http://scholars.ntou.edu.tw/handle/123456789/17766
Title: | The Estimation Life Cycle of Lithium-Ion Battery Based on Deep Learning Network and Genetic Algorithm | Authors: | Tan, Shih-Wei Huang, Sheng-Wei Hsieh, Yi-Zeng Lin, Shih-Syun |
Keywords: | STATE-OF-CHARGE;ARCHITECTURE | Issue Date: | Aug-2021 | Publisher: | MDPI | Journal Volume: | 14 | Journal Issue: | 15 | Source: | ENERGIES | Abstract: | This study uses deep learning to model the discharge characteristic curve of the lithium-ion battery. The battery measurement instrument was used to charge and discharge the battery to establish the discharge characteristic curve. The parameter method tries to find the discharge characteristic curve and was improved by MLP (multilayer perceptron), RNN (recurrent neural network), LSTM (long short-term memory), and GRU (gated recurrent unit). The results obtained by these methods were graphs. We used genetic algorithm (GA) to obtain the parameters of the discharge characteristic curve equation. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/17766 | ISSN: | 1996-1073 | DOI: | 10.3390/en14154423 |
Appears in Collections: | 07 AFFORDABLE & CLEAN ENERGY 資訊工程學系 電機工程學系 |
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