Peer-reviewed article · IEEE Access · 2026

Literature-Informed Stochastic Scenario Analysis of Thermal-Runaway Risk During eVTOL Battery Fast Charging

Rodrigo Mollo Furlan · Gabriel Luiz Goulart Rufino Vieira · Lucas Orbolato Carvalho · Daniel Alberto Pamplona · Marcelo Xavier Guterres

Publication

IEEE Access, 14, 129532–129543 (2026). DOI: 10.1109/ACCESS.2026.3725575.

Overview

The study uses a literature-informed Monte Carlo framework to analyze thermal-runaway initiation susceptibility during eVTOL battery fast charging. It evaluates stochastic input distributions, dependence scenarios, structural ablations, convergence, sensitivity, state-of-charge and C-rate interactions, and mitigation trade-offs under explicitly stated scenario assumptions.

Reproducibility and scope

The public code release provides the complete deterministic-seed analysis pipeline, automated tests, reference outputs, and machine-readable citation metadata. The model output is a dimensionless risk multiplier for scenario analysis; it is not a validated regulator-grade probability of battery fire, and the public documentation explicitly preserves the study's external-validity and calibration limitations.

github.com/Orbolato/eVTOL-Battery-Thermal-Runaway-Risk

BibTeX

@article{Furlan2026eVTOLThermalRunaway, author = {Furlan, Rodrigo Mollo and Vieira, Gabriel Luiz Goulart Rufino and Carvalho, Lucas Orbolato and Pamplona, Daniel Alberto and Guterres, Marcelo Xavier}, title = {Literature-Informed Stochastic Scenario Analysis of Thermal-Runaway Risk During eVTOL Battery Fast Charging}, journal = {IEEE Access}, volume = {14}, pages = {129532--129543}, year = {2026}, doi = {10.1109/ACCESS.2026.3725575} }