Uncertainty-Aware Simulation of Adaptive Charging for Electric Vehicle Batteries under Ultra-Fast Charging Conditions

This paper investigated the simulated thermal response of an adaptive charging strategy compared with a constant-current baseline for four electric vehicle battery-chemistry configurations. A reduced-order electro-thermal model was implemented to evaluate maximum temperature rise, energy delivered, final state of charge, and a temperature-based stress index over a 15-minute charging interval. A paired Monte Carlo procedure was also considered to examine the sensitivity of the predicted response to variations in electrical resistance, effective thermal capacity, and cooling coefficient. Under the selected nominal model assumptions, adaptive charging reduced the predicted maximum temperature rise for the NMC, NCA, and projected solid-state configurations. For NMC, the maximum temperature rise decreased from approximately 5.80°C to 5.15°C, whereas for NCA it decreased from approximately 5.29°C to 4.68°C. These reductions were accompanied by differences in energy delivery during the fixed charging interval. In contrast, the LFP configuration exhibited no difference between the charging strategies because its simulated state of charge remained below the adaptive controller's activation threshold. The paired uncertainty analysis further indicated that the direction of the predicted thermal-response difference remained consistent for NMC, NCA, and the projected solid-state configuration within the selected parameter ranges. This finding is conditional on the prescribed controller, simplified model structure, and assumed uncertainty distributions. It should not be interpreted as a probability of improved performance in a physical battery system. The principal outcome of this investigation is that the predicted effect of adaptive charging depends on the current-control schedule, charging duration, and assumed electrical and thermal parameters. Reporting temperature rise together with energy delivery and final state of charge provides a more informative comparison than relying on a single thermal indicator. The temperature-based stress index offers an additional means of comparing simulated temperature trajectories, but it does not directly quantify capacity fade or battery lifetime. The present work is exploratory and simulation-based. The model has not been calibrated against experimental measurements, and its constant-voltage approximation and lumped thermal representation limit its physical accuracy. Consequently, the results should be interpreted as comparative numerical observations rather than validated claims concerning battery safety, degradation reduction, or service-life improvement.

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