Energies (Jul 2021)

The Estimation Life Cycle of Lithium-Ion Battery Based on Deep Learning Network and Genetic Algorithm

  • Shih-Wei Tan,
  • Sheng-Wei Huang,
  • Yi-Zeng Hsieh,
  • Shih-Syun Lin

DOI
https://doi.org/10.3390/en14154423
Journal volume & issue
Vol. 14, no. 15
p. 4423

Abstract

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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.

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