User-Demand-Oriented Healthy Charging Control Strategy for EVs Based on Football Team Training Algorithm

With the rapid development of the electric vehicle (EV) market, effective charging control is essential for enhancing user experience and preserving battery health. Across various scenarios, this work proposes a user-demand-oriented healthy charging control strategy that balances charging efficiency and battery lifespan using the football team training algorithm (FTTA). Firstly, an enhanced hybrid stacking–boosting ensemble (EHSBE) model is designed to predict user charging duration through different feature selections and a hybrid framework. Secondly, a healthy charging control strategy based on the FTTA is developed. This strategy addresses a multi-objective optimization problem, considering two charging objectives: completing the charging task and reducing energy loss, as well as three safety-related constraints. The algorithm achieves a healthy strategy through interaction and iterative refinement among potential solutions. Simulation and experimental results show that the proposed strategy significantly reduces energy loss, generating only 5.8% and 24% of the energy loss generated by the fast charging approach under two different durations. With user expectations and maintenance of battery health, the charging process is optimized so that battery life is extended by 25.7% and user demand is satisfied.