Fault detection of cylindrical lithium-ion battery under Markov switching

Fault detecting is crucial for the safety of the lithium-ion battery. This is because thermal fault and sensor fault are the most common fault in battery, and it may be catastrophic. This study explores a novel fault detection scheme for the cylindrical lithium-ion battery. In this scheme, for the modeling simplicity and physical realism, an electrothermal model is adopted to describe the cell’s thermal behaviors. Specifically, based on the uncertainties and mode switching, this scheme proposed an interval filter to estimate the surface temperature of cell. Furthermore, upper and lower bounds of surface temperature estimates are established using interval filters and information of uncertainty. In addition, an effective method based on \(L_{\infty }\) $L_{\infty }$ norm is proposed to measure the effect of uncertainty. Finally, we perform simulation studies on the proposed scheme, verifying the potential of our method in thermal fault detection.