Multi-Objective and Dynamic Optimization on Fast Charging Strategies for Lithium-Ion Batteries Based on MCC-CV

Abstract

The widespread deployment of lithium-ion batteries (LIBs) in electric vehicles and energy storage systems urgently requires advanced fast-charging strategies that simultaneously improve charging efficiency and cycle durability. Traditional multi-stage constant-current constant-voltage (MCC-CV) charging optimization generally adopts fixed objective weights and ignores the time-varying aging characteristics of batteries throughout their lifecycle, leading to unbalanced performance among charging speed, temperature rise, and capacity degradation. To address this issue, this study proposes a novel dynamic multi-objective optimization framework for MCC-CV fast charging based on an electro-thermal coupled two-stage aging model that distinguishes linear SEI-dominated aging and accelerated lithium-plating-induced aging. A non-dominated sorting genetic algorithm (NSGA-II) is utilized to optimize the charging time and capacity fading with adaptive weight adjustment. The charging strategy is dynamically updated periodically according to the real-time battery aging state until the end-of-life criterion is satisfied. Five charging strategies are compared in terms of charging time, capacity fading, and maximum temperature rise. Compared with the baseline strategy (S1-1), the proposed S4 strategy reduces average charging time by 21.017% but induces higher temperature elevation and accelerated aging. The improved dynamic optimization strategy (S5), which adjusts optimization objectives and weights according to different aging stages, reduces average charging time by 16.983% while achieving the lowest maximum temperature rise among fast-charging strategies and effectively suppressing battery aging in the second stage. The proposed adaptive dynamic optimization method outperforms both static and conventional fixed-weight dynamic MCC-CV strategies, providing a reliable and balanced fast-charging solution that synergistically enhances charging efficiency, thermal safety, and cycle life of LIBs.