Battery diagnosis for electrical vehicles through semi-physical fuzzy models

An intelligent model of a Li-Ion battery for electrical vehicles is proposed that allows for a fast battery health evaluation without the need of removing the battery from the vehicle. The only data needed for performing the condition monitoring are logged performance records (currents and voltages) that are commonly available at Battery Management Systems. The model comprises a combination of differential equations and fuzzy rule-based systems, these last being embedded as non-linear blocks in the differential equations. Fuzzy rules are learnt from data with the help of metaheuristics and fine tuned with gradient descent algorithms. A TensorFlow\texttrademark implementation of the learning algorithm has been developed that takes advantage of the numerical processing capabilities of a massively parallel GPU and improves the learning speed by a high margin.