Multi-Fault Diagnosis of Interacting Multiple Model Batteries Based on Low Inertia Noise Reduction

In view of the problems declined estimation and diagnostic accuracy, as well diagnosis delay caused by fixed model transformation probability interacting multiple (IMM) fault algorithm, an IMM algorithm based on low inertia noise reduction (LN-IMM) was presented in this paper. The proposed realized multi-fault lithium-ion batteries combination with strong tracking Kalman filter (STKF). non-model stage, a transition correction function constructed using difference n-th order to suppress effect accuracy algorithm. jump threshold introduced reduce when matched switched quick transformation. Accordingly, final experiment proved that LN-IMM-STKF efficiently completed state improved faults while reducing attaining accurate detection rapid separation battery information.