Santos Euler B P, Castro Carlos A
Pontifical Catholic University of Campinas (PUC-Campinas), Campinas, Brazil.
Sci Rep. 2025 Jul 1;15(1):21031. doi: 10.1038/s41598-025-06788-y.
The automotive market is moving fast towards electric vehicles (EV). The ever-growing EV technology and associated service infrastructure, appropriate policies and regulations among other factors are increasing the user's acceptance and confidence in the EV industry, resulting in the growth of EV sales. The existing barriers to the expansion of EV sales such as relatively high purchase prices, the small number of charging stations, uneven distribution of charging stations, and charging times, tend to disappear over time and the expectation is that soon EVs will constitute a significant share of new car sales globally. This work tackles specifically the charging time problem and proposes solutions for coordinating the charging of a group of electric vehicles in a charging station based on the metaheuristic teaching-learning-based optimization (TLBO) and on a specialized heuristic technique. The proposed methods seek to deliver as much energy as possible to vehicles' batteries without violating the constraints and limits of the distribution grid. TLBO is an efficient metaheuristic algorithm that requires few tuning parameters and does not depend on historical data to obtain an optimal solution for an optimization problem. Also, the specialized heuristic technique makes use of specific knowledge about the optimal charging problem to obtain a fast, high-quality solution. Simulation results obtained from the TLBO algorithm are presented alongside those from the heuristic method, with discussions, performance comparisons, and recommendations for practical applications. It will be seen that the proposed approaches are able to meet the efficiency requirement expected by EV customers.
汽车市场正迅速向电动汽车（EV）转型。不断发展的电动汽车技术、相关服务基础设施、适当的政策法规等因素，正提高用户对电动汽车行业的接受度和信心，推动电动汽车销量增长。电动汽车销售扩张存在一些障碍，如较高的购买价格、充电桩数量少、分布不均以及充电时间长等，但随着时间推移这些障碍往往会消失，预计电动汽车很快将在全球新车销售中占据显著份额。这项工作专门解决充电时间问题，并基于元启发式基于教学学习的优化（TLBO）和一种专门的启发式技术，提出了在充电站协调一组电动汽车充电的解决方案。所提出的方法旨在在不违反配电网约束和限制的情况下，尽可能多地为车辆电池输送能量。TLBO是一种高效的元启发式算法，所需调整参数少，且不依赖历史数据来获得优化问题的最优解。此外，专门的启发式技术利用关于最优充电问题的特定知识来获得快速、高质量的解决方案。给出了从TLBO算法获得的仿真结果以及启发式方法的仿真结果，并进行了讨论、性能比较以及对实际应用的建议。可以看出，所提出的方法能够满足电动汽车客户预期的效率要求。
