Prior-based patch-level representation learning for electric vehicle battery state-of-charge estimation across a wide temperature scope

Songtao Ye, and Dou An

Code for our paper that predicts power battery SOC at different temperatures. [pdf]

Estimation of the State of Charge (SOC) of Lithium-ion batteries in a wide temperature scope.

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👌Usage

Step 0: Download the datasets

Download the LG dataset and put its content in the directory dataset/LG-18650HG2/

Step 1: Get the SOC-OCV curves at different temperatures (Already exists in the folder)

run preprocessing/get_SOCOCV.ipynb

Step 2: Fitting the OCV-SOC-Temperature relationship (Already exists in the folder)

run preprocessing/get_SOCOCV.ipynb

**Step 3: Train the model and use **

python train.py

✉️Contact

For any question, you can contact songtaoye9@gmail.com

👍Citation

If you use this code, please cite:

@article{ye2024priorsoc,
        title={Prior-based patch-level representation learning for electric vehicle battery state-of-charge estimation across a wide temperature scope}, 
        author={Ye, Songtao and An, Dou},  
        journal={SCIENCE CHINA Technological Sciences},  
        year={2024},
        doi={https://doi.org/10.1007/s11431-024-2765-2}
}

References

data-driven-modelling-of-li-ion-batteries

battery-state-estimation