Data for study: Methods for State of Charge Estimation of Latent Thermal Energy Storage Leveraging the Supercooling Phenomenon

1. Journal article: Methods for State of Charge Estimation of Latent Thermal Energy Storage Leveraging the Supercooling Phenomenon2. DOI: https://doi.org/10.5281/zenodo.21474365 3. Contact information Name: Alfons Vaclavik Institution: VSB-Technical University of Ostrava E-mail: [e-mail] ORCID: https://orcid.org/0009-0007-8783-6642 4. Dataset archiving (publication) date: 2026-07-22 5. Place of archiving (publication): Ostrava, Czechia 6. Dataset description: original data from original research within the project Research Platform forDigital Transformation and Society 5.0. PCM-TES thermal energy storage dataset - experimental dataset from a phase-change-material thermalenergy storage (PCM-TES) unit, instrumented with a dense multi-line temperature sensor grid. The datasupports research on real-time state-of-charge (SoC) estimation and sensor selection for thermalstorage control. Context and experiment:The storage unit is a vertical boiler (1800 x 400 x 140 mm) filled with a sodium-acetate-trihydrate-basedphase-change material and charged/discharged through a heat-transfer-fluid (HTF) circuit. Temperature ismeasured on a grid of 5 vertical lines x 20 positions = 100 channels (naming conventionline{i}_s{j}_temperature, i = 1..5, j = 0..19). Positions s0..s7 sit in the air/paraffin layer and areexcluded from modelling; s8..s19 are the usable channels. Each experiment follows a PLC-controlled cycle of heating, soak, and cooling phases (seeplc_step_codes.md). Sampling interval is 10 s. Alongside the PCM temperatures, each record contains HTFsignals (Temp_IN, Temp_OUT, flow_rate, Power), the cumulative calorimeter Energy, control states, andthe reproducible target column E_extractable_kWh (energy still extractable until a 30 °C cutoff). Package structure (files and folders): readme.txt This file - introduction, context, experiment description, citation. LICENSE, CITATION.cff Licence terms (CC BY 4.0) and formal citation metadata. data/ 97 CSV files of the new dataset with a unified column format. historic/ 53 CSV files of the historic dataset (v9-processed; ~116 channels incl. line3 s20..s35; includes the E_extractable_kWh target). Measured with the older, lower-resolution system - generally lower data quality. historic/schema.json Column description specific to the historic dataset (includes E_meas_kWh, cum_wall_loss_kWh, E_extractable_kWh). measurements.csv Per-experiment metadata for the new dataset: identifier, series, target temperature, soak duration, start timestamp, run length, peak energy, flag, notes. historic_measurements.csv Per-experiment metadata for the historic dataset (identifier, target, soak, start timestamp, run length, peak energy, quality flag, notes). schema.json Description of all new-dataset CSV columns incl. units, calibration constants, and the line{i}_s{j}_temperature naming convention. sensor_topology.json Map of the 100 sensor positions (line, height, coordinates in mm). loss_model_params.json Loss-model calibration parameters (UA_wall, UA_total, C_eff, T_cut) with reference to methodology v9. loeo_splits.json Canonical Leave-One-Experiment-Out 97-fold split for reproducible model comparison. tl_calibration.csv Per-triplet Q_standby, delta-T, UA values used to derive the loss parameters. scripts/compute_extractable.py Reproducible script that recomputes E_extractable_kWh from the raw signals. plc_step_codes.md Decoding table for the PLC state-machine Step codes. docs/infrastructure.pdf Hardware infrastructure description, instrument list and calibration uncertainties. docs/Zemanek_2026_ATE_PCM_TES_evaluation.pdf Related publication (Applied Thermal Engineering 2026, DOI 10.1016/j.applthermaleng.2026.131927) describing the measurement infrastructure and showing selected measurements. docs/baseline_results.md Reference Ridge LOEO result (RMSE ~ 0.954 kWh) as a benchmark. Series in the new dataset:- CH (77) - standard charging with an active soak (> 0 min).- PR (9) - pre-melt / no-soak baseline (0 min), covering 40-90 °C.- LS (5) - long-soak experiments.- TL (9) - thermal-loss triplets (ref / sPump / bezPump) at 60/75/85 °C. Three flagged experiments (CH30, CH43, and the TL02b sPump run) are excluded from data/ and from allLOEO folds. Historic dataset (historic/):The 53 historic experiments were recorded with an older measurement system (3/4" B-Meters GSD8 flowmeter, lower resolution) and are of generally lower data quality than the new dataset - this isinherent to the legacy hardware and cannot be corrected retrospectively. They are v9-processed and doinclude the E_extractable_kWh target plus the intermediate E_meas_kWh and cum_wall_loss_kWh columns,and have ~116 temperature channels (line 3 is extended to s35). Column semantics are inhistoric/schema.json; per-experiment metadata is in historic_measurements.csv. The canonical LOEO split(loeo_splits.json) covers the new dataset only. Reproducing the target: cd scripts python compute_extractable.py ../data/CH01_35C_60min.csv --check -> max|stored - recomputed| = 0.000000 kWhThe script reads calibration constants from loss_model_params.json and reproduces the storedE_extractable_kWh column exactly. How to cite:Please cite the dataset using the metadata in CITATION.cff. Suggested form: Zemanek, J. (2026). PCM-TES thermal energy storage dataset: multi-line temperature sensing for real-time state-of-charge estimation (v1.0.0) [Data set]. VSB - Technical University of Ostrava. https://doi.org/10.5281/zenodo.21474365. Licensed under CC BY 4.0. Related publication:The measurement infrastructure and selected measurements are described in the accompanying paperdocs/Zemanek_2026_ATE_PCM_TES_evaluation.pdf: Zemanek, J., Vaclavik, A., Hercik, R., Byrtus, R., Machacek, Z., Schwar, F., Walter, M., Martinek, R., Hameed, I. A., & Koziorek, J. (2026). Experimental evaluation of a modular phase-change material-based thermal energy storage system. Applied Thermal Engineering, 302, 131927. https://doi.org/10.1016/j.applthermaleng.2026.131927Please cite it alongside this dataset when referring to the hardware setup. Licence:Released under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence - see LICENSE. 7. Funding: This work was supported by the European Regional Development Fund under the projectResearch Platform for Digital Transformation and Society 5.0 CZ.02.01.01/00/23_021/0012599 withinthe Jan Amos Komensky Operational Program supported by the Ministry of Education, Youth and Sportsand co-financed by the European Union.