"Experimental Benchmark of Commercial 18650 Energy Storage Technologies: Li-Ion, Na-Ion, HSC, and EDLC"

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Authors: Fabio Corti, Fabio Canzanella, Gabriele Patrizi, Alberto Reatti, Lorenzo Ciani
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Abstract

"This dataset contains the raw experimental measurements used for the volumetric benchmarking of commercial 18650 energy storage technologies. The study compares five distinct chemistries: Lithium-Ion (NMC and LFP), Sodium-Ion (Na-Ion), Hybrid Supercapacitors (HSC), and Electric Double Layer Capacitors (EDLC).The data is organized according to the three main testing campaigns reported in the reference paper:Electrochemical Impedance Spectroscopy (EIS):The dataset includes impedance spectra measured across a frequency range from 10 mHz to 10 kHz. Measurements were conducted in a climatic chamber at five temperature steps: -10\u00b0C, +5\u00b0C, +25\u00b0C, +35\u00b0C, and +50\u00b0C. These files are essential for analyzing internal resistance (ESR) variations and equivalent circuit parameters under varying environmental conditions.High-Rate Discharge Profiles:Time-domain voltage curves obtained under constant current (CC) discharge at various C-rates are provided. The tests cover currents up to the maximum continuous ratings specified by datasheets (e.g., 10A, 20A, 30A), allowing for the evaluation of actual energy density and voltage sag under high-power stress.Thermal Stability Characterization:Synchronized with the discharge profiles, the dataset reports the surface temperature evolution of the cells during intensive cycling. The data highlight the temperature rise from rest to cut-off, demonstrating the thermal behavior and limits of each technology within the identical 18650 volume.This dataset is suitable for validating electro-thermal models, parameterizing equivalent circuits, and benchmarking emerging post-Lithium technologies such as Sodium-Ion."

Fields of Study & Subjects

Advanced Battery Technologies Research Advancements in Battery Materials Electric and Hybrid Vehicle Technologies

Publication details

Journal / source
IEEE DataPort
Publication date
28 January 2026
Document type
Dataset