To address the battery-related shortcomings of battery electric buses (BEBs), dynamic wireless charging (DWC) technology that allows BEBs to charge while in motion has emerged, thereby extending the driving range and reducing the size of onboard batteries. The introduction of DWC technology raises a critical problem, namely, the deployment of DWC facilities. To resolve the infrastructure planning problem, this study first proposes a (higher-level) strategic planning model that optimizes the deployment of DWC facilities and battery capacity of BEBs, and then establishes a (lower-level) tactical planning model of optimal charging scheduling under the time-of-use (TOU) tariff mechanism considering the interdependence between infrastructure design and charging activities of BEBs. Mixed-integer nonlinear programming (MINLP) is proposed to optimize the model, aiming to minimize the overall cost associated with charging facilities, batteries, and charging. The proposed optimization model is tested and evaluated using a real-world bus system network, and the results demonstrate that the model effectively determines the DWC facility locations and battery sizes and optimizes the charging scheduling considering the TOU tariff for BEBs. The proposed model in this study provides a comprehensive guideline for relevant practitioners and further promotes the application of DWC technology in BEBs.

为了解决纯电动公交车（BEB）与电池相关的缺点，动态无线充电（DWC）技术应运而生，该技术允许BEB在行驶中充电，从而延长行驶里程并缩小车载电池的尺寸。DWC技术的引入提出了一个关键问题，即DWC设施的部署。为了解决基础设施规划问题，本研究首先提出了优化 DWC 设施和 BEB 电池容量部署的（高层）战略规划模型，然后建立了在考虑BEB基础设施设计和收费活动之间相互依赖的分时电价机制。提出了混合整数非线性规划（MINLP）来优化模型，旨在最小化与充电设施、电池和充电相关的总体成本。使用真实的公交系统网络对所提出的优化模型进行了测试和评估，结果表明该模型有效地确定了 DWC 设施位置和电池尺寸，并考虑了 BEB 的分时电价优化了充电调度。本研究提出的模型为相关从业者提供了全面的指导，并进一步推动了DWC技术在BEB中的应用。