Abstract
Deploying shared automated electric vehicles (SAEVs) on current roadways in cities will significantly shape current transportation systems and make our urban mobility systems more efficient, convenient, and environmentally friendly. Utilizing wireless power transfer (WPT) technology to charge the SAEVs provides perfect fits for realizing a fully automated mobility system. However, the investment in wireless charging infrastructure (WCI) presents a critical barrier for commercializing and adopting this technology. The barrier can be cleared by realizing the proper design of the WPT system that maximizes the benefits and minimizes the cost of WCI at the same time. This paper introduces a system design optimization tool and methodology for WCI for serving fixed-route SAEVs in automated mobility districts (AMDs). The tool offers the capability of integrating driving data (simulated or collected from the real world), vehicle parameters (e.g., battery, motor, dimensions, and so on), and wireless charger characteristics (rate, locations, alignment, and so on) to generate energy and state-of-charge profiles for each vehicle, considering motoring, regenerative braking, and charging. Furthermore, the proposed tool incorporates a multi-objective optimization layer for searching the optimum design parameters based on predefined objectives and constraints. The proposed method was utilized to design the WCI for a hypothetical AMD scenario with four SAEVs. The outcomes show that implementing in-route wireless chargers at designated stops for the SAEVs with maximum power level has the potential to provide a charge sustaining operation with 52% reduction in the on-board battery and presents the most cost-effective solution. The proposed solution is assessed in comparison with other charging technologies, such as stationary WPT and dc fast charging, and it shows the most feasible option for an AMD network in terms of cost, convenience, and performance.
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