State of charge estimation of lithium-ion battery using denoising autoencoder and gated recurrent unit recurrent neural network
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DOI: 10.1016/j.energy.2021.120451
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- 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.
- Huang, Haichi & Bian, Chong & Wu, Mengdan & An, Dong & Yang, Shunkun, 2024. "A novel integrated SOC–SOH estimation framework for whole-life-cycle lithium-ion batteries," Energy, Elsevier, vol. 288(C).
- Semeraro, Concetta & Caggiano, Mariateresa & Olabi, Abdul-Ghani & Dassisti, Michele, 2022. "Battery monitoring and prognostics optimization techniques: Challenges and opportunities," Energy, Elsevier, vol. 255(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.
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- 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).
- 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).
- Takyi-Aninakwa, Paul & Wang, Shunli & Liu, Guangchen & Bage, Alhamdu Nuhu & Bobobee, Etse Dablu & Appiah, Emmanuel & Huang, Qi, 2024. "Enhanced extended-input LSTM with an adaptive singular value decomposition UKF for LIB SOC estimation using full-cycle current rate and temperature data," Applied Energy, Elsevier, vol. 363(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).
- 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.
- 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).
- 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).
- Yan Cheng & Xuesen Zhang & Xiaoqiang Wang & Jianhua Li, 2022. "Battery State of Charge Estimation Based on Composite Multiscale Wavelet Transform," Energies, MDPI, vol. 15(6), pages 1-16, March.
- 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).
- 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).
- 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).
- 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).
- Liu, Yongjie & Huang, Zhiwu & Wu, Yue & Yan, Lisen & Jiang, Fu & Peng, Jun, 2022. "An online hybrid estimation method for core temperature of Lithium-ion battery with model noise compensation," Applied Energy, Elsevier, vol. 327(C).
- 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).
- Li, Guannan & Li, Fan & Ahmad, Tanveer & Liu, Jiangyan & Li, Tao & Fang, Xi & Wu, Yubei, 2022. "Performance evaluation of sequence-to-sequence-Attention model for short-term multi-step ahead building energy predictions," Energy, Elsevier, vol. 259(C).
- Wang, Xiaofei & Sun, Quan & Kou, Xiao & Ma, Wentao & Zhang, Hong & Liu, Rui, 2022. "Noise immune state of charge estimation of li-ion battery via the extreme learning machine with mixture generalized maximum correntropy criterion," Energy, Elsevier, vol. 239(PD).
- He, Xitian & Sun, Bingxiang & Zhang, Weige & Su, Xiaojia & Ma, Shichang & Li, Hao & Ruan, Haijun, 2023. "Inconsistency modeling of lithium-ion battery pack based on variational auto-encoder considering multi-parameter correlation," Energy, Elsevier, vol. 277(C).
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Keywords
State of charge estimation; Lithium-ion battery; Denoising autoencoder; Gated recurrent unit; Recurrent neural network; Electric vehicle;All these keywords.
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