GitHub - ram2424/Performace-Comparison-of-LSTM-GRU-FCN-for-SoC-Estimation

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Name		Name	Last commit message	Last commit date
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LSTM_GRU_SoC_Estimation.ipynb		LSTM_GRU_SoC_Estimation.ipynb
LSTM_GRU_SoC_Estimation_EVOTLDataset.ipynb		LSTM_GRU_SoC_Estimation_EVOTLDataset.ipynb
LSTM_GRU_SoC_IEEEDataset.ipynb		LSTM_GRU_SoC_IEEEDataset.ipynb
Performance_Comparison_of_FCN_LSTM_and_GRU_for_State_of_Charge_Estimation.pdf		Performance_Comparison_of_FCN_LSTM_and_GRU_for_State_of_Charge_Estimation.pdf
Readme.txt		Readme.txt
SOC_Estimation_Final_FCN.ipynb		SOC_Estimation_Final_FCN.ipynb
SoC_Estimation_EditVersion_EvotlDataset.ipynb		SoC_Estimation_EditVersion_EvotlDataset.ipynb
SoC_Estimation_EditVersion_IEEEDataset.ipynb		SoC_Estimation_EditVersion_IEEEDataset.ipynb

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The code files contain python script which uses different neural network algorithms for State of Charge Estimation for Battery Management Systems
Algorithms :
- FCN
- LSTM
- GRU
Datatsets :
- CALCE
https://web.calce.umd.edu/batteries/data.htm
- eVTOL
https://kilthub.cmu.edu/articles/dataset/eVTOL_Battery_Dataset/14226830
- Battery and heating data in Real Drive Cycles
https://ieee-dataport.org/open-access/battery-and-heating-data-real-driving-cycles
- Also find the work Published in IEEE
https://ieeexplore.ieee.org/document/9951916