoqiang & Shao, Xingguo & Liu, Jichao, 2024. "A current dynamics model and proportional–integral observer for state-of-charge estimation of lithium-ion battery," Energy, Elsevier, vol. 288(C).
- Ouyang, Tiancheng & Pan, Mingming & Huang, Youbin & Tan, Xianlin & Qin, Peijia, 2023. "Thermodynamic design and power prediction of a solar power tower integrated system using neural networks," Energy, Elsevier, vol. 278(PA).
- Yao, Fang & He, Wenxuan & Wu, Youxi & Ding, Fei & Meng, Defang, 2022. "Remaining useful life prediction of lithium-ion batteries using a hybrid model," Energy, Elsevier, vol. 248(C).
- Zhang, Xinru & Hou, Lei & Liu, Jiaquan & Yang, Kai & Chai, Chong & Li, Yanhao & He, Sichen, 2022. "Energy consumption prediction for crude oil pipelines based on integrating mechanism analysis and data mining," Energy, Elsevier, vol. 254(PB).
- Wang, Qiao & Ye, Min & Wei, Meng & Lian, Gaoqi & Li, Yan, 2023. "Deep convolutional neural network based closed-loop SOC estimation for lithium-ion batteries in hierarchical scenarios," Energy, Elsevier, vol. 263(PB).
- Li, Chuan & Zhang, Huahua & Ding, Ping & Yang, Shuai & Bai, Yun, 2023. "Deep feature extraction in lifetime prognostics of lithium-ion batteries: Advances, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
- Zhang, Qiang & Wan, Guangwei & Li, Chaoran & Li, Jianke & Liu, Xiaori & Li, Menghan, 2024. "State of charge estimation for Li-ion battery during dynamic driving process based on dual-channel deep learning methods and conditional judgement," Energy, Elsevier, vol. 294(C).
- Jiang, Wei & Wang, Xin & Zhang, Shu, 2023. "Integrating multi-modal data into AFSA-LSTM model for real-time oil production prediction," Energy, Elsevier, vol. 279(C).
- Lian, Gaoqi & Ye, Min & Wang, Qiao & Li, Yan & Xia, Baozhou & Zhang, Jiale & Xu, Xinxin, 2024. "Robust state-of-charge estimation for LiFePO4 batteries under wide varying temperature environments," Energy, Elsevier, vol. 293(C).
- Xiaozhi Gao & Lichi Gao & Hsiung-Cheng Lin & Yanming Huo & Yaheng Ren & Wang Guo, 2022. "Development of MVMD-EO-LSTM Model for a Short-Term Photovoltaic Power Prediction," Energies, MDPI, vol. 15(19), pages 1-15, October.
- Xie, Yanxin & Wang, Shunli & Zhang, Gexiang & Fan, Yongcun & Fernandez, Carlos & Blaabjerg, Frede, 2023. "Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries," Applied Energy, Elsevier, vol. 336(C).
- Uzair Khan & Mohd Tariq & Arif I. Sarwat, 2024. "Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments," Energies, MDPI, vol. 17(22), pages 1-18, November.
- Shahjalal, Mohammad & Roy, Probir Kumar & Shams, Tamanna & Fly, Ashley & Chowdhury, Jahedul Islam & Ahmed, Md. Rishad & Liu, Kailong, 2022. "A review on second-life of Li-ion batteries: prospects, challenges, and issues," Energy, Elsevier, vol. 241(C).