Abstract
The fossil fuel scarcity worldwide has rapidly driven the electric vehicles and battery charging technologies, including contactless power transfer (CPT), over the past decades. There still exist many technical difficulties to be specifically addressed and ideas to be innovatively achieved although a lot of contribution on EVs charging solutions has been made by the engineering world. In this paper, the comparatively up to date CPT technologies for EVs charging were investigated and the project methodology was discussed from the aspects of maximizing the charging system efficiency, power transfer rating levels and air gaps of charging coupling coils. Until present, the different coil designs, ferrite core deployments, operating frequencies and air gaps are acting as the main investigation factors regarding producing transfer efficiencies and power ratings on the load end. By modeling and simulating the electromagnetic field couplings with the simplified inductive transmitting system in 3D finite-element methods based environment, an Axis-to-Axis (Coaxial) rectangular coil CPT system and an Axis-Parallel (Non-coaxial) rectangular coil system have been modeled and quantitatively compared. Besides, an axis-parallel coil system and a C-Type rectangular coil system deploying ferrite cores with 50 mm air gap have been analyzed, resulting in output efficiencies over 85% and 74%, respectively. In addition, the effectiveness of using a ferrite core to improve the flux linkage and magnetic flux density can be noticed. From the perspective of electromagnetic field, the contributions of deploying natural resonant frequencies of transmitting ground side and receiving vehicle side in terms of system efficiency, magnetic field strength generated and actual power transfer ratings have been described.
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Duan, J., Wang, W. (2019). Electromagnetic Coupling Optimization by Coil Design Improvements for Contactless Power Transfer of Electric Vehicles. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Proceedings of the Future Technologies Conference (FTC) 2018. FTC 2018. Advances in Intelligent Systems and Computing, vol 881. Springer, Cham. https://doi.org/10.1007/978-3-030-02683-7_69
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DOI: https://doi.org/10.1007/978-3-030-02683-7_69
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