Capacity fade diagnosis of lithium ion battery pack in electric vehicle base on fuzzy neural network

The lithium ion battery pack, which is filled with cells, is an important part in electric vehicles (EVs), also the main fault source. The inconsistent cells or the design and assembly fail of the pack could affect its performance and life or even endanger vehicles security in extreme situation, which makes the early fault diagnosis is essential. For further analysis, we introduce an equivalent circuit model (ECM) to identify the cell characteristics parameters, which supports the fault diagnosis by simulating the fault battery performance in dynamic cycle. According the battery working mechanism and the practical experience, via collecting data and preprocessing the typical data, a diagnostic method and model based on fuzzy neural network is proposed to discover the battery pack fault related to irreversible or reversible capacity loss.