| description abstract | This paper proposes rapid and accurate short circuit estimation under resting condition using joint moving horizon estimation (MHE). The use of lithium-ion batteries (LiBs) in electric vehicles (EVs) has been increasing, leading to heightened concerns regarding the safety of LiBs. Detecting a short circuit, which is a major cause of safety incidents, is challenging when it is in its early stages. Therefore, short circuits should be detected swiftly and accurately to prevent thermal runaway and potential fires, property damage, injuries, and mortalities. During leak testing of new cells or often an EV crash, applied current may be zero and parameters unknown. The presented work addresses these challenges through the application of a joint MHE approach, to estimate both short circuit current and battery capacity. The proposed approach is evaluated through extensive simulations involving various short circuit scenarios and is compared to a joint extended Kalman filter and joint unscented Kalman filter. Experimental data are also used to validate the effectiveness of states and parameters estimation. | |
