ArpanBiswas99 / Battery-State-of-Charge-Estimation

This repository contains code for estimating the State of Charge (SoC) of LG HG2 batteries using Fully Connected Network (FCN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) models along with optuna based hyperparameter tuning.

Date Created 2024-01-03 (12 months ago)

Commits 61 (last one 11 months ago)

Stargazers 27 (0 this week)

Watchers 1 (0 this week)

Forks 1

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RepositoryStats indexes 598,732 repositories, of these ArpanBiswas99/Battery-State-of-Charge-Estimation is ranked #584,215 (2nd percentile) for total stargazers, and #546,953 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #17,042/17,660.

ArpanBiswas99/Battery-State-of-Charge-Estimation is also tagged with popular topics, for these it's ranked: deep-neural-networks (#634/636), cnn (#552/557)

All Topics

cnn dnn fcn lstm optuna battery state-of-charge deep-neural-networks lstm-neural-networks lithium-ion-batteries

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61 commits on the default branch (main) since jan '22

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updated: 2024-12-11 @ 05:03pm, id: 738538197 / R_kgDOLAUy1Q