Multi-stage constant current charging strategies mostly use global optimization algorithms to find the currents in each section. However, there are deficiencies in the weight coefficient setting and solution stability of the objective function, resulting in the charging current sequence not being able to better meet the requirements. The objective function was set as a weighted form of charging time and energy loss, and the optimal adjustment rule of the weighting factor is derived through fuzzy logic to guide the search path of the Whale Optimization Algorithm (WOA), and introduces nonlinear convergence factors and diversity mutation operations. Improve optimization capabilities and obtain segmented optimized charging current. The average temperature rise of optimized charging is 36.3% lower than 1C constant current charging, that is, the interior resistance of the cell consumes less energy; compared with traditional five-stage charging, the charging time is shortened by 12.8% and the energy loss is lower by more than 3.4%.
Lithium-ion battery charging method based on improved whale optimization algorithm
2023-10-11
2722308 byte
Conference paper
Electronic Resource
English
Improved NSGA-II algorithm-based battery swap station charging and swap strategy optimization method
European Patent Office | 2025
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