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  1. National Taiwan Ocean University Research Hub
  2. 電機資訊學院
  3. 電機工程學系
請用此 Handle URI 來引用此文件: 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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