High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. The comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

车辆和充电基础设施的高昂前期成本以及基础设施规划和电动公交系统运营相关知识的缺乏是实施纯电动公交车 (BEB) 的主要障碍。为了克服障碍并促进 BEB 的采用，开发了一个综合优化框架来解决 BEB 系统的充电基础设施规划、车辆调度和充电管理的综合问题，目标是最大限度地降低总拥有成本。该问题被表述为混合整数非线性问题。然后提出了一种基于遗传算法的方法来解决这个问题。最后，基于犹他州盐湖城的一个次级公交网络，分析了三种替代方案，并与数值实验中的最佳方案结果进行了比较。