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A method for state-of-charge estimation of lithium-ion batteries based on PSO-LSTM
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“The resulting PSO-LSTM network outperformed others, achieving a 0.43% reduction in MSE for isothermal estimation.”
From Advancements in the estimation of the state of charge of lithium-ion battery: a comprehensive review of traditional and deep learning approaches (2025) · cites this paper as [80]
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Cites
Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318
Greff, K., Srivastava, R. K., Koutnik, J., Steunebrink, B. R., & Schmidhuber, J. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2582924 · Cited by 6,955
IEEE Transactions on Neural Networks and Learning Systems
(2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.5962385 · Cited by 1,184
Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles
Xiong, R., Cao, J., Yu, Q., He, H., & Sun, F. (2017) · IEEE Access · doi:10.1109/access.2017.2780258 · Cited by 1,046
State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network
Yang, F., Li, W., Li, C., & Miao, Q. (2019) · Energy · doi:10.1016/j.energy.2019.03.059 · Cited by 543
State-of-charge estimation of lithium-ion batteries using LSTM and UKF
Yang, F., Zhang, S., Li, W., & Miao, Q. (2020) · Energy · doi:10.1016/j.energy.2020.117664 · Cited by 461
A deep learning method for online capacity estimation of lithium-ion batteries
Shen, S., Sadoughi, M., Chen, X., Hong, M., & Hu, C. K. (2019) · Journal of Energy Storage · doi:10.1016/j.est.2019.100817 · Cited by 407
Data Augmentation for Deep Neural Network Acoustic Modeling
Cui, X., Goel, V., & Kingsbury, B. (2015) · IEEE/ACM Transactions on Audio, Speech, and Language Processing · doi:10.1109/taslp.2015.2438544 · Cited by 376
Online capacity estimation of lithium-ion batteries with deep long short-term memory networks
Li, W., Sengupta, N., Dechent, P., Howey, D. A., Annaswamy, A. M., & Sauer, D. U. (2020) · Journal of Power Sources · doi:10.1016/j.jpowsour.2020.228863 · Cited by 372
Zheng, L., Zhu, J. G., Lu, D. D., Wang, G., & He, T. (2018) · Energy · doi:10.1016/j.energy.2018.03.023 · Cited by 334
A new neural network model for the state-of-charge estimation in the battery degradation process
Kang, L., Zhao, X., & Ma, J. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.01.066 · Cited by 325
Bian, C., He, H., & Yang, S. (2020) · Energy · doi:10.1016/j.energy.2019.116538 · Cited by 284
Jiang, C. F., Wang, S., Wu, B., Fernández, C., Xiong, X., & Coffie-Ken, J. (2020) · Energy · doi:10.1016/j.energy.2020.119603 · Cited by 273
Sun, D., Yu, X., Wang, C., Zhang, C., Huang, R., Zhou, Q., Amietszajew, T., & Bhagat, R. (2021) · Energy · doi:10.1016/j.energy.2020.119025 · Cited by 242
Self-citationChen, J., Feng, X., Jiang, L., & Zhu, Q. (2021) · Energy · doi:10.1016/j.energy.2021.120451 · Cited by 193
Fasahat, M., & Manthouri, M. (2020) · Journal of Power Sources · doi:10.1016/j.jpowsour.2020.228375 · Cited by 178
Ye, M., Guo, H. N., & Cao, B. (2017) · Applied Energy · doi:10.1016/j.apenergy.2016.12.133 · Cited by 175
Ning, B., Cao, B., Wang, B., & Zou, Z. (2018) · Energy · doi:10.1016/j.energy.2018.04.026 · Cited by 123
Data Augmentation for deep neural network acoustic modeling
Cui, X., Goel, V., & Kingsbury, B. E. D. (2014) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2014.6854671 · Cited by 90
Zhao, X., Xuan, D., Zhao, K., & Li, Z.-Z. (2020) · Journal of Energy Storage · doi:10.1016/j.est.2020.101789 · Cited by 86
Liu, Z., Li, Z., Zhang, J., Su, L., & Ge, H. (2019) · Energies · doi:10.3390/en12040757 · Cited by 82
Seo, M., Song, Y., Kim, J., Paek, S. W., Kim, G., & Kim, S. W. (2021) · Energy · doi:10.1016/j.energy.2021.120301 · Cited by 62
Xu, W. Z., Xu, J., & Yan, X. (2019) · Journal of Power Electronics · doi:10.1007/s43236-019-00023-4 · Cited by 61
Liu, S., Cui, N., & Zhang, C. (2017) · Energies · doi:10.3390/en10091345 · Cited by 48
Self-citationA New State of Charge Estimation Method for Lithium-Ion Battery Based on the Fractional Order Model
Liu, S., Dong, X., & Zhang, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2932142 · Cited by 41
Self-citation
Research works printed but not linked: 3
- Snihir, 2005, Battery open-circuit voltage estimation by a method of statistical analysis, J Power Sources, 159, 1484, 10.1016/j.jpowsour.2005.11.090 · DOI · Paper page
- Jiang, 2021, A state-of-charge estimation method of the power lithium-ion battery in complex conditions based on adaptive square root extended Kalman filter, Energy, 219
- Sun, 2020, State of charge estimation for lithium-ion battery based on an Intelligent Adaptive Extended Kalman Filter with improved noise estimator, Energy, 214
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Overview of batteries and battery management for electric vehicles
Liu, W., Placke, T., & Chau, K. T. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.03.016 · Cited by 776
A review on second-life of Li-ion batteries: prospects, challenges, and issues
Shahjalal, M., Roy, P. K., Shams, T., Fly, A., Chowdhury, J. I., Ahmed, M. R., & Liu, K. (2021) · Energy · doi:10.1016/j.energy.2021.122881 · Cited by 520
Cui, Z., Wang, L., Li, Q., & Wang, K. (2021) · International Journal of Energy Research · doi:10.1002/er.7545 · Cited by 392
Gu, X., See, K. W., Li, P., Shan, K., Wang, Y., Zhao, L., Lim, K. C., & Zhang, N. (2022) · Energy · doi:10.1016/j.energy.2022.125501 · Cited by 385
SOC estimation for lithium-ion battery using the LSTM-RNN with extended input and constrained output
Chen, J., Zhang, Y., Wu, J., Cheng, W., & Zhu, Q. (2023) · Energy · doi:10.1016/j.energy.2022.125375 · Cited by 362
Metadata
- Authors
- Ren, X., Liu, S., Yu, X., & Dong, X.
- Affiliations
- Qilu University of Technology (CN)
- Corresponding author
- Liu, Shulin
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 234
- Pages
- 121236
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W3172280330
- Cited by
- 375
- References
- 27
- Citations by year
- 2026: 41 · 2025: 78 · 2024: 108 · 2023: 85 · 2022: 53 · 2021: 9
- FWCI
- 20.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Energy (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Natural Science Foundation of Shandong Province (ZR2020ME206, ZR2020QF064)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- state of charge estimation, lithium-ion batteries, battery management systems, long short-term memory neural network, particle swarm optimization, LSTM hyperparameter optimization, noise injection, interference suppression
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