Fitting OCV Curves with Composite tanh and cosh Functions in PyBaMM

Hello PyBaMM Community,​

I’m exploring methods to model the open-circuit voltage (OCV) versus state of charge (SOC) relationship in lithium-ion batteries. I’ve observed that composite functions incorporating hyperbolic tangent (tanh) and hyperbolic cosine (cosh) terms are often used to capture the nonlinear characteristics of OCV curves, especially the plateau regions and steep transitions.​

I’m interested in understanding how researchers and practitioners arrive at such composite functions:​

  • What is the rationale behind choosing tanh and cosh functions for modeling OCV curves?​
  • Are there standard forms or templates for these composite functions, or are they typically derived empirically based on experimental data?​
  • What methodologies or best practices are recommended for constructing and fitting these functions to experimental OCV data?​

I’m looking to gather insights into the derivation process of these functions

Any guidance, references, or shared experiences would be greatly appreciated.​

Thank you!

Hi,
you might find this helpful.

This is a tool that does OCV fitting and automatically creates a function that you can directly use in PyBaMM.

GitHub - BattModels/Diffthermo_OCV_paper: diffthermo, a python package for thermodynamically consistent OCV model construction

The theory behind this and the composite functions in general is also explained in the corresponding paper:

Open-Circuit Voltage Models Should Be Thermodynamically Consistent | The Journal of Physical Chemistry Letters

Hope this helps.

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