Lithium-ion battery charging optimization based on electrical, thermal and aging mechanism models

The development of power batteries has driven the popularity of electric vehicles (EVs). For EV, charging management directly affects battery pack performance and vehicle portability. In this paper, a multi-stage constant current charging mode considering the temperature rise, health loss, and charging time is proposed. Based on the equivalent circuit model, thermal model and aging empirical model of the battery, the objective function of charging optimization is constructed. The solution is solved by with different optimization algorithms. A comparative analysis of the different solutions on the Pareto front is performed, and the optimization results show that the non-dominated sorting genetic algorithm-II (NSGA-II) results are significantly better than the non-dominated sorting moth flame optimization (NSMFO). Finally, comparing the optimization results with the conventional constant current (CC) charging method shows that the charging optimization algorithm proposed in this work is able to reduce health loss and temperature rise. Although, there is a mutually binding relationship between charging time, temperature rise and health loss. However, the best charging optimization can be obtained on the Pareto front according to different charging requirements.