EV Wireless Inductive Power Pad and Resonant Magnetic Field Coupling Multiple Unit Station

The high rate of the electric vehicle (EV) adoption increased the pressure of finding the efficient and convenient to use and reliable types of charging technologies. The traditional plug-in charging solutions have the drawbacks of connector wear, environmental interaction and exposure, inconvenience to the user and limited accessibility. To eliminate these drawbacks, this project suggests and designs a 4-wheel electric vehicle wireless charging system based on the concept of resonant inductive coupling with several transmission pads. The proposed system incorporates two or three copper-based transmission pads beneath the charging surface and they produce a high-frequency alternating magnetic field. This magnetic flux is then picked up by corresponding receiver coils installed under the electric vehicle and converted into electrical energy that is used to charge up the battery. At a resonant frequency, the system greatly increases the power transfer efficiency and allows efficient transfer of energy over a specified air gap without the need to touch.This design provided several transmission pads, which are the main characteristic of a design, so that it is more tolerant to misalignment of the vehicle and changes in the parking position. The multi-pad design guarantees a closer distribution of the magnetic field to create a balanced power distribution to the battery system and less power loss when compared to single-pad wireless charging systems. Moreover, the modular pad system can scale the power level and can be used in a flexible deployment in both residential and public charging applications. The system architecture comprises of the high frequency inverter, resonant compensation networks, rectification and regulation phases and battery management interface to provide safe and efficient charging. The parameters that performance analysis is concerned with include the efficiency of coupling, power transfer ability, alignment tolerability and thermal characteristics of the coils. The experiment using a scaled version has shown credible results of wireless power transfer, increased flexibility of alignment and constant stationary charging..

Electric Vehicle (EV), Wireless Power Transfer (WPT), Resonant Inductive Coupling, Wireless EV Charging

1. L. Cheng, Y. Chang, Q. Wu, W. Lin, and C. Singh, “Evaluating charging service reliability for plug-in EVs from the distribution network aspect,” IEEE Transactions on Sustainable Energy, vol. 5, no. 4, pp. 1287–1296, 2014. [Google Scholar] [Crossref]

2. N. Xu and Y. Chung, “Reliability evaluation of distribution systems including vehicle-to-home and vehicle-to-grid,” IEEE Transactions on Power Systems, vol. 31, no. 1, pp. 759–768, 2016. [Google Scholar] [Crossref]

3. Alah Yari, M. Fotuhi-Firozabad, and M. Rastegar, “Incorporating customer reliability cost in PEV charge scheduling schemes considering vehicle-to-home capability,” IEEE Transactions on Vehicular Technology, vol. 64, no. 6, pp. 2783–2791, 2015. [Google Scholar] [Crossref]

4. S. Habib, M. Kamran, and U. Rashid, “Impact analysis of vehicle-to-grid technology and charging strategies of electric vehicles on distribution networks—A review,” Journal of Power Sources, vol. 277, pp. 205–214, 2015. [Google Scholar] [Crossref]

5. M. Ansari, A. Al-Awami, E. Sortomme, and M. Abido, “Coordinated bidding of ancillary services for vehicle-to-grid using fuzzy optimization,” IEEE Transactions on Smart Grid, vol. 6, no. 1, pp. 261–270, 2015. [Google Scholar] [Crossref]

6. L. Hua, J. Wang, and C. Zhou, “Adaptive electric vehicle charging coordination on distribution network,” IEEE Transactions on Smart Grid, vol. 5, no. 6, pp. 2666–2675, 2014. [Google Scholar] [Crossref]

7. Antúnez, J. F. Franco, M. J. Rider, and R. Romero, “A new methodology for the optimal charging coordination of electric vehicles considering vehicle-to-grid technology,” IEEE Transactions on Sustainable Energy, vol. 7, no. 2, pp. 596–607, 2016. [Google Scholar] [Crossref]

8. N. Xu and Y. Chung, “Well-being analysis of generating systems considering electric vehicle charging,” IEEE Transactions on Power Systems, vol. 29, no. 5, pp. 2311–2320, 2014. [Google Scholar] [Crossref]

9. W. Su and M. Chow, “Performance evaluation of a PHEV parking station using particle swarm optimization,” in Proceedings of the IEEE Power and Energy Society General Meeting, pp. 1–6, 2011. [Google Scholar] [Crossref]

10. V. Aravinthan and W. Jewell, “Controlled electric vehicle charging for mitigating impacts on distribution assets,” IEEE Transactions on Smart Grid, vol. 6, no. 2, pp. 999–1009, 2015. [Google Scholar] [Crossref]

11. Dellinger, D. Krampe, and M. Weinschel, “Vehicle-to-grid regulation reserves based on a dynamic simulation of mobility behaviour,” IEEE Transactions on Smart Grid, vol. 2, no. 2, pp. 302–313, 2011. [Google Scholar] [Crossref]

12. Corchero, M. Cruz-Zambrano, H. Miguel, and F. Heredia, “Optimal energy management for a residential microgrid including a vehicle-to-grid system,” IEEE Transactions on Smart Grid, vol. 5, no. 5, pp. 2163–2172, 2014. [Google Scholar] [Crossref]

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