The search for eco-friendly means of transportation is significantly increasing, causing the demand for electric vehicles (EVs) to skyrocket. However, the main limitation that is slowing down the adoption of electric vehicles is range anxiety, where users are discouraged to drive an electric vehicle (EV) due to fear of running out of charge mid-trip. This revealed the need for implementing better EV charging solutions including dynamic wireless charging systems. Dynamic Wireless Charging (DWC) exploits wireless power transfer (WPT) to deliver electrical energy from the grid to the EV while in motion, via wireless charging lanes (WCL) placed on the roads. In addition to reducing range anxiety, DWC also eliminates the need for charging downtime. However, expensive infrastructure is needed to deploy the necessary hardware needed for DWC, which explains the need for optimizing the deployment locations of the charging lanes along with the corresponding lane lengths and charging power levels. In this work, the objective of the deployment optimization framework is to minimize the total system costs. The optimization framework is formulated based on traffic simulation data for the city of Sharjah. The problem is then solved using the metaheuristic genetic algorithm to provide recommendations on the most suitable locations to deploy the charging lanes within the traffic map under consideration.


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    Titel :

    Deployment Optimization of Dynamic Wireless Chargers for Electric Vehicles


    Beteiligte:


    Erscheinungsdatum :

    15.06.2022


    Format / Umfang :

    1604625 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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