Health-aware multi-stage charging strategy for lithium-ion batteries based on whale optimization algorithm

Lithium-ion batteries are widely used in electronics, new energy electric vehicles and energy storage plants. They have become ideal energy storage devices for their excellent characteristics of high energy density, low self-discharge rate, low carbon and environmental protection. Thus, research on lithium-ion batteries has wide scientific and engineering significance. To promote the application of lithium-ion batteries, the charging speed and aging rate of the lithium-ion batteries should be optimized to improve the convenience and economics for using them. Therefore, in this paper, a health-aware multi-stage charging strategy is presented based on the whale optimization algorithm. Specifically, the electrical model, thermal model, and the semi-empirical aging model are established firstly. Then the multi-stage charging optimization strategy considering charging time and battery health loss is proposed. The whale optimization algorithm is presented to obtain the optimal current value at each stage, followed by exploring the factors affecting the charging performance which include fitness function weight, cut-off voltage and current stage number. Compared with constant current (CC) charging, the total fitness function loss decreased by 34.64%, and the charging time decreased by 11.45%. This paper provides audiences with a strategy to meet the trade-off between charging rapidity and battery life in different scenarios by setting the optimization weights.