Development of Novel MSCCCTCV Charging Strategy for Health-Aware Battery Fast Charging Using QOGA Optimization

This research introduces a new charging methodology, the multistep constant-current constant-temperature constant-voltage (MSCCCTCV) strategy. The main objective of this approach is to achieve rapid battery charging while giving utmost importance to maintaining battery longevity. The thermoelectric aging cell model (TEACM) is introduced, which incorporates impedance, thermal, and aging models within a robust semi-empirical framework. The accuracy of voltage detection, current detection, and cycle life prediction by the TEACM was found to be 91%, 97%, and 99%, respectively, as evidenced by experimental results obtained from a cell cycling test bench. A personalized charging strategy is developed by employing a quad-objective genetic algorithm (QOGA) based on the TEACM parameters. The optimization process employed by the QOGA considers the maximum allowable temperature and charging rate values, aiming to minimize charging time, degradation rate, energy loss, and temperature increase. Additionally, this research presents three novel charging strategies based on the number of CC steps employed, namely single-step, dual-step, and triple-step. The findings indicate that implementing the triple-step CCCTCV approach leads to a reduction of 31% in charging time and an enhancement of 66% in cycle life compared to the conventional 1C CC-CV charging technique.