A method for state of energy estimation of lithium-ion batteries based on neural network model
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
SOE estimation algorithms that extract the relationship between SOC and SOE had accuracy totally dependent on estimated SOC results, and their estimated SOE results were merely verified at load current no more than 1.0 C.
“However, the SOE estimat ion accuracy of these algorithms were totally dependent on the estimated SOC results, and the estimated SOE results were merely verified at load current of no mo re than 1.0 C.”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [15]
All above-mentioned research works only focused on SOE estimation and did not involve prediction of voltage responses of batteries; in online SOE estimators, voltage responses were taken as input factors.
“Last but not least, unfortunately, all of the above-mentioned research works only focused on the estimat ion of SOE but did not involve the prediction of the voltage responses of batteries: in the online SOE estimators [15][16][17][18][19][20][21], the voltage responses were taken as input factors.”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [15]
Cites
Ng, K. S., Moo, C.-S., Chen, Y.-P., & Hsieh, Y.-C. (2009) · Applied Energy · doi:10.1016/j.apenergy.2008.11.021 · Cited by 1,636 · see citing works
State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF
Charkhgard, M., & Farrokhi, M. (2010) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2010.2043035 · Cited by 779 · see citing works
Zou, Y., Hu, X., Ma, H., & Li, S. E. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.09.146 · Cited by 723 · see citing works
Wavelet neural networks for function learning
Zhang, J., Walter, G. G., Miao, Y., & Lee, W. (1995) · IEEE Transactions on Signal Processing · doi:10.1109/78.388860 · Cited by 721 · see citing works
Sun, F., Hu, X., Zou, Y., & Li, S. (2011) · Energy · doi:10.1016/j.energy.2011.03.059 · Cited by 614 · see citing works
Support Vector Machines Used to Estimate the Battery State of Charge
Álvarez Antón, J. C., García Nieto, P. J., Blanco Viejo, C., & Vilán Vilán, J. A. (2013) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2013.2243918 · Cited by 512 · see citing works
Determination of state-of-charge and state-of-health of batteries by fuzzy logic methodology
Salkind, A. J., Fennie, C., Singh, P., Atwater, T., & Reisner, D. E. (1999) · Journal of Power Sources · doi:10.1016/s0378-7753(99)00079-8 · Cited by 457 · see citing works
A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries
He, Y., Liu, X., Zhang, C., & Chen, Z. (2012) · Applied Energy · doi:10.1016/j.apenergy.2012.08.031 · Cited by 276 · see citing works
Self-citationFathabadi, H. (2014) · Energy · doi:10.1016/j.energy.2014.04.046 · Cited by 261 · see citing works
Zhong, L., Zhang, C., He, Y., & Chen, Z. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.08.008 · Cited by 247 · see citing works
Self-citationEnergy-Optimal Control of Plug-in Hybrid Electric Vehicles for Real-World Driving Cycles
Stockar, S., Marano, V., Canova, M., et al. (2011) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2011.2158565 · Cited by 237 · see citing works
Liu, X., Chen, Z., Zhang, C., & Wu, J. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.02.072 · Cited by 235 · see citing works
Self-citationWaag, W., & Sauer, D. U. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.05.001 · Cited by 216 · see citing works
A method for joint estimation of state-of-charge and available energy of LiFePO4 batteries
Wang, Y., Zhang, C., & Chen, Z. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.08.081 · Cited by 200 · see citing works
Self-citationEnhanced sample entropy-based health management of Li-ion battery for electrified vehicles
Hu, X., Li, S. E., Jia, Z., & Egardt, B. (2014) · Energy · doi:10.1016/j.energy.2013.11.061 · Cited by 187 · see citing works
Zhang, W., Shi, W., & Ma, Z. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.04.148 · Cited by 178 · see citing works
Liu, X., Wu, J., Zhang, C., & Chen, Z. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.07.107 · Cited by 176 · see citing works
Self-citationMethod for estimating capacity and predicting remaining useful life of lithium-ion battery
Hu, C. K., Jain, G., Tamirisa, P. A., & Gorka, T. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.03.086 · Cited by 162 · see citing works
Guenther, C., Schott, B., Hennings, W., Waldowski, P., & Danzer, M. A. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.02.041 · Cited by 157 · see citing works
Hausmann, A., & Depcik, C. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.01.174 · Cited by 145 · see citing works
Yi, J., Kim, U., Shin, C., Han, T., & Park, S. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.02.085 · Cited by 122 · see citing works
Kang, J., Yan, F., Zhang, P., et al. (2014) · Energy · doi:10.1016/j.energy.2014.04.038 · Cited by 108 · see citing works
Mamadou, K., Lemaire, E., Delaille, A., Riu, D., Hing, S. E., & Bultel, Y. (2012) · Journal of The Electrochemical Society · doi:10.1149/2.075208jes · Cited by 73 · see citing works
Shen, W. (2006) · Energy Conversion and Management · doi:10.1016/j.enconman.2006.06.023 · Cited by 70 · see citing works
PHIL Implementation of Energy Management Optimization for a Parallel HEV on a Predefined Route
Kermani, S., Trigui, R., Delprat, S., et al. (2011) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2011.2107534 · Cited by 65 · see citing works
Low-temperature electrochemical performances of LiFePO4 cathode materials for lithium ion batteries
Wang, F., Chen, J., Tan, Z., Wu, M., Yi, B., Su, W., Wei, Z., & Liu, S. (2014) · Journal of the Taiwan Institute of Chemical Engineers · doi:10.1016/j.jtice.2014.02.013 · Cited by 38 · see citing works
Liu, X. T., Wu, J., Zhang, C. B., & Chen, Z. H. (2014) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.535.167 · Cited by 7 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
State estimation for advanced battery management: Key challenges and future trends
Hu, X., Feng, F., Liu, K., Zhang, L., Xie, J., & Liu, B. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109334 · Cited by 857 · see citing works
Wei, J., Dong, G., & Chen, Z. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2782224 · Cited by 643 · see citing works
Li, K., Wei, F., Tseng, K. J., & Soong, B.-H. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2779411 · Cited by 160 · see citing works
Dong, G., Chen, Z., Wei, J., Zhang, C., & Wang, P. (2016) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.10.011 · Cited by 139 · see citing works
Self-citationNovel methods for estimating lithium-ion battery state of energy and maximum available energy
Zheng, L., Zhu, J., Wang, G., He, T., & Wei, Y. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.06.031 · Cited by 92 · see citing works
Battery States Monitoring for Electric Vehicles Based on Transferred Multi-Task Learning
Che, Y., Zheng, Y., Wu, Y., Lin, X., Li, J., Hu, X., & Teodorescu, R. (2023) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2023.3260466 · Cited by 45 · see citing works
Waseem, M., Huang, J., Wong, C.-N., & Lee, C. K. M. (2023) · Mathematics · doi:10.3390/math11204263 · Cited by 26 · see citing works
- Authors
- Dong, G., Zhang, X., Zhang, C., & Chen, Z.
- Affiliations
- University of Science and Technology of China (CN)
- Corresponding author
- Chen, Zonghai
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2015-10
- Volume
- 90
- Pages
- 879-888
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W1145556568
- Cited by
- 187
- References
- 27
- Citations by year
- 2026: 10 · 2025: 14 · 2024: 17 · 2023: 26 · 2022: 23 · 2021: 16 · 2020: 15 · 2019: 18 · 2018: 12 · 2017: 18 · 2016: 14 · 2015: 4
- FWCI
- 16.51
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Energy (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Natural Science Fund of China (61375079)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Keywords
- lithium-ion batteries, state of energy estimation, wavelet neural network, battery modeling, lithium iron phosphate batteries, electric vehicles, battery management systems, terminal voltage, measurement noise reduction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
