Wireless charging technology presents an ideal fit for autonomous electric vehicles for realizing a fully automated system (vehicle and charger). This article presents a planning optimization analysis for a pilot project of in-route wireless charging infrastructure serving fixed-route on-demand shared automated electric shuttles (SAESs) at Greenville, SC, USA. A single-objective nonlinear mixed integer system planning optimization problem is formulated. A comprehensive cost model representing the overall inductively charged SAESs system is developed, considering road construction, power electronics and materials, traction battery, and installation costs. The optimization problem is solved to determine the best combination of the system key design parameters (number and allocations of wireless chargers, charging power level, track length, and on-board battery capacity) that show the most cost-effective solution and allow the SAESs to achieve charge-sustaining operation. The planning platform incorporates representative simulated traffic data (driving speed and routes) for four SAESs in the Greenville using the Simulation of Urban Mobility tool. These data are fed to a vehicle powertrain model and a wireless charger power model to predict the battery power, energy and state-of-charge profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. The results indicate that implementing high-power (100 kW) wireless charger at a few designated stops for fixed-route SAESs with the proper track length allows the vehicles to realize charge-sustaining operation, infinite range, and zero recharge downtime, with a significant reduction in the on-board battery (36%) and road coverage (69%), at minimum cost.

中文翻译：

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南卡罗来纳州格林维尔感应充电按需自动电动班车项目的规划优化

无线充电技术是自动电动汽车实现全自动系统（车辆和充电器）的理想选择。本文介绍了在美国南卡罗来纳州格林维尔为固定路线按需共享自动电动班车 (SAES) 提供服务的在途无线充电基础设施试点项目的规划优化分析。提出了一个单目标非线性混合整数系统规划优化问题。考虑到道路建设、电力电子和材料、牵引电池和安装成本，开发了代表整个感应充电 SAES 系统的综合成本模型。解决优化问题，确定系统关键设计参数（无线充电器的数量和分配、充电功率水平、轨道长度、和车载电池容量），显示出最具成本效益的解决方案，并允许 SAES 实现充电持续运行。规划平台使用城市交通模拟工具整合了格林维尔四个 SAES 的代表性模拟交通数据（行驶速度和路线）。这些数据被馈送到车辆动力系统模型和无线充电器功率模型，以预测电池功率、能量和充电状态曲线，这些数据被提供给搜索算法以评估特定约束下的设计目标。结果表明，在具有适当轨道长度的固定路线 SAES 的几个指定站点实施大功率（100 kW）无线充电器可以使车辆实现充电持续运行、无限范围和零充电停机时间，