Physics-based battery model parameterization from impedance data
by The Electrochemical Society, Gamry Instruments, BioLogic, EL-Cell · Physics WorldJoin the audience for a live webinar at 3 p.m. GMT/10 a.m. EST on 21 January 2026 Discover the role of impedance analysis in advancing battery-model development
Want to take part in this webinar?
Electrochemical impedance spectroscopy (EIS) provides valuable insights into the physical processes within batteries – but how can these measurements directly inform physics-based models? In this webinar, we present recent work showing how impedance data can be used to extract grouped parameters for physics-based models such as the Doyle–Fuller–Newman (DFN) model or the reduced-order single-particle model with electrolyte (SPMe).
We will introduce PyBaMM (Python Battery Mathematical Modelling), an open-source framework for flexible and efficient battery simulation, and show how our extension, PyBaMM-EIS, enables fast numerical impedance computation for any implemented model at any operating point. We also demonstrate how PyBOP, another open-source tool, performs automated parameter fitting of models using measured impedance data across multiple states of charge.
Battery modelling is challenging, and obtaining accurate fits can be difficult. Our technique offers a flexible way to update model equations and parameterize models using impedance data.
Join us to see how our tools create a smooth path from measurement to model to simulation.
An interactive Q&A session follows the presentation.
Want to take part in this webinar?
Noël Hallemans is a postdoctoral research assistant in engineering science at the University of Oxford, where he previously lectured in mathematics at St Hugh’s College. He earned his PhD in 2023 from the Vrije Universiteit Brussel and the University of Warwick, focusing on frequency-domain, data-driven modelling of electrochemical systems.
His research at the Battery Intelligence Lab, led by Professor David Howey, integrates electrochemical impedance spectroscopy (EIS) with physics-based modelling to improve understanding and prediction of battery behaviour. He also develops multisine EIS techniques for battery characterisation during operation (for example, charging or relaxation).