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

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...

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Bibliographic Details
Main Authors: Shih-Wei Tan, Sheng-Wei Huang, Yi-Zeng Hsieh, Shih-Syun Lin
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/15/4423
Description
Summary: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.
ISSN:1996-1073