Research papers · Posted 2026.03.24 · Preprint
SynForceNet: A Force-Driven Global-Local Latent Representation Framework for Lithium-Ion Battery Fault Diagnosis
SynForceNet: A Force-Driven Global-Local Latent Representation Framework for Lithium-Ion Battery Fault Diagnosis
Overview
SynForceNet combines one-class anomaly detection, physical constraints and neural-dynamics-inspired representations for battery faults. Real electric-vehicle data are used to evaluate fault discrimination, normal-state boundaries and robustness of latent representations.
Version: v1