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http://bura.brunel.ac.uk/handle/2438/23697| Title: | State of Charge Estimation in Lithium-Sulfur Cells Using LSTM Recurrent Neural Networks * |
| Authors: | Wang, Z Fotouhi, A Auger, DJ |
| Keywords: | batteries;training;estimation;temperature measurement;temperature;logic gates;task analysis |
| Issue Date: | 20-Jul-2020 |
| Publisher: | IEEE |
| 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. |
| URI: | https://bura.brunel.ac.uk/handle/2438/23697 |
| DOI: | https://doi.org/10.23919/ecc51009.2020.9143926 |
| ISBN: | 978-3-90714-402-2 978-1-7281-8813-3 |
| Appears in Collections: | Dept of Computer Science Research Papers |
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