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http://bura.brunel.ac.uk/handle/2438/23697Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Wang, Z | - |
| dc.contributor.author | Fotouhi, A | - |
| dc.contributor.author | Auger, DJ | - |
| dc.date.accessioned | 2021-12-07T21:19:52Z | - |
| dc.date.available | 2021-12-07T21:19:52Z | - |
| dc.date.issued | 2020-07-20 | - |
| dc.identifier.citation | Wang, Z., Fotouhi, A. and Auger, D.J. (2020) 'State of Charge Estimation in Lithium-Sulfur Cells Using LSTM Recurrent Neural Networks *', 2020 European Control Conference (ECC), St. Petersburg, Russia (Virtual), 12-15 May, pp. 1-7. doi: 10.23919/ecc51009.2020.9143926. | en_US |
| dc.identifier.isbn | 978-3-90714-402-2 | - |
| dc.identifier.isbn | 978-1-7281-8813-3 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/23697 | - |
| dc.format.extent | 1 - 7 (7) | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.rights | © 2020 IEEE. Except where otherwise noted, this item's license is described as Attribution-NonCommercial 4.0 International. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | - |
| dc.source | 2020 European Control Conference (ECC) | - |
| dc.source | 2020 European Control Conference (ECC) | - |
| dc.subject | batteries | en_US |
| dc.subject | training | en_US |
| dc.subject | estimation | en_US |
| dc.subject | temperature measurement | en_US |
| dc.subject | temperature | en_US |
| dc.subject | logic gates | en_US |
| dc.subject | task analysis | en_US |
| dc.title | State of Charge Estimation in Lithium-Sulfur Cells Using LSTM Recurrent Neural Networks * | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.doi | https://doi.org/10.23919/ecc51009.2020.9143926 | - |
| dc.relation.isPartOf | 2020 European Control Conference (ECC) | - |
| pubs.finish-date | 2020-05-15 | - |
| pubs.finish-date | 2020-05-15 | - |
| pubs.publication-status | Published | - |
| pubs.start-date | 2020-05-12 | - |
| pubs.start-date | 2020-05-12 | - |
| Appears in Collections: | Dept of Computer Science Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | 1.21 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License
