Dataset: Practical considerations and limitations of online EIS-based battery internal temperature estimation in traction applications
Description
This research aims to find an universally applicable impedance feature and frequency range for electrochemical impedance spectroscopy (EIS)-based internal cell temperature estimation independent of of cell capacity and chemistry. Based on this meta-analysis of 68 publications comprising 83 cells, extended by our own measurements, we propose the impedance phase, evaluated at frequencies between 100 Hz and 1 kHz, as an optimal estimator for internal cell temperature. This repository contains three datasets of battery EIS data and derived parameters compiled from multiple published studies and our own experimental data: 1. Dataset A: Temperature sensitivities of 86 EIS-based internal cell temperature estimators 2. Dataset B: Nyquist curve features of 44 cells 3. EIS: EIS measurements from six cells as a function of temperature For detailed information about data structure, experimental protocols, and data processing methodologies, refer to the README.md file included with the dataset. Corresponding publication: https://doi.org/10.1016/j.jpowsour.2025.239111
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Institutions
- Universitat Bayreuth Fakultat fur Ingenieurwissenschaften
- Infineon Technologies AG