A1-007-DST(50)-US06-FUDS-20120824: Lithium-Ion Battery Test Data for SOC and RUL Modeling

Two A123 LiFePO4 pouch cells were experimentally characterized using low-current open-circuit voltage protocols and dynamic driving cycles across multiple temperatures. The dataset supports a unified framework integrating state-of-charge estimation, degradation modeling, and probabilistic reliability assessment. It was authored by Parisa Mobasheri and last updated on 2026-06-01.

Use Cases

• Train state-of-charge estimators based on open-circuit voltage and Coulomb counting data.
• Model temperature-dependent battery degradation kinetics using Arrhenius-based relationships.
• Perform probabilistic life prediction and reliability assessment based on Weibull survival analysis.
• Validate extended Kalman filter algorithms for SOC estimation under dynamic driving cycles like DST, US06, and FUDS.
• Conduct sensitivity analysis to quantify parameter uncertainty propagation into SOC and RUL predictions.

Strengths

• Experimental results demonstrate voltage estimation errors below 0.02 V, corresponding to approximately 1–2% SOC deviation.
• Data captures significant life divergence between nominally identical cells (≈1000 vs. 200 cycles).
• The 3.8 MB XLSX file contains data from a validated experimental-analytical pipeline.
• Testing includes multiple representative dynamic driving cycles (DST, US06, FUDS) across various temperatures.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (3.8 MB), which may limit the scope of analysis.

Provenance

Source

Parisa Mobasheri via figshare

Collection Method

Experimental characterization of two A123 LiFePO4 pouch cells using low-current OCV protocols and dynamic driving cycles.

Freshness

Last updated 2026-06-01 17:41:43; freshness should be verified.