Multistage fast charging optimization protocol for lithium-ion batteries based on the biogeography-based algorithm

Lithium-ion batteries play an important role in the application scenarios of electric vehicles and renewable energy systems. However, it is difficult to charge these batteries safely and quickly. Charging lithium-ion batteries has been the bottleneck problem affecting the large-scale application of electric vehicles. To find a balance between safety and speed, this study proposes a multistage fast charging protocol utilizing the biogeography-based optimization (BBO) algorithm. The optimization function of the charging time and the temperature rise of lithium-ion batteries are established through the thermoelectric coupling model of lumped parameters. In the example of a five-stage charging protocol, the Pareto front is obtained using the BBO algorithm and is composed of the optimal solutions of the two objectives under different weights. Subsequently, the optimal solution that minimizes the global optimization function is obtained. Compared with the multistage constant current charging protocol, the results show that the BBO charging optimization protocol shortens the battery charging time by 19.13% whereas the maximum temperature increase remains nearly identical. • A Biogeography-Based Optimization (BBO) algorithm was introduced to solve the problem of battery charging optimization. • A balanced charging strategy with the shortest charging time and the smallest temperature rise was studied, and the battery capacity loss was introduced as an evaluation index. • The BBO algorithm introduced enriches the choice of battery fast charging field.