Battrery-SOC-Kalman

This is the battery soc estimation code for lab EE401

A simple and naive battery modelisation + Kalman filter for state of charge (SoC) estimation

Python implementation

python3 implementation of an extended Kalman filter for state of charge (SoC) estimation of a simulated lithium battery. The model used for the battery is a simple Thevenin model.

To run it just launch:

$> python Python/main.py

Or use any python IDE (spyder/ jupyter notebook) and run the main.py file.

A CC/CV charge and a pulse discharge will be simulated. Then a graph will be displayed showing simulation results. You can play around with the capacity and Thevenin model values in Python/main.py. The charge/discharge protocol can also be changed, values are found in Python/protocol.py.

Dependencies:

- python3
- numpy
- matplotlib