Multi-States Fusion based Internal Short Circuit Fault Diagnostic for Lithium-Ion Battery

With the merits of high energy density and long lifespan, lithium-ion batteries (LIBs) have emerged as the dominant power source for a wide range of industrial applications. However, the safety hazards of LIBs hinder its further promotion and need to be solved urgently. Internal short circuit (ISC) is one of the most critical causes for the dangerous thermal runaway of lithium-ion battery (LIB); thus, the accurate early-stage detection of the ISC failure is critical to improving the safety of LIBs. Motivated by this, this paper proposes a multi-state fusion-based ISC diagnostic method to diagnose the ISC fault quantitatively, with high robustness to the capacity fading. Particularly, a model-switching framework is established to model the electrical characteristic of the LIBs. Within this framework, the battery states are estimated using onboard measured load current and voltage. Then, the estimated multiple states of LIB are fused to estimate the ISC current and ISC resistance, which evaluates the severity of the ISC fault. The proposed method is validated experimentally for the superiority in terms of diagnostic accuracy and robustness to battery degradation.