Abstract
This study conducted an experimental study on the external short circuit (ESC) fault characteristics of lithium-ion batteries for electric vehicles. An experimental platform was established to simulate the electrical behavior of lithium batteries during ESC failure using a modified first-order RC model. The model parameters are reidentified by the dynamic neighborhood particle swarm optimization algorithm. An ESC fault diagnosis algorithm based on two-layer model is proposed. The first layer performs initial fault detection and the second layer performs accurate model-based diagnostics. The four new units are shorted to evaluate the proposed algorithm. The results show that the ESC fault can be diagnosed within 5 s, and the error between the model and the measured data is less than 0.36 V. The proposed algorithm can make a correct diagnosis.
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