IDEAS home Printed from https://ideas.repec.org/r/eee/energy/v175y2019icp66-75.html

State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Zhang, Meng & Hu, Tao & Wu, Lifeng & Kang, Guoqing & Guan, Yong, 2021. "A method for capacity estimation of lithium-ion batteries based on adaptive time-shifting broad learning system," Energy, Elsevier, vol. 231(C).
  2. Shuo Sun & Qianli Zhang & Junzhong Sun & Wei Cai & Zhiyong Zhou & Zhanlu Yang & Zongliang Wang, 2022. "Lead–Acid Battery SOC Prediction Using Improved AdaBoost Algorithm," Energies, MDPI, vol. 15(16), pages 1-20, August.
  3. He, Qiang & Yang, Yang & Luo, Chang & Zhai, Jun & Luo, Ronghua & Fu, Chunyun, 2022. "Energy recovery strategy optimization of dual-motor drive electric vehicle based on braking safety and efficient recovery," Energy, Elsevier, vol. 248(C).
  4. Li, Jingmiao & Wang, Jun, 2020. "Forcasting of energy futures market and synchronization based on stochastic gated recurrent unit model," Energy, Elsevier, vol. 213(C).
  5. Li, Marui & Dong, Chaoyu & Xiong, Binyu & Mu, Yunfei & Yu, Xiaodan & Xiao, Qian & Jia, Hongjie, 2022. "STTEWS: A sequential-transformer thermal early warning system for lithium-ion battery safety," Applied Energy, Elsevier, vol. 328(C).
  6. Semeraro, Concetta & Caggiano, Mariateresa & Olabi, Abdul-Ghani & Dassisti, Michele, 2022. "Battery monitoring and prognostics optimization techniques: Challenges and opportunities," Energy, Elsevier, vol. 255(C).
  7. Yang, Fangfang & Zhang, Shaohui & Li, Weihua & Miao, Qiang, 2020. "State-of-charge estimation of lithium-ion batteries using LSTM and UKF," Energy, Elsevier, vol. 201(C).
  8. Abdul Ghani Olabi & Salah Haridy & Enas Taha Sayed & Muaz Al Radi & Abdul Hai Alami & Firas Zwayyed & Tareq Salameh & Mohammad Ali Abdelkareem, 2023. "Implementation of Artificial Intelligence in Modeling and Control of Heat Pipes: A Review," Energies, MDPI, vol. 16(2), pages 1-18, January.
  9. Guo, Ruohan & Shen, Weixiang, 2022. "A data-model fusion method for online state of power estimation of lithium-ion batteries at high discharge rate in electric vehicles," Energy, Elsevier, vol. 254(PA).
  10. 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).
  11. Ma, Wentao & Guo, Peng & Wang, Xiaofei & Zhang, Zhiyu & Peng, Siyuan & Chen, Badong, 2022. "Robust state of charge estimation for Li-ion batteries based on cubature kalman filter with generalized maximum correntropy criterion," Energy, Elsevier, vol. 260(C).
  12. Wenxian Duan & Chuanxue Song & Silun Peng & Feng Xiao & Yulong Shao & Shixin Song, 2020. "An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery," Energies, MDPI, vol. 13(23), pages 1-19, December.
  13. Sun, Li & Li, Guanru & You, Fengqi, 2020. "Combined internal resistance and state-of-charge estimation of lithium-ion battery based on extended state observer," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  14. 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).
  15. Xu, Dongxin & Pan, Yongjun & Zhang, Xiaoxi & Dai, Wei & Liu, Binghe & Shuai, Qi, 2024. "Data-driven modelling and evaluation of a battery-pack system’s mechanical safety against bottom cone impact," Energy, Elsevier, vol. 290(C).
  16. Zheng, Bowen & Deng, Zhichao & Luo, Zhenhao & Mao, Shuoyuan & Ouyang, Minggao & Han, Xuebing & Wang, Hewu & Li, Yalun & Sun, Yukun & Wang, Depeng & Yuan, Yuebo & He, Liangxi & Yang, Zhi & Zhu, Yanlin, 2025. "A comprehensive review of lithium-ion battery modelling research and prospects: in-depth analysis of current research and future directions," Applied Energy, Elsevier, vol. 401(PB).
  17. Guo, Peng & Ma, Wentao & Liu, Xinghua & Chen, Badong, 2025. "Robust SOC estimation of lithium-ion battery combining gated recurrent unit and square root CKF with generalized correntropy," Energy, Elsevier, vol. 338(C).
  18. Vichard, L. & Ravey, A. & Venet, P. & Harel, F. & Pelissier, S. & Hissel, D., 2021. "A method to estimate battery SOH indicators based on vehicle operating data only," Energy, Elsevier, vol. 225(C).
  19. Omid Rezaei & Reza Habibifar & Zhanle Wang, 2022. "A Robust Kalman Filter-Based Approach for SoC Estimation of Lithium-Ion Batteries in Smart Homes," Energies, MDPI, vol. 15(10), pages 1-21, May.
  20. 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).
  21. Donghoon Shin & Beomjin Yoon & Seungryeol Yoo, 2021. "Compensation Method for Estimating the State of Charge of Li-Polymer Batteries Using Multiple Long Short-Term Memory Networks Based on the Extended Kalman Filter," Energies, MDPI, vol. 14(2), pages 1-19, January.
  22. Li, Jiabo & Wang, Xingtong & Tian, Di & Ye, Min & Niu, Yuan, 2025. "State of charge estimation method for lithium-ion battery based on informer model combining time domain and frequency domain attention," Energy, Elsevier, vol. 335(C).
  23. 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).
  24. Lei Pei & Cheng Yu & Tiansi Wang & Jiawei Yang & Wanlin Wang, 2024. "A Training-Free Estimation Method for the State of Charge and State of Health of Series Battery Packs under Various Load Profiles," Energies, MDPI, vol. 17(8), pages 1-20, April.
  25. Shuqing Li & Chuankun Ju & Jianliang Li & Ri Fang & Zhifei Tao & Bo Li & Tingting Zhang, 2021. "State-of-Charge Estimation of Lithium-Ion Batteries in the Battery Degradation Process Based on Recurrent Neural Network," Energies, MDPI, vol. 14(2), pages 1-21, January.
  26. 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).
  27. Li, Feng & Zuo, Wei & Zhou, Kun & Li, Qingqing & Huang, Yuhan & Zhang, Guangde, 2024. "State-of-charge estimation of lithium-ion battery based on second order resistor-capacitance circuit-PSO-TCN model," Energy, Elsevier, vol. 289(C).
  28. Fan, Yuqian & Yan, Chong & Wu, Xiaoying & Li, Yi & Dou, Wenwen & Gao, Guohong & Zhang, Pingchuan & Guan, Quanxue & Tan, Xiaojun, 2025. "Mechanical stress-based state-of-charge estimation for lithium-ion batteries via deep learning techniques," Energy, Elsevier, vol. 326(C).
  29. Jia, Chenyu & Tian, Yukai & Shi, Yuanhao & Jia, Jianfang & Wen, Jie & Zeng, Jianchao, 2023. "State of health prediction of lithium-ion batteries based on bidirectional gated recurrent unit and transformer," Energy, Elsevier, vol. 285(C).
  30. Kurucan, Mehmet & Özbaltan, Mete & Yetgin, Zeki & Alkaya, Alkan, 2024. "Applications of artificial neural network based battery management systems: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  31. Shunli Wang & Pu Ren & Paul Takyi-Aninakwa & Siyu Jin & Carlos Fernandez, 2022. "A Critical Review of Improved Deep Convolutional Neural Network for Multi-Timescale State Prediction of Lithium-Ion Batteries," Energies, MDPI, vol. 15(14), pages 1-27, July.
  32. Guo, Yuanjun & Yang, Zhile & Liu, Kailong & Zhang, Yanhui & Feng, Wei, 2021. "A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system," Energy, Elsevier, vol. 219(C).
  33. 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).
  34. Jie Xing & Peng Wu, 2021. "State of Charge Estimation of Lithium-Ion Battery Based on Improved Adaptive Unscented Kalman Filter," Sustainability, MDPI, vol. 13(9), pages 1-16, April.
  35. Chen, Zheng & Zhao, Hongqian & Shu, Xing & Zhang, Yuanjian & Shen, Jiangwei & Liu, Yonggang, 2021. "Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter," Energy, Elsevier, vol. 228(C).
  36. Bingzi Cai & Mutian Li & Huawei Yang & Chunsheng Wang & Yougen Chen, 2023. "State of Charge Estimation of Lithium-Ion Battery Based on Back Propagation Neural Network and AdaBoost Algorithm," Energies, MDPI, vol. 16(23), pages 1-15, November.
  37. Hu, Chunsheng & Ma, Liang & Guo, Shanshan & Guo, Gangsheng & Han, Zhiqiang, 2022. "Deep learning enabled state-of-charge estimation of LiFePO4 batteries: A systematic validation on state-of-the-art charging protocols," Energy, Elsevier, vol. 246(C).
  38. Qian, Cheng & Guan, Hongsheng & Xu, Binghui & Xia, Quan & Sun, Bo & Ren, Yi & Wang, Zili, 2024. "A CNN-SAM-LSTM hybrid neural network for multi-state estimation of lithium-ion batteries under dynamical operating conditions," Energy, Elsevier, vol. 294(C).
  39. Xinyu Gu & KW See & Yunpeng Wang & Liang Zhao & Wenwen Pu, 2021. "The Sliding Window and SHAP Theory—An Improved System with a Long Short-Term Memory Network Model for State of Charge Prediction in Electric Vehicle Application," Energies, MDPI, vol. 14(12), pages 1-15, June.
  40. Jiang, Han & Yin, Le & Xu, Zihan & Hu, Lizhou & Huang, Wei & Zhao, Yixin, 2025. "A novel hybrid framework for SOC estimation using PatchMixer-LSTM and adaptive UKF," Energy, Elsevier, vol. 335(C).
  41. Li, Yihuan & Li, Kang & Liu, Xuan & Li, Xiang & Zhang, Li & Rente, Bruno & Sun, Tong & Grattan, Kenneth T.V., 2022. "A hybrid machine learning framework for joint SOC and SOH estimation of lithium-ion batteries assisted with fiber sensor measurements," Applied Energy, Elsevier, vol. 325(C).
  42. Wu, Yan & Wang, Tong & Zhu, Keming & Xu, Yingying & Ma, Haoyuan & Luo, Jiayuan & Tang, Xiaoyu & Huang, Yuqi, 2025. "Enhancing cross-temperature state-of-charge estimation accuracy for lithium-ion batteries using multi-physics features and physical guidance," Energy, Elsevier, vol. 333(C).
  43. Li, Renzheng & Wang, Hui & Dai, Haifeng & Hong, Jichao & Tong, Guangyao & Chen, Xinbo, 2022. "Accurate state of charge prediction for real-world battery systems using a novel dual-dropout-based neural network," Energy, Elsevier, vol. 250(C).
  44. Qi, Wei & Qin, Wenhu & Yun, Zhonghua, 2024. "Closed-loop state of charge estimation of Li-ion batteries based on deep learning and robust adaptive Kalman filter," Energy, Elsevier, vol. 307(C).
  45. Feng, Xiong & Chen, Junxiong & Zhang, Zhongwei & Miao, Shuwen & Zhu, Qiao, 2021. "State-of-charge estimation of lithium-ion battery based on clockwork recurrent neural network," Energy, Elsevier, vol. 236(C).
  46. He, Lin & Wang, Yangyang & Wei, Yujiang & Wang, Mingwei & Hu, Xiaosong & Shi, Qin, 2022. "An adaptive central difference Kalman filter approach for state of charge estimation by fractional order model of lithium-ion battery," Energy, Elsevier, vol. 244(PA).
  47. Saleh Mohammed Shahriar & Erphan A. Bhuiyan & Md. Nahiduzzaman & Mominul Ahsan & Julfikar Haider, 2022. "State of Charge Estimation for Electric Vehicle Battery Management Systems Using the Hybrid Recurrent Learning Approach with Explainable Artificial Intelligence," Energies, MDPI, vol. 15(21), pages 1-26, October.
  48. 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).
  49. Shen, Jiangwei & Ma, Wensai & Xiong, Jian & Shu, Xing & Zhang, Yuanjian & Chen, Zheng & Liu, Yonggang, 2022. "Alternative combined co-estimation of state of charge and capacity for lithium-ion batteries in wide temperature scope," Energy, Elsevier, vol. 244(PB).
  50. Sun, Daoming & Yu, Xiaoli & Wang, Chongming & Zhang, Cheng & Huang, Rui & Zhou, Quan & Amietszajew, Taz & Bhagat, Rohit, 2021. "State of charge estimation for lithium-ion battery based on an Intelligent Adaptive Extended Kalman Filter with improved noise estimator," Energy, Elsevier, vol. 214(C).
  51. Liu, Wenxue & Hu, Xiaosong & Zhang, Kai & Xie, Yi & He, Jinsong & Song, Ziyou, 2025. "Enabling high-fidelity electrothermal modeling of electric flying car batteries: A physics-data hybrid approach," Applied Energy, Elsevier, vol. 388(C).
  52. Jiandong Duan & Peng Wang & Wentao Ma & Xinyu Qiu & Xuan Tian & Shuai Fang, 2020. "State of Charge Estimation of Lithium Battery Based on Improved Correntropy Extended Kalman Filter," Energies, MDPI, vol. 13(16), pages 1-18, August.
  53. 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).
  54. Ge, Dongdong & Jin, Guiyang & Wang, Jianqiang & Zhang, Zhendong, 2024. "A novel data-driven IBA-ELM model for SOH/SOC estimation of lithium-ion batteries," Energy, Elsevier, vol. 305(C).
  55. Guo, Shanshan & Ma, Liang, 2023. "A comparative study of different deep learning algorithms for lithium-ion batteries on state-of-charge estimation," Energy, Elsevier, vol. 263(PC).
  56. 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).
  57. Kong, Fanhou & Liang, Xue & Yi, Lanlin & Fang, Xiaohui & Yin, Zhongbin & Wang, Yulong & Zhang, Ruixiang & Liu, Longyang & Chen, Qing & Li, Minghan & Li, Changjiu & Jiang, Hong & Chen, Yongjun, 2021. "Multi-electron reactions for the synthesis of a vanadium-based amorphous material as lithium-ion battery cathode with high specific capacity," Energy, Elsevier, vol. 219(C).
  58. Chen, Junxiong & Feng, Xiong & Jiang, Lin & Zhu, Qiao, 2021. "State of charge estimation of lithium-ion battery using denoising autoencoder and gated recurrent unit recurrent neural network," Energy, Elsevier, vol. 227(C).
  59. Yu He & Norasage Pattanadech & Kasiean Sukemoke & Minling Pan & Lin Chen, 2025. "The State of Health Estimation of Retired Lithium-Ion Batteries Using a Multi-Input Metabolic Gated Recurrent Unit," Energies, MDPI, vol. 18(5), pages 1-21, February.
  60. Zhou, Yanting & Wang, Yanan & Wang, Kai & Kang, Le & Peng, Fei & Wang, Licheng & Pang, Jinbo, 2020. "Hybrid genetic algorithm method for efficient and robust evaluation of remaining useful life of supercapacitors," Applied Energy, Elsevier, vol. 260(C).
  61. Ren, Xiaoqing & Liu, Shulin & Yu, Xiaodong & Dong, Xia, 2021. "A method for state-of-charge estimation of lithium-ion batteries based on PSO-LSTM," Energy, Elsevier, vol. 234(C).
  62. 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).
  63. Wang, Ya-Xiong & Chen, Zhenhang & Zhang, Wei, 2022. "Lithium-ion battery state-of-charge estimation for small target sample sets using the improved GRU-based transfer learning," Energy, Elsevier, vol. 244(PB).
  64. Bian, Chong & He, Huoliang & Yang, Shunkun, 2020. "Stacked bidirectional long short-term memory networks for state-of-charge estimation of lithium-ion batteries," Energy, Elsevier, vol. 191(C).
  65. Liu, Gengfeng & Zhang, Xiangwen & Liu, Zhiming, 2022. "State of health estimation of power batteries based on multi-feature fusion models using stacking algorithm," Energy, Elsevier, vol. 259(C).
  66. 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.
  67. Clerici, Davide, 2025. "POLISOC: A hybrid state of charge estimation algorithm for lithium-ion batteries based on electrical and mechanical measurements," Applied Energy, Elsevier, vol. 401(PC).
  68. Edgar D. Silva-Vera & Jesus E. Valdez-Resendiz & Gerardo Escobar & Daniel Guillen & Julio C. Rosas-Caro & Jose M. Sosa, 2024. "Data-Driven Modeling and Open-Circuit Voltage Estimation of Lithium-Ion Batteries," Mathematics, MDPI, vol. 12(18), pages 1-16, September.
  69. Panagiotis Eleftheriadis & Spyridon Giazitzis & Sonia Leva & Emanuele Ogliari, 2023. "Data-Driven Methods for the State of Charge Estimation of Lithium-Ion Batteries: An Overview," Forecasting, MDPI, vol. 5(3), pages 1-24, September.
  70. Wang, Chu & Dou, Manfeng & Li, Zhongliang & Outbib, Rachid & Zhao, Dongdong & Zuo, Jian & Wang, Yuanlin & Liang, Bin & Wang, Peng, 2023. "Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
  71. Mehta, Rohit & Gupta, Amit, 2024. "Mathematical modelling of electrochemical, thermal and degradation processes in lithium-ion cells—A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  72. Hu, Lipeng & Tang, Jinjun & Xu, Fuqiao & Liang, Xiao, 2025. "SOC prediction for electric buses based on interpretable transformer model: Impact of traffic conditions and feature importance," Energy, Elsevier, vol. 324(C).
  73. Wang, Jun & Cao, Junxing & Yuan, Shan & Cheng, Ming, 2021. "Short-term forecasting of natural gas prices by using a novel hybrid method based on a combination of the CEEMDAN-SE-and the PSO-ALS-optimized GRU network," Energy, Elsevier, vol. 233(C).
  74. Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  75. 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).
  76. Dapai Shi & Jingyuan Zhao & Chika Eze & Zhenghong Wang & Junbin Wang & Yubo Lian & Andrew F. Burke, 2023. "Cloud-Based Artificial Intelligence Framework for Battery Management System," Energies, MDPI, vol. 16(11), pages 1-21, May.
  77. Tian, Jinpeng & Xiong, Rui & Shen, Weixiang & Lu, Jiahuan, 2021. "State-of-charge estimation of LiFePO4 batteries in electric vehicles: A deep-learning enabled approach," Applied Energy, Elsevier, vol. 291(C).
  78. Shu, Xing & Li, Guang & Shen, Jiangwei & Lei, Zhenzhen & Chen, Zheng & Liu, Yonggang, 2020. "An adaptive multi-state estimation algorithm for lithium-ion batteries incorporating temperature compensation," Energy, Elsevier, vol. 207(C).
  79. Liang Zhang & Shunli Wang & Daniel-Ioan Stroe & Chuanyun Zou & Carlos Fernandez & Chunmei Yu, 2020. "An Accurate Time Constant Parameter Determination Method for the Varying Condition Equivalent Circuit Model of Lithium Batteries," Energies, MDPI, vol. 13(8), pages 1-12, April.
  80. Fan, Xinyuan & Zhang, Weige & Zhang, Caiping & Chen, Anci & An, Fulai, 2022. "SOC estimation of Li-ion battery using convolutional neural network with U-Net architecture," Energy, Elsevier, vol. 256(C).
  81. Yi, Yahui & Xia, Chengyu & Shi, Lei & Meng, Leifeng & Chi, Qifu & Qian, Liqin & Ma, Tiancai & Chen, Siqi, 2024. "Lithium-ion battery expansion mechanism and Gaussian process regression based state of charge estimation with expansion characteristics," Energy, Elsevier, vol. 292(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.