iTransformer Network Based Approach for Accurate Remaining Useful Life Prediction in Lithium-Ion Batteries

Electric vehicles (EVs) are paving the way toward a sustainable future by reducing carbon footprints and gaining widespread global acceptance; predicting the EV battery’s remaining useful life (RUL) is crucial. As the Li-ion batteries degrade and lose lithium and active material, managing the battery’s state of health and charge is necessary to prevent it from reaching its End of Life (EOL). This paper explores a unique application of the …