Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
73
datasets available to search
ShareScore release 0.9.0
Dataset results
73 results for “lithium-ion”
United States recycled content standards for lithium-ion batteries
Open the record for dataset details and reuse information.
Thermal modeling of a high-energy prismatic lithium-ion battery cell and module based on a new thermal characterization methodology
Open the record for dataset details and reuse information.
State of Health Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy and Backpropagation Neural Network
Open the record for dataset details and reuse information.
A novel liquid cooling plate concept for thermal management of lithium-ion batteries in electric vehicles
Open the record for dataset details and reuse information.
A comparative study between air cooling and liquid cooling thermal management systems for a high-energy lithium-ion battery module
Open the record for dataset details and reuse information.
Multi-objective particle swarm optimization and training of datasheet-based load dependent lithium-ion voltage models
Open the record for dataset details and reuse information.
Experimental and numerical thermal analysis of a lithium-ion battery module based on a novel liquid cooling plate embedded with phase change material
Open the record for dataset details and reuse information.
Model Development for State-of-Power Estimation of Large-Capacity Nickel-Manganese-Cobalt Oxide-Based Lithium-Ion Cell Validated Using a Real-Life Profile
Open the record for dataset details and reuse information.
Figures for Developing an online data-driven approach for prognostics and health management of lithium-ion batteries
Open the record for dataset details and reuse information.
Addendum to "Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset]"
<p>This is an addendum to the previously published dataset with the title "Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset]" (DOI: 10.35097/1947).<br>In the previous publication, the "cell_eisv2.zip" file was incomplete and only contained data for cells P001_1 to P044_2.<br>The fixed "cell_eisv2_fixed.zip" file of this addendum contains data for all 228 cells P001_1 to P076_3.</p>
Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset]
<p>Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies can help to better understand and model degradation and to optimize the operation strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications.<br>To our knowledge, the dataset presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for more than a year under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to some of the cells. The dataset includes result data (such as the remaining usable capacity or impedance measured in check-ups) and raw data (i.e., measurement logs with two-second resolution).<br>The data can be used in a wide range of applications, for example, to model battery degradation, gain insight into lithium plating, optimize operation strategies, or test battery impedance or state estimation algorithms using machine learning or Kalman filtering.</p>
Supporting Data for: Resolving high potential structural deterioration in Ni-rich layered cathode materials for lithium-ion batteries operando
<p>The following file contains supporting data for "Resolving high potential structural deterioration in Ni-rich layered cathode materials for lithium-ion batteries operando" manuscript.</p>
Dataset of 5035 Conductivity Experiments for Lithium-Ion Battery Electrolyte Formulations at Various Temperatures
<p>Dataset containing 5035 Conductivity Experiments for Lithium-Ion Battery Electrolyte Formulations at Various Temperatures which is accopaning the data descriptor publication titled "5035 Conductivity Experiments for Lithium-Ion Battery Electrolyte Formulations at Various Temperatures and their Automated Analysis" by the same authors.</p>
Dataset: Experimental Investigation of Power Available in Lithium-Ion Batteries
<p>Dataset for the paper Experimental Investigation of Power Available in Lithium-Ion Batteries. </p> <p>The paper is available (open access) at <a href="https://doi.org/10.1016/j.jpowsour.2024.235168">https://doi.org/10.1016/j.jpowsour.2024.235168</a> </p> <ul> <li>Battery: Melasta LCO 6.8Ah pouch cell</li> <li>Test: Dynamic load profile followed by a 30-second 10C rate pulse</li> <li>Experiment I: Tests @25°C, 05 fresh cells, 05 repetitions on each cell</li> <li>Experiment II: One-factor-at-time experiment, [50°C, 15°C, 20kPa, 60kPa, 100% SOC, 20% SOC]</li> </ul> <p> </p>
3D lithium-ion battery image for testing P3T-Net
<p>These are the dataset used for training and testing P3T-Net for 3D unpaired domain transfer in .tif format. Images can be directly opened with ImageJ, Avizo, Python, Matlab, etc.</p> <p>Target domain: nano-CT image of a dual-mode scan of Lithium-ion battery cathode (voxel size: 128nm); Source domain: a nano-CT images of a single-mode scan of lithium-ion battery cathode (voxel size: 128nm).</p>
Feature Engineered Dataset from HPPC Files for Lithium-Ion Battery Cells
<p>This dataset contains time-series data from Hybrid Pulse Power Cycle (HPPC) tests of lithium-ion battery cells, specifically designed for evaluating cell performance and degradation over multiple cycles. The dataset originally published by (Popp et al., 2024) includes information from both charge and discharge tests for each cell, with additional engineered features derived from the raw data. The cells in this dataset were evaluated under different States of Health (SoH), providing insights into performance across various degradation levels.</p> <h2>Dataset Overview</h2> <p>The dataset comprises charge and discharge cycles from 256 individual cells. Each test involves the following procedures:</p> <ol> <li>Cells were equilibrated at 25 °C inside a thermal chamber to ensure a stable temperature before testing.</li> <li>Cells were charged using constant current/constant voltage (CC/CV) mode with a charging rate of C/2 and a cutoff current of 98 mA.</li> <li>After a resting period to allow thermal stabilization, the cells were discharged at a rate of C/5 until the voltage dropped to 2.5 V, capturing the full discharge capacity.</li> <li>A second resting period was conducted until the cells reached thermal equilibrium.</li> <li>HPPC cycles were performed at multiple stages of the charge and discharge cycles to assess cell performance at different State of Charge (SOC) levels.</li> </ol> <p>The dataset also includes a micro HPPC cycle performed at every 10% SOC decrement, starting from 100% SOC down to 10% SOC, with a final HPPC test at 0% SOC. Cells were tested using a combination of charge and discharge pulses to simulate real-world usage patterns. All cycles were recorded at 100 Hz for standard charge/discharge cycles and 1 kHz for the HPPC tests, allowing for high-resolution analysis of the cell behavior.</p> <h2>Data Features</h2> <p>The dataset includes the following features recorded by (Popp. et al., 2024) during the tests:</p> <ul> <li><strong>Time</strong>: Timestamp for each data point.</li> <li><strong>ClimaTemp</strong>: Temperature recorded from the climate chamber.</li> <li><strong>I</strong>: Current applied to the cell (in Amps).</li> <li><strong>Itarget</strong>: Setpoint for the applied current (in Amps).</li> <li><strong>P</strong>: Power output of the cell (in Watts).</li> <li><strong>Q</strong>: Total charge accumulated in the cell (in Amp-seconds).</li> <li><strong>Qneg</strong>: Negative charge accumulated (in Amp-seconds).</li> <li><strong>Qpos</strong>: Positive charge accumulated (in Amp-seconds).</li> <li><strong>Temp_Cell</strong>: Temperature measured at the cell (in °C).</li> <li><strong>U</strong>: Cell voltage (in Volts).</li> </ul> <p>In addition to these core features, engineered features have been included to facilitate analysis of battery performance and degradation trends:</p> <ul> <li><strong>Cumulative_Cycles</strong>: Running count of cycles completed by the cell.</li> <li><strong>Avg_Voltage</strong>: The average voltage of the cell up to the current cycle.</li> <li><strong>Capacity_Fade_Rate</strong>: The rate of capacity degradation over time.</li> <li><strong>Avg_Temperature</strong>: Average temperature experienced by the cell up to the current cycle.</li> <li><strong>Temp_Variation</strong>: Maximum difference in cell temperature over time.</li> <li><strong>High_Temp_Flag</strong>: Binary flag indicating whether the cell temperature exceeded 40°C.</li> <li><strong>Internal_Resistance</strong>: Internal resistance of the cell, calculated from voltage and current data.</li> <li><strong>Power_Consumption_Rate</strong>: Rate at which power is consumed by the cell.</li> <li><strong>Energy_Efficiency</strong>: Efficiency of energy storage, calculated from the ratio of positive to negative charge.</li> <li><strong>Rolling_Avg_Voltage</strong>: Rolling average of the cell voltage over recent cycles.</li> <li><strong>Std_Dev_Voltage</strong>: Standard deviation of cell voltage across cycles.</li> <li><strong>Max_Voltage</strong>: Maximum voltage observed during the test.</li> <li><strong>Min_Voltage</strong>: Minimum voltage observed during the test.</li> <li><strong>Dynamic_Resistance</strong>: Resistance change calculated from voltage and current differentials.</li> <li><strong>Impedance</strong>: Impedance calculated from voltage and current changes.</li> <li><strong>Temp_Coefficient</strong>: Rate of change in power with respect to temperature.</li> <li><strong>Thermal_Runaway_Risk</strong>: Flag indicating the potential for thermal runaway conditions.</li> <li><strong>Effective_Capacity</strong>: Net charge retained by the cell after each cycle.</li> <li><strong>Energy_Throughput</strong>: Total energy delivered by the cell over time, calculated from power and time.</li> </ul> <p>This dataset is suitable for research into lithium-ion battery degradation, performance modeling, and State of Health prediction. The engineered features provide a robust foundation for predictive modeling, including the estimation of Remaining Useful Life (RUL) and optimization of battery usage in practical applications.</p> <p>The dataset has been structured for easy integration with machine learning workflows, with all features provided in CSV format for each test cycle.</p> <h3>Citation:</h3> <p>Popp, A., Spaeth, U., & Schmuelling, B. (2024). Samsung INR21700-50E Capacity and HPPC tests (V1.0) [Data set]. 2024 IEEE Transportation Electrification Conference and Expo (ITEC), Rosemont, IL, USA. Zenodo. <a href="https://doi.org/10.5281/zenodo.10891871" target="_new" rel="noopener">https://doi.org/10.5281/zenodo.10891871</a></p>
Dataset: Stack pressure on lithium-ion pouch cells: a comparative study of constant pressure and fixed displacement devices
<p>Dataset for the paper Experimental Investigation of Power Available in Lithium-Ion Batteries.</p> <ul> <li>Battery: Melasta LCO 6.8Ah pouch cell</li> </ul> <p>Static Pressure Loss:</p> <ul> <li>Test 01: Fixed displacement device</li> <li>Test 02: Constant pressure (springs)</li> <li>Test 03: Constant pressure (pneumatic)</li> </ul> <p>Dynamic pressure variation:</p> <ul> <li>Test 04</li> </ul> <p>Spring stiffness investigation:</p> <ul> <li>Test 05</li> </ul> <p> </p>
Diagnosis of lithium-ion batteries degradation with P2D model parameters identification: a case study on low temperature charging
<p>Dataset and code of the equilibrium model. They refer to publication <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.fub.2024.100006" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.fub.2024.100006</span></span></a></p>
Exothermal data from thermal safety assessment of type 21700 lithium-ion batteries with NMC, NCA and LFP cathodes by means of Accelerating Rate Calorimetry (ARC)
<p>Data of safety investigation and thermal abuse behavior of commercial type 21700 LIB cells is provided.</p> <p>It has been acquired with Accelerating Rate Calorimetry (ARC), using a Thermal Hazard Technology type ES ARC.</p> <p>Moreover, thermal abuse was done by means of the so-called Heat-Wait-Seek (HWS) test, at different states of charge (SOC) from 0 to 100.</p> <p>Different cathode chemistries are compared (NMC, NCA and LFP), as well as for NCA chemistry, the high energy (HE) and high power (HP) cell design.</p> <p>For each cell, data includes the exothermal behavior of the cells, which is recorded only when the cell is behaving exothermally in the ARC, above a threshold of 0.02 °C / min.</p> <p>Hence, in the files, time in minutes, temperature on the surface at the center of the cell in °C and the registered temperature rate in °C / min is provided. Cathode chemistry, as well as SOC, is indicated in the file name, each set of parameters has been tested at least twice with another cell, which is indicated with M and consecutive numbering of the test number.</p> <p>This data is supporting this article in the journal Batteries:</p> <p><a href="https://doi.org/10.3390/batteries9050237">https://doi.org/10.3390/batteries9050237</a></p> <p>Additional supporting material to this article are the maximum temperatures for thermal abuse, that are published here:</p> <p><a href="https://doi.org/10.5281/zenodo.7867730">https://doi.org/10.5281/zenodo.7867730</a></p> <p> </p> <p> </p>
Assessing Sustainability Potential of Spent Lithium-ion Battery Mining using Deep Eutectic Solvents
<p>This dataset provides technical advantages/disadvantages, economic inputs/outputs, and life cycle environmental impacts of solvometallurgy (deep eutectic solvents), pyrometallurgy, and hydrometallurgy systems for critical metals recycling from spent lithium-ion battery.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.