https://github.com/bjyurkovich/battery_model_python
https://github.com/bjyurkovich/battery_model_python
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/bjyurkovich/battery_model_python
- Owner: bjyurkovich
- Created: 2017-05-27T03:24:59.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2017-05-27T21:35:29.000Z (about 8 years ago)
- Last Synced: 2025-01-21T06:43:30.400Z (4 months ago)
- Language: Python
- Size: 78.9 MB
- Stars: 0
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Battery Model
This repo contains a battery model of a 15Ah LG Chem Automotive Li-Ion (LMO) battery cell. The model is based on the model derivation from [this work](http://rave.ohiolink.edu/etdc/view?acc_num=osu1281632214).
The model parameters were identified using a subspace technique found [here](https://www.researchgate.net/publication/251589129_Linear_parameter_varying_battery_model_identification_using_subspace_methods). The parameters are simplified in the base model, but can be extended to include, as the paramters can be found in `/data/battery_mappings.mat` which are dependent on current direction and SOC.
## Running the Model
To begin, start your virtual environment:
```bash
virtualenv venv
source venv/bin/activate
pip install -r requirements.txt
```
> If you don't have `virtualenv`, you may need to `pip install virtualenv`.
Then just run the model which runs a simple step profile generated in the file `battery_model.py`:
```bash
python battery_model.py
```
The output is saved in `data/output.mat` and can be imported into MATLAB for plotting and viewing.