IET Electric Power Applications · 2020 · 24 citations · 27 references
EngineeringElectrical EngineeringMechatronics EngineeringElectric Vehicle TechnologyInternet Of ThingsMachine VisionCharging SystemsElectric Vehicle ElectronicsFast Charging TechnologiesIot Embedded SystemsMagnetic SensorsWireless Power TransferInductive Power TransferMachine Vision SensorsMachine Vision SystemsMagnetic FluxMagnetic Flux DensitySensingSmart ChargingWireless Power Transfer Control
Electric vehicle (EV) technology proposed itself as a great solution for the predictable shortage in traditional energy sources. Using wireless power transfer (WPT) technology for charging the battery can be considered as a good solution to overcome the battery charging time problem. The considered WPT technique in this research is an inductive magnetic resonance (IMR). The problem now is to design a smart controller system that enables the EVs to obtain the optimum value of WPT by using the machine vision and the technology of Internet of Things (IOT). The utilisation technique of the maximum WPT in this research based on the simulation study of the magnetic flux density between the sending and receiving coils of the WPT system. Maximum efficiency of IMR method depends directly on the ideality of coils alignment. To achieve this alignment, a smart controller has been introduced with four integrated controlling layers. Coordinating an image processing technique with smart embedded sensing elements is considered the main solution key to better positioning. National instrument packages NI LabVIEW and NI vision are considered to fully control the system. NI Data Dashboard enables creating a wireless link using the concept of IOT to a smartphone running simple graphical user interface.
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Jaegue Shin, Seungyong Shin, Yang-Su Kim et al. · IEEE Transactions on Industrial Electronics · 2013 · 854 citations
Engineering, Automotive Engineering, Electrical Engineering +17