Design Optimization of Inductive Power Transfer Systems for Contactless Electric Vehicle Charging Applications

Authors

Masood Moghaddami, Florida International UniversityFollow

Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Electrical Engineering

First Advisor's Name

Arif Sarwat

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Osama Mohammed

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Nezih Pala

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Sakhrat Khizroev

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

Francisco de Leon

Fifth Advisor's Committee Title

Committee Member

Keywords

control, electric vehicle, power electronics, inductive power transfer, magnetics, wireless power transfer

Date of Defense

10-18-2018

Abstract

Contactless Electric Vehicle (EV) charging based on magnetic resonant induction is an emerging technology that can revolutionize the future of the EV industry and transportation systems by enabling an automated and convenient charging process. However, in order to make this technology an acceptable alternative for conventional plug-in charging systems it needs to be optimized for different design measures. Specifically, the efficiency of an inductive EV charging system is of a great importance and should be comparable to the efficiency of conventional plug-in EV chargers.

The aim of this study is to develop solutions that contribute to the design enhancement of inductive EV charging systems. Specifically, generalized physics-based design optimization methods that address the trade-off problem between several key objectives including efficiency, power density, misalignment tolerance, and cost efficiency considering critical constraints are developed. Using the developed design methodology, a 3.7kW inductive charging system with square magnetic structures is investigated as a case study and a prototype is built to validate the optimization results. The developed prototype achieves 93.65% efficiency (DC-to-DC) and a power density of 1.65kW/dm³.

Also, self-tuning power transfer control methods with resonance frequency tracking capability and bidirectional power transfer control are presented. The proposed control methods enhance the efficiency of power converters and reduce the Electromagnetic Interference (EMI) by enabling soft-switching operations. Several simplified digital controllers are developed and experimentally implemented. The controllers are implemented without the use of DSP/FPGA solutions. Experimental tests show that of the developed simplified controllers can effectively regulate the power transfer around the desired value. Moreover, the experiments show that compared to conventional converters, the developed converters can achieve 4% higher efficiency at low power levels.

Moreover, enhanced matrix converter topologies that can achieve bidirectional power transfer and high efficiency with a reduced number of switching elements are introduced. The self-tuning controllers are utilized to design and develop control schemes for bidirectional power transfer regulation. The simulation analyses and experimental results show that the developed matrix converters can effectively establish bidirectional power transfer at the desired power levels with soft-switching operations and resonance frequency tracking capability. Specifically, a direct three-phase AC-AC matrix converter with a reduced number of switches (only seven) is developed and built. It is shown that the developed converters can achieve efficiencies as high as 98.54% at high power levels and outperform conventional two-stage converters.

Identifier

FIDC007049

ORCID

https://orcid.org/0000-0002-9414-6486

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Recommended Citation

Moghaddami, Masood, "Design Optimization of Inductive Power Transfer Systems for Contactless Electric Vehicle Charging Applications" (2018). FIU Electronic Theses and Dissertations. 3853.
https://digitalcommons.fiu.edu/etd/3853