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Faculty of Graduate Studies

Akanksha

  • BTech (Punjab Engineering College, 2023)

Notice of the Final Oral Examination for the Degree of Master of Applied Science

Topic

Adaptive and Predictive Control of Wireless Power Transfer Systems for Light Electric Vehicle Charging

Department of Electrical and Computer Engineering

Date & location

  • Wednesday, August 26, 2026

  • 11:00 A.M.

  • Virtual Defence

Reviewers

Supervisory Committee

  • Dr. Ilamparithi Thirumarai Chelvan, Department of Electrical and Computer Engineering, University of Victoria (Supervisor)

  • Dr. Navneet Popli, Department of Electrical and Computer Engineering, UVic (Member) 

External Examiner

  • Prof. Qingsong Wang, Electrical Engineering, École de Technologie Supérieure 

Chair of Oral Examination

  • Dr. Jaya Prakash Champati, Department of Computer Science, UVic 

Abstract

Wireless power transfer (WPT) chargers for light electric vehicles (LEVs) experience variations in magnetic coupling due to coil misalignment, which can degrade current regulation dynamics and increase convergence time during transient operation. Although conventional fixed-gain controllers can achieve current regulation under nominal conditions, their fixed parameters may limit performance when the coupling condition changes. This thesis investigates adaptive and predictive control strategies for a phase-shifted full-bridge (PSFB)-based WPT charger to improve transient response and robustness under aligned and misaligned operating conditions.

A laboratory-scale series-series compensated prototype operating at 85 kHz was implemented with a PSFB inverter, resonant tank, rectifier, sensing interface, wireless communication link, and lithium-ion battery load. Two controllers were developed and compared with fixed-gain proportional-integral (PI) control: a Twin Delayed Deep Deterministic Policy Gradient (TD3)-based adaptive PI controller and a model predictive controller (MPC). Under aligned, lateral misalignment, and angular mis alignment conditions, the TD3 controller reduced convergence time from 8.50 ms to 5.95 ms, 17.00 ms to 11.05 ms, and 26.00 ms to 14.82 ms, achieving improvements of 30.0%, 35.0%, and 43.0%, respectively. The MPC achieved the best performance, reducing convergence time to 4.80 ms, 9.03 ms, and 13.20 ms, corresponding to improvements of 43.5%, 46.9%, and 49.2%, respectively. These results demonstrate that adaptive and predictive control strategies improve transient response and maintain robust current regulation under varying coupling conditions in LEV WPT systems.

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