A combined experimental‐numerical framework for residual energy determination in spent lithium‐ion battery packs

Summary The present research proposes a combined framework that evaluates remaining capacity, material behavior, ions concentration of remaining metals, and current rate of chemical reactions of spent Li‐ion batteries accurately. Voltage, temperature, internal resistance, and capacity were studied during charging and discharging cycles. Genetic programming was applied on the obtained data to develop a model to predict remaining capacity. The results of experimental work and those estimated from model were found to be correlated, confirming the validation of model. Materials structure and electrochemical behavior of electrodes during cycles were studied by cyclic voltammetry, scanning electron microscopy, and energy dispersion spectrum. Key Points (Highlights) To address the problem of recycling of battery packs, a comprehensive framework combining of the experimental and numerical approaches was proposed for the analysis of residual energy of lithium‐ion batteries used in electric vehicles (EVs). Experiments are conducted, and genetic programming is applied based on the obtained data. In addition, scanning electron microscope (SEM) and energy dispersion spectrum (EDS) have been performed for material characteristics. The developed model is best suited to the immediate use in industrial applications to determine recyclability and reusability of the batteries. In addition, the significant changes in the electrode structure and elemental composition are highlighted after 50 cycles The results of cyclic voltammetry coincide with the results of scanning electron microscope (SEM) in understanding the changes happening in the batteries, which can be used as inputs to improve the performance of the model by many folds.