PyFDAM is a Python implementation of the Frequency Domain Admittance Method (FDAM), whose purpose is to fit electrochemical models to impedance data and compute its charge/discharge behavior with inverse Laplace transform. FDAM and this code was used to perform the work in modeling electric double layer capacitors in this paper and pseudocapacitors in this paper
This is a very lightweight Python module. In fact, it is essentially a small wrapper to the LMFIT package to do non-linear fitting of impedance data and our own numerical implementation for inverse Laplace transform to perform time-domain "simulations". The theory behind these methods can be found on the previous papers!
If you're on Linux, you can clone this project on the terminal and run the pip install command directly on the source folder
$ git clone https://github.com/muhammadhasyim/pyfdam.git
$ cd pyfdam
$ pip install .If you're on Windows, you can download the ZIP file of this project and extract the contents on some directory. Open either command prompt or Powershell and then go the main folder and type
pip install .All Python dependency should be automatically installed once you run the pip install command. If there's enough demand, I might release this project on PyPi, but we'll see!
On the tutorial folder, there is a Jupyter notebook that would walk you through on how to fit an impedance model onto a mock impedance and galvanostatic discharge data. If you view it from here, it should render as a static page.
I am most maintaining this project and won't be active developing it. However, feel free to contact me via GitHub for any features that you'd like to see.